How Inequality is Undermining China’s Prosperity


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  • Scott Rozelle
    Scott Rozelle is the senior Fellow at the Freeman Spogli Institute for International Studies and Co-director at Stanford Center on China’s Economy and Institutions. His specialization and focus is in Chinese agricultural policy, including the supply, demand, and trade in agricultural projects; the emergence and evolution of markets and other economic institutions in the transition process and their implications for equity and efficiency; and the economics of poverty and inequality, with an emphasis on rural education, health and nutrition.
A bicycle repair man waits for customers at a streetcorner in Beijing on March 2, 2010, near the China Central Television Headquarters.
FRED DUFOUR/AFP via Getty Images

China’s Inequality Challenge

Chinese policymakers are confronting a visibly faltering economy that may no longer grow at the rate needed to achieve the country’s development goals. The challenge is compounded by the country’s persistent inequality.

Stanford University professor Scott Rozelle and his research collaborators at other universities around the world have been at the forefront of research on inequality and work in both rural and urban China for decades. Data they have collected on wages, education, and labor markets highlight some of the challenges posed to China’s development by stubbornly high levels of inequality.

Changes in the labor market are leading to a rapid increase in the number of workers entering the less secure informal economy, while employment in the formal manufacturing sector, once the foundation of China’s employment, is falling. Moreover, continued inequality in access to education and healthcare means that many employees lack the capabilities needed to excel in the high-skilled, high-wage jobs that are appearing as China’s economy seeks to reach high-income status. Automation is also increasing in China and could further reduce employment opportunities for a sizable portion of the workforce in the years ahead.

These developments are taking place at an inflection point for China’s economy: after decades of record growth, when even the wage rates of the unskilled labor force were rising steadily, the country is now facing major headwinds. Central and local leaders will have to operate in a challenging socioeconomic environment, with lower growth, fewer stable jobs in the formal economy, especially for the unskilled segment of the manufacturing and construction sectors, and increased demand for an educated workforce. Furthermore, recent economic policies and political dynamics have in some cases increased uncertainty regarding the sustainability of economic growth.

While the central government has pursued economic upgrading by stimulating the growth of strategic high-tech sectors, it also has marginalized companies operating in growth industries, such as private tutoring, real estate, and certain kinds of internet businesses. The leadership has touted inequality as a top priority to be tackled through its Common Prosperity initiative, but this goal was barely mentioned in the 14th Five-Year Plan. And in the spring of 2022, the economy was dealt a severe blow by extended lockdowns in major cities introduced as part of the leadership’s zero-Covid strategy. All of this will likely worsen inequality and further complicate China’s economic outlook.

The latest data on inequality in China shows deep structural challenges that the country will have to address to achieve continued economic development. This has important implications for the United States, which should plan for a less economically dynamic China.

A group of Chinese migrant workers rest during their lunch break at a construction site in Beijing 05 December 2003.
GOH CHAI HIN/AFP via Getty Images

Inequality in China: The Basics

Two of the most common ways of assessing inequality are through the Gini coefficient and by comparing the shares of income received by each population quintile. The Gini coefficient is a composite measure that assigns a score to an economy between 0 and 1 based on the distribution of income. The closer the score is to 0, the more equal a society, and vice versa. A score of 0.4, which by most estimates China has surpassed years ago, is indicative of a highly unequal society. By comparison, according to the UNU-WIDER Database, countries such as Germany, Canada, and Japan all have estimated Gini coefficients that hover at just over 0.3. The United States, which is relatively more unequal than other developed economies, has consistently had a Gini coefficient below China’s (see Figure 1).

There have been multiple efforts to calculate China’s Gini coefficient. The National Bureau of Statistics (NBS) publishes its own estimates, but many observers note that NBS calculations omit important factors that are conventionally used to derive international Gini calculations and are therefore unrealistically low. Alternative estimates are based on different data sets and methods, including the well-regarded China Family Panel Studies (CFPS).

Figure 1

Given the methodological issues, the CFPS Gini is far more reliable than the NBS, and it suggests consistently high and increasing inequality. Even using China’s official numbers, however, the estimated Gini coefficients are high and not falling over time.

Figure 2
Chart showing income quintiles show inequality in China is high but stable

Income shares by quintile from the NBS show that, while highly skewed toward the top quintile, China’s income distribution also has remained fairly stable over the past decade (Figure 2). But there are aspects of inequality that are not captured by broad estimates of income distribution and inequality. Better understanding changing socioeconomic conditions in China requires delving deeper into the data.

Chinese construction workers wear protective masks as they leave a site at the end of the work day on March 20, 2020 in Beijing, China.
Kevin Frayer/Getty Images

Growing Inequality in China’s Labor Market

To appreciate the dynamics of inequality and how China’s labor force is faring, it is necessary to look at data on China’s labor market and factors driving inequality in wages. One important finding from Rozelle and his colleagues is that while employment in agriculture (the “primary sector”) continues to decline, workers are no longer flocking toward jobs in industry and construction (the “secondary sector”). In fact, job growth in the latter has plateaued since 2012. Meanwhile, employment in services (the “tertiary sector”) has grown the fastest (see Figure 3). Economic uncertainty since 2020, which has depressed investment in new construction, and manufacturing plants, means that these trends will only have accelerated in the past two years.

Figure 3
Line graph showing total employment trends in China by sector

Taking a closer look at the data reveals even more about employment trends in cities. The service sector includes a wide variety of jobs, which are usually categorized as either skill intensive (e.g., the technology, finance, culture, education, and health) or labor intensive (e.g., retail, hospitality, and logistics).

While overall service sector employment has been increasing, when disaggregated between skill-intensive and labor-intensive jobs, the latter has been growing the fastest. In fact, labor-intensive services appear to be absorbing many workers who previously went into construction and manufacturing (see Figure 4).

Figure 4
Line graph showing urban unemployment in tertiary sector industries growing while secondary sector employment stagnates

The trend is particularly striking because overall employment has also not been growing significantly in recent years. The data portrayed in Figures 3 and 4 indicate that job opportunities in manufacturing and construction are declining, which Rozelle and his colleagues expect is due to a combination of offshoring, automation, and a slowdown in new construction.

China is, in fact, no longer a low-wage, low-cost manufacturing country. As the economy boomed in the mid-2000s, wages increased, curbing demand for workers in manufacturing. As a result, labor-intensive, low-end manufacturing (e.g., textiles and electronics) has been relocating to Bangladesh, Vietnam, and elsewhere. The construction industry, a reliable driver of employment for decades, has also slowed significantly in recent years. Official Chinese data indicates that employment in the manufacturing sector has been declining since 2013. Finally, increased automation may also be hurting job opportunities for workers in lower-skilled occupations.

Importantly, the quality and security of work available to those entering the labor-intensive service sector are not equivalent to those available in manufacturing. Many labor-intensive service jobs are not regulated by the state or officially reported, meaning they are part of the informal economy. NBS data from China’s government statistical system show that informal urban employment is growing and today accounts for almost 60 percent of all non-agricultural workers, up from 40 percent 15 years ago (Figure 5). It is clear that the labor-intensive service sector—which includes a broad variety of jobs ranging from nannies and drivers to food stall workers and roadside repairmen—is driving this trend. Also, most of those working in these positions are migrants from the countryside who lack an urban residency permit (hukou), which is necessary to access a variety of welfare services, including pension benefits, healthcare insurance, and unemployment insurance.

Without formal employment, the path to acquiring an urban hukou and accessing the benefits that come with it is more arduous. The consequences are that a large segment of the population is living in relatively precarious conditions. In 2014, only an estimated 16 percent of rural migrants working in cities were covered by pension benefits, only 18 percent had urban health insurance, and only 10 percent had unemployment insurance. This points to a different source of inequality that is not captured by income trends and is harder to quantify, even though it affects people’s lives in a very direct way.

Figure 5
Line graph showing the share of urban unemployment in the informal economy is increasing

There are other disadvantages to having a shrinking share of formal employment. Countries with large and persistent informal economies often must contend with frequent tax evasion and weakened state capacity. Evidence from Mexico suggests that a large informal sector can be destabilizing and further exacerbate inequality. Similar situations are common across the middle-income world. Finally, employment in the informal sector is also correlated with higher savings rates, which households need if they lack a reliable safety net. This translates into lower consumption that could hurt growth prospects. This dynamic appears to be playing out in China.

Figure 6
Line graph showing most employment in China's informal economy is in labor-intensive services

There are close to 200 million people working in the labor-intensive informal economy today in China that are facing the challenges outlined above (see Figure 6). These workers are also facing the dual pressure of looking for jobs in an increasingly competitive landscape while also confronting slowing wage growth. As Figure 7 shows, real wages have grown less quickly in the informal economy than the formal economy and are growing slower than GDP growth.

Figure 7
Line graph showing average real wages in the informal economy are growing slower than GDP

What makes these trends particularly striking is the similarity to other middle-income countries that have struggled to achieve higher rates of development. Moreover, the data suggests that China has already started to face the same challenges in confronting manufacturing labor displacement that the United States and other advanced industrialized economies have struggled with for years due to globalization, automation, and a weak domestic social safety net.

Two factors could significantly accelerate current trends. One is the economic impact of Covid-19, including the extensive use of lockdowns and other restrictions imposed in 2022. How significantly it will impact long-term employment trends is unclear, but it will depend on government policies, global supply chains, and the speed of global and Chinese economic recovery. For example, official data show that the economy suffered and unemployment grew in April 2022 as Shanghai and other cities were placed under lockdown. As a result, the government’s goal of 5.5 percent GDP growth for 2022 will be challenging to achieve. The second, more structural trend is automation and the rapid adoption of robots in Chinese factories.

The 5G intelligent factory is high efficiently running on 18th May, 2021 in Qingdao, Shandong, China
TPG/Getty Images

The Rapid Adoption of Robots Could Accelerate Problems

There is no doubt that the use of industrial robots is expanding rapidly in China. There were 87,000 industrial robots sold in China in 2016, accounting for around 30 percent of global sales. That year, China also accounted for 19 percent of the global stock of industrial robots. The actual impact of the rapid deployment of robots in China on the labor market, though, is less clear. Some industries, such as automobiles, have a much higher penetration rate of robots than others, and the use of industrial robots may vary by region as well. Chinese observers, including official sources such as Xinhua, typically highlight the opportunities rather than the risks associated with the introduction of robots in manufacturing and even some service jobs.

Part of the challenge in assessing actual displacement is that robots have been introduced in the first place to counter labor shortages and provide an alternative to businesses offshoring in response to rising wages. Stanford professor Hongbin Li and a team of researchers, drawing on surveys conducted in 2015 in Guangdong and Hubei provinces, found that the firms most likely to introduce robots were those whose workers had already left voluntarily. In other words, the introduction of robots did not precede worker firings.

In addition to rising wages and labor shortages, Li and his co-authors also found that the other main driver for the introduction of industrial robots was government policies to stimulate the robotics industry, including subsidies. Industrial policy in this area appears to have had some success, as many of the robots deployed in China are now made domestically. In 2017, 131,000 robots were produced in the country, a 20-fold increase since 2012. That said, while the market share of domestic firms is increasing, the majority of industrial robot manufacturers in China are still foreign-invested firms. For instance, in 2017, only 29 percent of robots purchased in China in 2017 were made by domestic companies.. In any case, China’s muscular industrial policy in this area suggests that potential worker displacement may be a secondary concern.

As robots become more common, worker replacement trends may intensify. However, robots are only one aspect of automation, which is happening more broadly. It is also possible that these trends may be counteracted by the creation of more employment opportunities, especially for high-skilled workers. If more workers were to find high-skilled service jobs, this would likely enable the country to progress forward in its economic development goals. Unfortunately, shortfalls in education mean lower-skilled workers may have trouble attaining the skills to fill higher-skilled jobs.

Chinese schoolchildren attend a class at a rural elementary school in Hefei, central China's Anhui province on May 12, 2010.
AFP/AFP via Getty Images

Poor Education May Stymie China’s Growth

While automation may influence wage trends and inequality, one factor that is unequivocally critical is education. To China’s detriment, average educational attainment in the country is low by international standards. While reports on the high number of science, technology, engineering, and medicine (STEM) graduates reflect increasing investment in research and development (R&D) and STEM education, they do not represent overall educational trends across China. A large majority of individuals in China’s labor force are unlikely to even have attended high school (see Figure 8).

Data from 2015 and 2020 show that although China’s average educational attainment is increasing, it is still lower than that of other countries at comparable levels of per capita income. This suggests that workers may find it challenging to transition from low-skilled to high-skilled jobs, potentially undermining China’s transition to high-value added manufacturing.

Even more striking is a comparison with economies that reached similar levels of economic development in the past. Research on Ireland, Taiwan, South Korea, and Israel in the 1980s shows that their high school attainment was relatively high. Education attained in high school and college is typically critical for high-skilled jobs, ranging from technicians to office workers.

Figure 8

And although the government has made progress in expanding access to education, the quality of schools may be lagging. For example, a 2015 study analyzing 10,000 students in two provinces in China found that students who attended vocational schools experienced an absolute reduction in math skills and no gains in computing skills. Another comparative assessment of nationally representative samples of engineering university students in China, the United States, and Russia in 2016 also showed that Chinese students experienced no improvements in cognitive skills in the first two years of college. Russian and American students, by comparison, experienced improvements.

Figure 9
Chart of reading tests scores of students in rural China are low by global standards

Moreover, the quality of education in rural China remains especially low. A 2015 survey of 23,143 students in rural counties of three provinces—Shaanxi, Guizhou, and Jiangxi—found that they had the lowest achievement of any of the other 50+ economies participating in the Progress in International Reading Literacy Study, a reading comprehension exam (see Figure 9).

Rural education matters because over 70 percent of China’s children today are rural hukou holders. Even if parents have relocated to cities to work, without formal employment, they are unlikely to acquire the urban hukou needed to enroll their children in higher-quality, urban schools. Therefore, the increase in informal employment in China means not only that a large proportion of workers lacks access to welfare support but also that their children enrolled in rural schools are less likely to acquire the cognitive skills that are needed to succeed in high-skilled jobs.

Children in rural areas are also far more likely than their urban counterparts to experience developmental delays or suffer from health conditions such as anemia, uncorrected vision, or intestinal worms, which can affect their ability to learn. And recent data on the economic outlook of China’s rural areas suggests that they may be facing increasing economic challenges due to Covid-19.

A farmer carries harvested wheat to the road on June 12, 2010 near Yongji, Shanxi province, China.
Lucas Schifres/Getty Images

Rural Income has Declined Since Covid

Much of China’s workforce comes from the countryside, and many students attend rural schools. Therefore, it is important to track the rural economy to understand China’s broader socio-economic outlook.

In 2020, the Stanford Rural Education Action Program (REAP), directed by Professor Rozelle, conducted four rounds of surveys in seven provinces and 726 villages to assess the situation in rural China. The responses show that the Covid-19 pandemic has had a negative impact on rural wages and income. A majority of respondents, 54 percent, reported that their family’s total annual income had declined on average by 33 percent compared to the previous year (2019). Likewise, almost 40 percent of respondents said their monthly wages fell on average by RMB 716 ($104).

Moreover, survey responses indicated that government initiatives reached very few villagers. For example, 98 percent of rural workers surveyed were not covered by unemployment insurance, and 81 percent of villagers reported no government training programs. In short, the survey indicates that rural workers are struggling and that state support is far from adequate to meet their needs.

A worker leaves a construction site in Beijing on October 28, 2020.
NICOLAS ASFOURI / AFP

Policy Implications

After decades of continuous growth and economic development, China is beginning to face the challenges of other middle-income and some advanced economies. In cities, as employment opportunities in manufacturing and construction decline, more people are entering the labor-intensive service sector, where wage growth is stagnant. Moreover, these workers face an uncertain future because they lack access to high-quality health insurance, pensions, and other support.

But while most economies have experienced a relative decline in manufacturing employment relative to the service sector as they have moved from middle-income to high-income status, China’s workers may find it harder to transition to white-collar jobs because of low education levels. Access to education is increasing in China but lags behind other middle-income countries. Finally, data from villages also show that rural China is still suffering with low employment and wages, a trend exacerbated by the Covid-19 pandemic.

High inequality, especially when it takes the form of unequal access to education and health services, will hamper overall economic growth, but it will also undermine efforts to achieve technological upgrading and raise productivity. Uneven educational levels and inadequate skills could hold back the growth of the most innovative parts of the economy. Advanced tech companies may be constrained to operating near regional innovation hubs rich in talent and be unable to tap into the growing number of underemployed, undereducated workers. Expanding access to high-quality education and strengthening the social safety net for urban and rural residents alike may be the key to whether China can move toward high-income status.

Additionally, persistently high inequality in a period of lower economic growth may have broader implications for social cohesion and political stability. In past decades of high growth, survey research has found that inequality had little bearing on China’s political stability. Although wealth became more concentrated in the hands of few, real wages rose for almost everyone from the 1980s to the 2010s, leaving most better off. Hence, even the relatively poor had a positive outlook thanks to reasonable prospects of upward social mobility. The rising informality of the economy and stagnating wages for unskilled workers may cause large swaths of the population to lose this confidence, introducing new fragility in the social system. Higher rates of crime and other problems, including protests, could follow, sowing the seeds of political instability.

Professor Rozelle’s findings show that China’s broad development targets and aims to become a high-tech power, particularly in advanced manufacturing, may be harder to achieve than many imagine. Similarly, if a large portion of China’s population has stagnant real wages and continues to save for a rainy day, their ability to consume will be limited. This means that rather than a consumption-driven economy, China’s growth will continue to depend on state-driven investment, which will translate into expanding debt—a vicious cycle that will also weigh down growth.

What does this mean for U.S. policymakers? If the economic shocks of the past two years have proven anything, it is that economic and social issues in the world’s most populous country and second-largest economy have a large impact on the United States and the rest of the world. There are at least three key areas of action.

1) Policymakers in the United States should plan for a China that is simultaneously highly competitive in certain areas and weighed down in others by substantial problems, such as low growth, persistent inequality, an aging population, and rising debt. Although these trends are well known, there is still limited planning for the policy implications. For example, the National Intelligence Council’s Global Trends in 2040 identifies the risk posed by high inequality to China’s continued economic growth in the next decade, but it fails to incorporate the likelihood of Beijing struggling with internal domestic issues in its future scenarios.

China is almost certainly going to continue to prove itself a formidable economic competitor for the United States in the coming years, but it will also face significant hurdles to achieve continued economic growth and development. As a consequence, the United States will need to prepare to compete against China at the leading edge of industries as well as deal with a country grappling with internal social challenges. These trends can reinforce China’s statist tendencies, meaning a continued use of industrial policy tools to benefit strategic domestic industries. The United States will need to integrate and align tactics with like-minded economies to simultaneously deal with the consequences of Chinese successes and weaknesses.

Persistent inequality also has potential implications for China’s foreign policy. A China that is less economically dynamic and more exposed to economic volatility could turn inward and be more isolationist. However, China’s leaders could also be more tempted to use an aggressive foreign policy to unite an otherwise fragmenting populace. Such a destabilizing outcome could have disastrous effects for the United States and the rest of the world. Thus, Washington should closely track and measure inequality and internal discontent in China, looking for signs of whether the leadership is drumming up external tensions for domestic political purposes.

2) If Washington wants to compete effectively with China, it needs a strategy to reduce the United States’ own glaring gap in wages between skill-intensive and labor-intensive service jobs, rebuild the economy’s infrastructure, and enhance the competitiveness of U.S. industries and the American workforce. The United States cannot simply hope that China’s economic growth will falter without enhancing its own strength.

A policy aimed at “slowing down” China through tariffs and export restrictions without complementary policies to improve domestic economic competitiveness is unlikely to succeed in the long term. Related legislation currently being considered in Congress, including the United States Innovation and Competition Act of 2021, could be a significant step in this direction, but the executive branch and state and local governments will need to stay committed to these goals over an extended period.

The Biden administration has outlined a “worker-centered trade strategy” that includes seeking better protections for workers in the United States and abroad while defending U.S. economic interests and building more domestic resilience. But the United States’ competitiveness also comes from openness, including the international network of U.S. partners and the country’s attractiveness to international talent. Retaining this advantage means allowing more students, immigrants, and foreign investors to study, live, and work in the United States. And at the same time, it means maintaining access to foreign markets and strengthening U.S. manufacturing that can fuel American exports. Protecting workers and creating more business opportunities should be seen as complementary agendas, not competing ones.

3) While the United States and China are competing, they may also find ways to collectively address some of these common challenges, especially issues posed by automation. Despite the two countries’ differences, they face surprisingly similar kinds of labor and wage challenges. There may be opportunities for educational exchanges and bilateral or multilateral discussions at the academic level or within international organizations, such as the World Trade Organization (WTO) or the International Labour Organization, which has already been working on the issue. One useful area of discourse could be how to best educate and train the workforce for the twenty-first century to mitigate the uneven effects of globalization. If cooperation with China proves too challenging, there may be fruitful opportunities to engage with U.S. partners, particularly those in the Organisation for Economic Cooperation and Development (OECD) or possibly the nascent Indo-Pacific Economic Framework (IPEF).

Finally, the WTO has made trade liberalization its dominant focus, and it has not yet provided satisfactory solutions to the impact on workers and wages of widespread automation, wage gaps, and regional underemployment caused by globalization. To address this gap, the United States should push the WTO to put these issues on the agenda of its upcoming ministerial meeting in June. Overall, the data in this study call for paying closer attention to how factors in the labor market, inequality, education, and rural development play out and interact with each other—at home and abroad.

Box 1 – Methodology: Doing Surveys in China

 

There are inherent shortcomings in using official Chinese data, including data compiled by the National Bureau of Statistics (NBS). Yet, this is one of the best sources of consistent data over time for tracking population, labor force, and education trends in China. As international scholarly exchanges decline and the political environment in China becomes more challenging to navigate, alternative data sources have become increasingly difficult to access.

To address this issue, Professor Scott Rozelle and his collaborators use a variety of methodologies and collaborations to assess different aspects of China’s economy. This feature combined data collected through a variety of formal surveys, and official NBS data to paint a more complete picture of the urban labor market, China’s rural economy, and education attainment. Some of the surveys focus on particular provinces and are not necessarily representative of the whole country, but they help put into context or triangulate national data from NBS.

The data used in the visualizations for this feature are published in the following papers:

Figure 1: Sources: National Bureau of Statistics of China (www.stats.gov.cn); for CFPS Gini Coefficient estimates: Ravi Kanbur, Yue Wang, and Xiaobo Zhang, “The Great Chinese Inequality Turnaround,” Journal of Comparative Economics 49, no. 2 (June 2021): 467–82; for all other countries estimates: UNU-WIDER, World Income Inequality Database (WIID). Version 31 May 2021.

Figure 2: National Bureau of Statistics of China (www.stats.gov.cn).

Figures 3-7: National Bureau of Statistics of China (www.stats.gov.cn). Adapted from: Scott Rozelle et al., “Moving Beyond Lewis: Employment and Wage Trends in China’s High- and Low-Skilled Industries and the Emergence of an Era of Polarization: Presidential Address for the 2020 Association for Comparative Economic Studies Meetings,” Comparative Economic Studies 62, no. 4 (December 2020): 555–89.

Figures 8: GDP per capita data: World Bank, IMF. Educational attainment data for 2015: Yu Bai et al., “Past Successes and Future Challenges in Rural China’s Human Capital,” Journal of Contemporary China 28, no. 120 (November 2, 2019): 883–98. Educational attainment data for 2020: data for all countries except China is from OECD (2021), Education at a Glance 2021: OECD Indicators, OECD Publishing, Paris. For China: Institute of Social Science Survey, Peking University, 2015, “China Family Panel Studies (CFPS)”, https://doi.org/10.18170/DVN/45LCSO, Peking University Open Research Data Platform, V42.

Qiufeng Gao et al., “Reading Achievement in China’s Rural Primary Schools: A Study of Three Provinces,” Educational Studies 47, no. 3 (May 4, 2021): 344–68, doi:10.1080/03055698.2019.1701994.


In addition to the papers listed above, the feature also draws on the following research:

Yu Bai et al., “Past Successes and Future Challenges in Rural China’s Human Capital,” Journal of Contemporary China 28, no. 120 (November 2, 2019): 883–98, doi:10.1080/10670564.2019.1594102.

Hong Cheng et al., “The Rise of Robots in China,” Journal of Economic Perspectives 33, no. 2 (June 1, 2019): 71–88, doi:10.1257/jep.33.2.71.

Niny Khor et al., “China’s Looming Human Capital Crisis: Upper Secondary Educational Attainment Rates and the Middle-Income Trap,” China Quarterly 228 (December 2016): 905–26, doi:10.1017/S0305741016001119.

Hongbin Li et al., “Human Capital and China’s Future Growth,” Journal of Economic Perspectives 31, no. 1 (February 2017): 25–48, doi:10.1257/jep.31.1.25.

Scott Rozelle and Natalie Hell, Invisible China: How the Urban-Rural Divide Threatens China’s Rise (Chicago: University of Chicago Press, 2020).

Box 2 – Additional Resources

 

On Inequality and Political Stability in China

Martin King Whyte, “China’s Dormant and Active Social Volcanoes,” China Journal 75 (January 2016): 9–37, doi:10.1086/683124.

Martin King Whyte, Myth of the Social Volcano: Perceptions of Inequality and Distributive Injustice in Contemporary China (Stanford: Stanford University Press, 2010).

Susan Shirk, China: Fragile Superpower (New York: Oxford University Press, 2008).

Scott Rozelle and Matthew Boswell, “Complicating China’s Rise: Rural Underemployment,” Washington Quarterly 44, no. 2 (April 3, 2021): 61–74, doi:10.1080/0163660X.2021.1932097.

Yingnan Joseph Zhou and Shuai Jin, “Inequality and Political Trust in China: The Social Volcano Thesis Re-Examined,” China Quarterly 236 (December 2018): 1033–62, doi:10.1017/S0305741018001297.

On Measuring Inequality

Ravi Kanbur, Yue Wang, and Xiaobo Zhang, “The Great Chinese Inequality Turnaround,” Journal of Comparative Economics 49, no. 2 (June 2021): 467–82, doi:10.1016/j.jce.2020.10.001.

“World Income Inequality Database (WIID) Companion Dataset (Wiidcountry),” UNU-WIDER, https://www.wider.unu.edu/node/236613

On China’s Urbanization and Employment

Mary E. Gallagher, “Can China Achieve Inclusive Urbanization?,” in Fateful Decisions: Choices That Will Shape China’s Future, ed. Thomas Fingar and Jean C. Oi (Redwood City, CA: Stanford University Press, 2020).

Hong Cheng et al., “The Rise of Robots in China,” Journal of Economic Perspectives 33, no. 2 (June 1, 2019): 71–88, doi:10.1257/jep.33.2.71.

Mary E. Lovely, “China is deindustrializing but has a way to go to match other upper-middle-income economies,” Peterson Institute for International Economics, February 26, 2021, https://www.piie.com/research/piie-charts/china-deindustrializing-has-way-go-match-other-upper-middle-income-economies.

On China’s Human Capital and Education

Yu Bai et al., “Past Successes and Future Challenges in Rural China’s Human Capital,” Journal of Contemporary China 28, no. 120 (November 2, 2019): 883–98, doi:10.1080/10670564.2019.1594102.

Qiufeng Gao et al., “Reading Achievement in China’s Rural Primary Schools: A Study of Three Provinces,” Educational Studies 47, no. 3 (May 4, 2021): 344–68, doi:10.1080/03055698.2019.1701994.

Niny Khor et al., “China’s Looming Human Capital Crisis: Upper Secondary Educational Attainment Rates and the Middle-Income Trap,” China Quarterly 228 (December 2016): 905–26, doi:doi:10.1017/S0305741016001119.

Hongbin Li et al., “Human Capital and China’s Future Growth,” Journal of Economic Perspectives 31, no. 1 (February 2017): 25–48, doi:10.1257/jep.31.1.25.

Prashant Loyalka et al., “The Impact of Vocational Schooling on Human Capital Development in Developing Countries: Evidence from China,” World Bank, August 27, 2015, https://openknowledge.worldbank.org/handle/10986/22651.

Scott Rozelle and Natalie Hell, Invisible China: How the Urban-Rural Divide Threatens China’s Rise (Chicago: University of Chicago Press, 2020).

Scott Rozelle et al., “Moving Beyond Lewis: Employment and Wage Trends in China’s High- and Low-Skilled Industries and the Emergence of an Era of Polarization: Presidential Address for the 2020 Association for Comparative Economic Studies Meetings,” Comparative Economic Studies 62, no. 4 (December 2020): 555–89, doi:10.1057/s41294-020-00137-w.

This picture taken on March 22, 2019 shows a skyline of Chongqing from the top of Raffles City Chongqing under construction in southwest China's Chongqing Municipality.
WANG ZHAO/AFP via Getty Images

About the Author

  • Ilaria Mazzocco
    Ilaria Mazzocco is a fellow with the Trustee Chair in Chinese Business and Economics at the Center for Strategic and International Studies (CSIS). Prior to joining CSIS, she was a senior research associate at the Paulson Institute, where she led research on Chinese climate and energy policy for Macropolo, the institute’s think tank. She holds a PhD from the Johns Hopkins School of Advanced International Studies (SAIS), where her dissertation investigated Chinese industrial policy by focusing on electric vehicle promotion efforts and the role of local governments. She also holds master’s degrees from Johns Hopkins SAIS and Central European University, as well as a bachelor’s degree from Bard College.

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This feature was made possible through the generous support of the Stanford Center on China’s Economy and Institutions (SCCEI). Special thanks goes to Professor Scott Rozelle and his colleagues for sharing their work and time with us, and to the SCCEI team of Scott Rozelle, Matthew Boswell, and Jennifer Choo for the dedication to this collaboration. I am also grateful for Scott Kennedy’s guidance and edits, as well as the hard work and professionalism of my CSIS colleagues, including the Trustee Chair’s Alyssa Perez, Qin (Maya) Mei, and Shayla Gibson and the iDeas Lab’s Laurel Weibezahn and Tucker Harris. All opinions and errors are the solely the author's.

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Ilaria Mazzocco, "How Inequality is Undermining China’s Prosperity," Big Data China, Center for Strategic and International Studies, May 26, 2022, last modified July 26, 2022, https://bigdatachina.csis.org/how-inequality-is-undermining-chinas-prosperity/.