This paper provides evidence of heterogeneous human-capital externality using CHIP 2002, 2007, and 2013 data from urban China. After instrumenting city-level education using the number of relocated university departments across cities in the 1950s, one additional year of city-level education increases individual hourly wages by 22.0 percent, more than twice the OLS estimate. Human-capital externality is greater for all groups of urban residents in the instrumental variables estimation.
Many people do not like large cities because they think large population is associated with so-called urban diseases like congestion, pollution, crime, and expensive housing. The worry about large cites leads to policies which aim to restrict their population growth. Although it’s very hard to control domestic migration in most of the countries in the world, China, which has a powerful government, is still using the Hukou system (household registration system) to discriminate migrants in large cities. However, people from rural areas and small- and medium-sized cities are still heading for large cities all over the world. In recent researches, economists have both theoretically and empirically argued that human capital externalities promote knowledge spillover, productivity, and income growth (Lucas, 1988; Rauch, 1993; Moretti, 2004) that can explain the population growth in large cities.
Over the past thirty years, China’s average years of schooling have increased from 3.7 to 7.5 (Barro and Lee, 2011), yet in the same period, China’s per capita GDP has gone up by more than 1200 percent. If there is a large role for human-capital externalities, then education’s aggregate impact must be vastly larger than its individual impact, which suggests that education has played a significant role in China’s rapid growth. Human-capital externalities can also help to explain why returns to higher education keep rising, even though the number of college graduates has increased to roughly seven million in 2017—a great expansion from the one million graduates in the late 1990s (Liang and Lu, forthcoming).
If we follow Rauch (1993) and estimate human-capital spillovers using individual-level data from the 2002, 2007, and 2013 Chinese Household Income Project Surveys (CHIP2002, CHIP2007, CHIP2013) for urban households, we find that for every extra year of schooling at the city level, individual hourly earnings increase by 8.36 percent, holding individual-level and other city-level characteristics constant. For male workers, one year of city-level schooling increases earnings by 9.19 percent. For female workers, one year of city-level schooling increases earnings by 7.06 percent when we consider total salaries for female workers. If anything, the benefits of area-level education appear to be stronger for less educated workers in terms of both magnitude and statistical significance.
As Acemoglu and Angrist (2001) and others have emphasized, there are significant problems with regressing individual earnings on average years of schooling: omitted unobserved human capital and omitted area-level characteristics. Places with unobserved advantages in economic opportunity might also attract workers who are more skilled along unobserved dimensions, which would bias the coefficient upwards. Places with more consumption amenities might also attract more educated workers, and such amenities are typically associated with lower wages in a spatial equilibrium. If the location of skilled workers is fixed, then added migration of less skilled workers to more productive areas could lead toward downward bias in the OLS coefficient, since more productive areas will have a lower average skill level.
There are two typical approaches to address these biases: shocks to people and shocks to place. Shocks to people, like the U.S. Moving to Opportunity Experiment, randomly allocated people across space, which addresses unobserved personal attributes. Shocks to places, like the compulsory schooling laws used by Acemoglu and Angrist (2001), or the location of land-grant colleges used by Moretti (2004), address omitted place-based characteristics, but typically cannot address subsequent sorting on unobservables.
The nation-wide movement of reallocating university departments at the founding of the People’s Republic of China provides a unique opportunity for us to address both forms of omitted characteristics simultaneously. During the early years of communism, some areas experienced a radical reduction in their local educational institutions, for largely political reasons, while other areas saw their educational institutions grow, again largely because of politics. The influence of the former Soviet Union persuaded Chinese leaders to follow their highly specialized university system, which focused on concrete skills rather than liberal arts. Moreover, to spread communist ideology, the Party wanted to remove the influence of the pre-existing education system.
To carry out the plan of relocating university departments, the central government established the Ministry of Higher Education in 1952. With the support of local governments, the nation-wide movement of reallocating university departments was almost realized in 1952. The relocation occurred not only across institutions, but also across regions. Staff and students, as well as facilities and libraries, were moved. Among the 502 departments moved out of a school, 282 moved to different cities. Among the 623 departments moved in, 333 came from a different city. The discrepancy between the number of departments moved in and out reflects the creation, destruction, division, and merging of departments. These changes are robustly correlated with education levels today—each extra department is associated with about 0.032 extra years of average schooling in the area— but not correlated with city characteristics in 1953. Moreover, these department relocations are uncorrelated with investments in infrastructure or capital during the 1950s and 1960s. The economic development strategy during the Great Leap Forward was focused on industrialization, not education.
Consequently, we interpret the impact of department relocations on urban-born workers in 2002 as a relatively clean experiment illustrating the impact of area-level education on individual earnings. The experiment is not perfect. We cannot be sure that the department relocations are perfectly orthogonal to all other city characteristics. We cannot be sure that there is no selective historical migration in our estimation using urban sample, although we have excluded current migrants without local Hukou. Yet given the difficulties with measuring these human-capital externalities, we believe that this provides a plausible addition to the literature.
Our OLS regression finds that one more year of city-level education is associated with an 8.4 percent increase in hourly wage. City-level education has the strongest positive effect on the least educated group of workers. Presumably, this effect reflects that while skilled people substitute for one another, an unskilled person may complement a skilled individual, either in the same firm or by providing services for the skilled. The impact of area-level education is slightly higher in manufacturing jobs, but lower in manual services and even insignificant in abstract services. The substitution effects among skilled laborers that reduce positive human-capital externalities in more skill intensive service jobs may explain these differences. This will also be revisited in the instrumental variables estimation.
Our instrumental variables estimate is that, on average, an extra year of schooling at the city level is associated with 22.0 percent higher hourly wages across cities. The heterogeneity of human capital externalities almost disappears after using IV. The measured effect is more than double the effect estimated by OLS. This larger effect could reflect omitted variables that are correlated with the instrument, but it could also reflect the true impact of area education on productivity. If less skilled people move disproportionately to more productive areas, then the true treatment effect of skills on productivity should be substantially higher than the OLS estimate. We investigate this hypothesis by examining the connection between population flows and academic relocations. We find that population growth seems to have been 1.2 percent higher between 1953-2000 for each extra academic department. The extra supply of labor force in more educated areas might readily explain why the OLS estimate is about one-half of the instrumental variables estimate.
We also examine whether these effects are stronger on the most or least skilled workers. Unlike the OLS results, the instrumental variables results suggest that area-level education has almost the same effect on differently skilled workers. The difference in coefficients is not statistically significant, but since the department shifts seem to have disproportionately attracted the more skilled, the changing pattern of heterogeneous treatment effects between the OLS and instrumental variables results is compatible with the view that extra departments attracted skilled workers who depressed wages for skilled workers.
Even if the area-level impact of years of schooling is 22.0 percent per year instead of 8.36 percent, the growth of Chinese education is still far from being able to explain the country’s massive increase in earnings. Even if a year of schooling increased earnings by 40 percent, four extra years could not explain a 1200 percent rise in per capita GDP. Considering that college graduates, together with other migrants, are moving to large cities with higher educational levels and greater human-capital externalities (Liang and Lu, forthcoming), the role of education in accelerating growth should have been more important. Another possibility is that human-capital effects at the country level are far higher than effects at the district level, but that is mere speculation.
This paper argues that not only in developed countries, but also in developing countries like China, human-capital externalities are both statistically and economically significant. In the past 40 years, China has had a great achievement of human capital accumulation. Human-capital externalities amplify the returns to education and help explain why China has grown. Yet even with these large human capital externality estimates, education does not explain all or most of China’s growth since 1990. If education explains that growth, then national returns to human capital must be even larger than the regional returns to human capital. Because the large cities are the places with strong human capital externalities and play a leading role in modern economic growth, the policies restricting population in large cities may undermine their productivity and consequently the whole country’s growth.
Authors’ note: The authors gratefully acknowledge funding by the National Social Science Funds (13&ZD015). This research is also supported by Shanghai Institute of International Finance and Economics and Fudan Lab for China Development Studies. We thank Wenquan Liang and Hong Gao for their excellent research assistance. All remaining errors are our own.
This article is a reprint with minor revisions from the VoxEU article published at https://voxeu.org/article/human-capital-externalities-china. The authors are grateful to the permission given by VoxEU.org to publish this article.
(Edward L. Glaeser, Department of Economics, Harvard University; Ming Lu, China Centre for Development Studies at Shanghai Jiao Tong University.)
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