From Pyramids to Olives

Abstract

Since embarking on a path of economic reforms in the late 1970s, China has achieved two milestones in improving people’s livelihoods. First, China’s per capita income has risen rapidly, from US$156 to US$12,556 between 1978 and 2021, making it one of the fastest growing economies in the world. Second, China’s poverty rate has declined dramatically. In the past 40 years, China has lifted 770mn rural people out of poverty, accounting for more than 70% of global poverty reduction in the same period. Despite China’s socio-economic achievements in development, we believe a sustained effort is still required to raise income levels and address economic inequality, in order to achieve inclusive growth. Currently, China still has a large low-income population, and the income distribution pattern represents a pyramid rather than an olive shape. China’s Gini coefficients in income, consumption, and wealth distribution are at a high level, and inequality is a prominent issue. China’s economy is still subject to urban–rural disparities; in fact, we can attribute nearly half of the income gap attributed to the urban–rural gap. In addition, wealth in China has continued to concentrate over the past 30 years. With housing assets becoming the main component of household wealth, rising urban housing prices are a major driver of wealth concentration in China. Based on the World Income Inequality Database (WIID), we find that based on certain income classification criteria, the shape of China’s income distribution represents a pyramid shape. This contrasts with that of Nordic countries, Japan, and the US, which are closer to an olive shape. The main reason for this difference is that China still has a large number of low-income people, and its middle-income population is not large enough to support the “waist” of the olive shape. In addition, the income level of China’s middle-income population is relatively low, and their weak risk resilience makes this income group vulnerable to a return to poverty. The focus of improving income distribution is not to create an olive-shaped pattern, but to raise the per capita income level and expand the population size of the middle-income group. We believe that China should continue to raise per capita income and deepen reforms and “opening up” policies, while at the same time implementing redistribution policies to reduce inequality.

Authors: Yang Zhao, Chao Xie, Haiyan Guo, Yating Li, Lei Xu, Naixi Wang, Yiran Liu, Xiaohui Wu, Wei He, Zeyu Yao, Sijie Lin, Yada Li, Linggang Jiang, Lu Lu, Jin Li, Gen Li, Wei Nie, Dong Wei, Yunjie Wu, Hongbo Deng, Hanfeng Wang.

1.1 Measuring Inequality with Income, Consumption, and Wealth Gini Coefficient

This section describes economic inequality in China using four data categories. Individual income is defined by per capita household income and includes household members within the household who do not have income. For example, children with no income are not classified in the zero-income group, but in the income group corresponding to the per capita income of their household. Thus, when measuring the size of the income group in a given income range, we are actually measuring all people whose household per capita income falls in that range.

• 1. Data published by the National Bureau of Statistics (NBS) and other official agencies in China: The NBS publishes relatively limited data on income distribution, mainly the Gini coefficient and the mean, median, and quantile of per capita disposable income. Among the various data on income disparity, we believe data from the NBS is the most trustworthy.

• 2. Databases published by international organizations: These include the World Income Inequality Database (WIID), PovcalNet, and the World Inequality Database (WID). The raw data of these databases are official data obtained from countries and survey data from research institutions, some of which are adjusted for international comparison. The advantage of these databases is their high degree of international comparability.

• 3. Household survey data released by academic institutions: Some academic institutions conduct sample surveys on the economic situation of Chinese households over a long period. These surveys in China include CHIP, CFPS, CGSS, CHNS, and CHFS,¹ which describe household economic situations in detail. The drawbacks of survey data are small sample size, statistical biases, and insufficient coverage of the very-high-income group.

• 4. Income and property data on high-net-worth individuals (HNWIs) published by commercial institutions: For example, we refer to wealth management data provided by private banks. This type of data helps depict the HNWI population, but may be limited by its own sampling as well as modelling.

1.1.1 The Income Gini Coefficient Has Steadily Decreased Over the Past Decade, but Remains at a High Level

Despite various limitations, the Gini coefficient is still an important indicator for measuring inequality. Data from the NBS indicates that China’s income Gini coefficient is at a relatively high level. The NBS, National Development and Reform Commission (NDRC), and international organizations have estimated China’s income Gini coefficient (Fig. 1.1). The highest value was provided by NBS at 0.47 in 2020. The Gini estimate published by the NBS should be the most accurate, because the NBS calculates Gini coefficient directly based on micro-level survey data, and the “missing rich” problem is addressed using tax data.² Gini estimates by other agencies are based on quantile data provided by the NBS and are more likely to underestimate the Gini coefficient.³ In terms of comparison across countries, the latest data from the WIID database shows that China’s income Gini coefficient was 0.43 in 2019, higher than that of the US (0.42) and most European countries (e.g. Germany 0.32).

Fig. 1.1

Source China Statistical Yearbook, World Bank, PovcalNet, World Income Inequality Database (Version 31 May 2021), National Development and Reform Commission,Footnote

National Development and Reform Commission, Institute of Social Development Research Group [23].

CICC Global Institute

Gini coefficients in China from different sources (1978–2020). Note The World Bank’s Gini coefficient was not continuous until 2010.

China’s income Gini coefficient has been rising since 1978, and has now fallen from its peak. China’s income Gini coefficient rose gradually from 1984 to 2000, reached its highest level around 2009, and then declined. It is still above 0.4 based on various sources. However, the rise in the Gini coefficient cannot be attributed to economic reforms and opening up. Ravallion and Chen [27] shows that there is no significant evidence that economic growth policies or urbanization per se caused income divergence after 1980.⁵ We believe the urban–rural gap is the most important factor accounting for the widening income gap in China. The urban–rural dual system established in the planned economy has not been entirely reformed, which has largely prevented rural residents from seeing the same level of income growth as urban residents. Therefore, China’s rising Gini coefficient implies that some people, especially rural residents, have not been able to fully reap the reform dividends of marketization and urbanization, and that China’s market-oriented reforms are still ongoing.

China’s income Gini coefficient experienced a downward trend over the past decade. The income Gini coefficients estimated by various institutions have reversed their previous upward trend and have fallen to some extent over the past decade, indicating a reduction in income inequality. The ongoing urbanization process has reduced the income inequality caused by the urban–rural gap. In addition, the government has vigorously promoted poverty alleviation policies to raise the income level of rural residents, which helped to narrow not only the urban–rural gap, but also the income gap within the rural areas.

1.1.2 Consumption Accounts for a Relatively Small Share of China’s Economy, and There Is Considerable Inequality Within the Country

Consumption is a direct indicator of national welfare. After the global financial crisis in 2008, consumption became an important engine of China’s economic growth, but consumption growth still lags other countries and it remains uneven. China’s consumption-to-GDP ratio is lower than that of developed countries and other emerging market economies. According to Wind data and our estimates, the household consumption-to-GDP ratio in China was 38% in 2020 (Fig. 1.2), significantly lower than that in the US (67%), Japan (54%), and India (63%). Although in aggregate-level terms, China’s consumption has grown rapidly over the past 15 years, with total consumption in China in 2020 being five times higher than in 2005, there is still much room for increasing household consumption in terms of GDP share.

Fig. 1.2

Source Wind, CICC Global Institute

Household consumption as a share of GDP.

Income inequality inevitably triggers consumption inequality. According to the World Bank, the Gini coefficient of consumption in China was 0.38 in 2016, which is relatively high among developing countries. Consumption of basic goods and services such as food, housing, and health care account for a higher share of expenditure in low-income households, while consumption in high-income households is more skewed toward upgrading consumption categories such as culture, education, entertainment, and household appliances.⁶ Compared to the US, the correlation between income and consumption inequality is stronger in China, which can be explained by two phenomena. First, low-income households in China have insufficient access to social transfers or financial instruments to smooth their consumption when experiencing income shocks. Even if the income shock is temporary, poorer households have fewer assets at their disposal and the imperfect financial system provide them with insufficient consumer credit, leading to a stronger correlation between income and consumption in the same period. Second, in the economic restructuring related to digitization and automation, the income declines faced by low-skill workers are likely to be long-term rather than temporary.

Consumption inequality in China is slightly less severe than income inequality. First, relative to the income Gini coefficient, China’s consumption Gini coefficient experienced a faster decline over the last decade (Fig. 1.1). Since the marginal propensity to consume is higher for low-income groups, the decline in consumption Gini coefficient reflects the increased consumption and improved welfare of low-income groups in China, which is closely related to China’s ongoing urbanization reforms and poverty alleviation policies. Second, China ranks better in consumption Gini coefficient than in income Gini coefficient. The WIID and PovcalNet databases provide comparable Gini coefficient estimates across countries.⁷ The income Gini coefficient provided by the WIID database shows that China’s income Gini coefficient is 0.43, higher than two-thirds of countries available in the database. The PovcalNet database has measured the consumption Gini coefficient of more than 50 countries since 2015. China’s consumption Gini coefficient is higher than 60% of countries in the database, ranking slightly better than its income Gini coefficient.

1.1.3 Wealth Is Concentrated with Economic Development

China’s Gini coefficient of wealth has increased significantly along with economic development. Since the reform and opening up in 1978, especially after the accession to the WTO in 2001, personal wealth in China has increased significantly. However, in this process, there was also a trend of wealth concentration. According to the Asian Development Bank, the Gini coefficient of wealth in China rose from 0.34 to 0.73 between 1998 and 2012,⁸ far exceeding the rise in the income Gini coefficient over the same period. The NBS does not publish the Gini coefficient of wealth, but scholars have estimated the wealth Gini, showing that from the 1990s to the 2010s, the Gini coefficient of wealth rose significantly in China.⁹

Rising housing prices have been an important driver of wealth concentration in China. For most Chinese urban households, housing is their most important asset. Based on the Urban Household Assets and Liabilities Survey conducted by the People’s Bank of China in 2019, the average total assets of urban households are about Rmb3.18 mn, of which housing assets amount to Rmb1.88 mn, accounting for 60% of total household assets.¹⁰ As the home ownership rate in China is high, the concentration of wealth in urban households is more a reflection of the value of their assets as opposed to whether or not they own a home. The poorest quintile of Chinese households has a homeownership rate of 89%, compared to 33% in the US.¹¹ The disparity in housing prices has widened across regions in China over the past few decades, leading to a significant divergence in wealth among households. In particular, rural housing prices have remained largely unchanged. This has resulted in a concentration of wealth in favor of urban households, exacerbating the urban–rural gap in terms of household wealth. Based on a study released by Southwest University of Finance and Economics in cooperation with Ant Group, from 2020 to 2021, appreciation in the property value explained about 60–77% of the increase in Chinese household assets, while returns from financial investments contributed to another 15–30% of the increase in household assets.¹²

Concentration of financial assets is another contributor to the rising wealth inequality in China. According to estimates from McKinsey, less than 1% of Chinese households have personal financial assets of US$1 mn or more.¹³ Only a small proportion of households benefit from high-return financial investment opportunities.

1.2 Income Distribution in China

1.2.1 Income Structure: Pyramid Versus Olive

We believe the ideal income distribution pattern for a society is olive-shaped. What is the current shape of income distribution in China? The NBS only publishes quantile data of household income, making it difficult to measure China’s income structure in more detail. The WIID database provides percentile data on personal income in China in 2019, which is often used by academics. Using the WIID data originally compiled by the NBS, we classify China’s population into 11 income groups based on disposable income per capita, and calculate the population share in each group. It is important to note that income here refers to per capita household income, not individual income. For example, in a family of four in which the father and mother each earn Rmb10,000 per year and there are two children, the four members of the household are assigned into the income group of Rmb5,000 per capita. According to the above classification criteria, one-third of the population in China is in the income group with less than 0.5 times per capita disposable income, while those in the range of 1.0–1.5 and 1.5–2.0 times per capita disposable income account for 17 and 9% of the population. As shown in Fig. 1.3, the income structure is shaped like a pyramid in China.

Fig. 1.3

Source Calculated from WIID percentile data provided by UNU-WIDER (Version 31 May 2021), CICC Global Institute

Population share by income groups across countries. Note We use the latest available data for each country in the WIID database. Considering that the income structure is stable over a 10-year period, the difference in source years of data is unlikely to bias our analysis.

Applying the same approach to other countries’ income data, we find that the income distribution in the Nordic countries is closer to an olive shape. For example, the middle-income group (0.5–1.0 times per capita disposable income range) accounts for half of the population in Denmark, and the lowest income group (less than 0.5 times per capita disposable income) accounts for only 10% of the population in Denmark. Considering that the Nordic countries are mostly small economies and may not represent the income structure of large economies, we conduct estimates for the US, Japan, and India. The share of population in the 0.5–1.0 times per capita disposable income range in the US is 36%, slightly higher than in China. In Japan, this share reaches 50%, being closest to the ideal olive shape among large economies. India also has a pyramid shaped income structure, with a population share of 41% in the lowest-income group.

Improving income distribution does not only mean the expansion of the middle-income group, but also implies a need to raise income levels such as the median income. In fact, as one classifies the population into narrower income groups, income distribution always shows an olive-shaped structure with a gradually smaller bottom. The real question is: At what level is the income of the majority of the population? Given the olive analogy, we have to ask at what height is the waist of the olive? According to the NBS, China’s GDP per capita in 2021 is around Rmb80,000, and the disposable income per capita is Rmb35,128, but the median disposable income per capita is only Rmb29,975, equivalent to a monthly disposable income of less than Rmb2500. In fact, in the two decades prior to the reform and opening up in 1978, China’s income distribution pattern was close to olive-shaped. However, at that time, the World Bank estimated that more than 45% of the world’s people living in poverty were in China.¹⁴ This implies a society featuring widespread poverty during that time, not prosperity. The olive-shaped income distribution of Nordic countries is considered affluent, primarily due to their high level of per capita income. It is the high per capita income level and the large number of middle-income people that are important, rather than the olive-shaped income structure itself. Therefore, to achieve an olive-shaped society in accordance with the meaning of “prosperity,” we think China needs to continue to develop its economy, deepen reforms and opening up policies, and raise per capita disposable income. At the same time, redistribution policies need to promote equality.

Though the income structure in some high-income countries is closer to an olive shape, increasing per capita income does not automatically promote economic equality. By analyzing the correlation between the share of population earning 0.5–1.0 times per capita disposable income and GDP per capita across countries over time, we have two findings. First, when GDP per capita is below US$10,000 (2017 PPP), the share of people with 0.5–1.0 times disposable income per capita was mostly in the range of 20–50%. Second, when GDP per capita is above US$30,000, the share of people with 0.5–1.0 times disposable income per capita is mostly in the range of 35–55%. This seems to imply a positive correlation between the income level and the share of middle-income population, but this shift does not happen automatically with economic growth. For example, despite continuous income growth between 1947 and 2018 in the US, income inequality was initially reduced and then increased. Also of note is that when the US, UK, and Japan were at the level of GDP per capita comparable to China’s current level, these countries had a higher share of the population with 0.5–1.0 times per capita disposable income. Thus, China still has room to improve its income distribution at the current income levels.¹⁵

1.2.2 Raising the Middle-Income Level and Expanding the Middle-Income Group

According to our analysis of income distribution in China, Chinese households can be roughly divided into four income groups: A very-high-income group, a high-income group, a middle-income group, and a low-income group. Among them, there are significant differences between the very-high-income group and the high-income group. The former group is small and they obtain their wealth mainly by running businesses or through investments. People in the latter group mainly earn salaries, and their wealth levels are far below the very-high-income group. We think the absolute income level of the middle-income group still needs to increase, and the population share of middle-income group in China is considerably lower than that of developed countries. To achieve the goal of common prosperity, it is important to build a stronger middle-income group by increasing the middle-income level and expanding the size of this group.

Market survey data from financial institution paints a picture of the very-high-income group, which in China mainly consists of entrepreneurs and investors. They are also generally referred to as high-net-worth individuals (HNWIs), with the criteria of having more than Rmb10 mn of investable assets.¹⁶ According to 2021 China Private Wealth Report—China’s Private Banking Industry: Embracing rivers to form the sea, a report published by China Merchants Bank (CMB), China’s HNWI population reached 2.62 mn in 2020.¹⁷ According to the 2020 Fanta—Hurun Wealth Report, the number of high-net-worth households in 2019 was about 1.08 mn, corresponding to about 2.82 mn people,¹⁸ roughly consistent with the CMB report. In 2017, CITIC Bank and Hurun Report jointly released Wealth Management: Trends of the Chinese HNWI, mentioning that business owners accounted for 55% of the HNW population, while the rest were mainly company executives, property speculators, and full-time stock market investors. According to China Private Banking Report 2017 jointly published by Industrial Bank and Boston Consulting Group (BCG), nearly half of the respondents reported that they accumulated their wealth by founding companies, followed by respondents who gained profits from investments, including real estate investment.

High-income groups can be defined as people whose incomes are in the top ranking of society, but there is a gap between this group and the very-high-income group (i.e., high-net-worth individuals). After we deduct the high-net-worth population share (0.2%) from the top 10% of income earners, we are left with the high-income population. According to China Statistical Yearbook 2021, the per capita disposable income of the top quintile of urban households in China in 2020 is about Rmb96,000. As the NBS urban household survey has difficulty covering the high-net-worth population, we believe Rmb96,000 should be close to the average annual income of China’s high-income population. There are income variations within the high-income group. Based on the China Household Financial Survey (CHFS), among the top 1% sampled respondents with highest income, 94% are employees, and their average annual income is about Rmb340,000, roughly equivalent to per capita income in the US.¹⁹

The size of middle-income group varies depending on definition criteria.²⁰ Criteria for defining the middle-income group can include income, wealth, occupation, and social class, but income is used as the most fundamental indicator. The middle-income group can be defined based on absolute income levels or relative income range. In the first case, the middle-income group covers all individuals whose income is in a fixed range. For example, the NBS in China defines a household with annual income of Rmb100,000–500,000 as a middle-income household in 2018, and the middle-income population in China under this criterion is about 400 mn, accounting for 28% of the total population.²¹ The relative standard of middle income generally constructs an income range based on a benchmark such as the national median income. Thurow [31] defines the middle-income group as those within 75–125% of the median income,²² and a large number of studies have continued to use this standard.²³ The absolute standard of middle income needs to be adjusted over time as living standards improve. To avoid this adjustment, most researchers in practice prefer to use the relative standard of middle income.

According to the definition of middle income (75–125% of median) proposed by Thurow [31], the median disposable income in China published by the NBS is Rmb27,540 in 2020, implying that the middle-income range in China is Rmb20,655–34,425. Based on the WIID database and population statistics published by NBS, the estimated population share of the middle-income group in China was 22% in 2020,²⁴ slightly lower than the proportion of middle-income population measured by NBS according to absolute criteria (28%). Other Chinese researchers have estimated the population share of middle-income group in China based on different definition criteria and data sources, and the results are mostly in the range of 20–40%.²⁵

It should be emphasized that the middle-income group is not necessarily the same as the middle class. The middle class is a relatively stable, affluent, and secure group that emerges along with long-term economic growth. It corresponds to a certain income, occupation, education, consumption patterns, as well as social status.²⁶ Given this concept, the middle class is not equivalent to the middle-income group in China, but is closer to the high-income group in the top 10% income quantile. The middle-income group in China has average annual income of less than Rmb30,000 and faces considerable vulnerability. Financial risks relating to mortgages, medical expenditures, and unemployment may prevent these middle-income individuals from improving their finances, and they may even fall into the low-income group. Based on the CFPS 2010–2016 longitudinal surveys, Liu et al. (2021) show that households entering middle-income group face a period of rising vulnerability, and only 74% of these households are able to maintain middle income for more than five years.²⁷ Therefore, we think helping middle-income households survive the period of vulnerability is important in policymaking aimed at building a strong middle-income group.

Among China’s middle-income populations, rural–urban migrant workers are noteworthy. According to the 2020 Migrant Workers Monitoring Survey Report published by the NBS, the average monthly income of China’s 290 mn rural–urban migrant workers in 2020 was Rmb4072.²⁸ This number is higher than the per capita income of the top 20% of rural high-income households and comparable to urban middle-income households, both by absolute and relative standards. Thus, many migrant workers are included in middle-income populations. However, families of these rural migrant workers are covered by weaker social protection, such as lower levels of pension and healthcare reimbursement, and migrants are more likely to participate in informal employment, leading to economic instability. The economic instability of migrant workers is an example of a vulnerability of the middle-income group in China. In addition, rural workers are still subject to the urban–rural dual structure system, which is based on the household registration system and implies differentiated social benefits between rural and urban residents. To make middle-income group stronger, we think policies should help migrant workers settle in cities and make access to social benefits more equal for rural and urban residents.

1.2.3 The Low-Income Group Mainly Lives in Rural Areas

Though absolute poverty, defined as people living below the national poverty line, has been eliminated, China still has a considerably large population with low incomes. According to the NBS, the per capita disposable income of the bottom 20% of urban households was Rmb1300 per month in 2020, while the bottom 20% of rural households was only Rmb400 per month. According to Shen and Li (2020), using 40% of the national median income as the relative poverty line, the relative poverty population in 2020 is about 200 mn, with more than 80% in rural areas.²⁹ The per capita monthly income of rural residents is less than Rmb2000 in every province in the Chinese mainland except Jiangsu, Zhejiang, Beijing, Shanghai, and Tianjin³⁰; it is less than Rmb1000 in Guizhou and Gansu. Thus, most low-income people in China are living in rural areas, especially in western regions.

What kind of people are more likely to fall into the low-income group? Survey data show that people who are older, less educated, and in poor health are more likely to fall into poverty (Figure 1.4). Notably, the incidence of poverty for the poor-health group was 1.5% in 2019, three times as high as for those considered to be in good health. In other words, illness and healthcare expenses may severely deteriorate household finances for families who have only recently been lifted out of poverty.

Fig. 1.4

Source Office of Household Survey of the NBS,Footnote

Office of Household Survey, National Bureau of Statistics [24].

CICC Global Institute

Poverty rate by age, education, and health status in rural China (2019).

The difference in income is not directly equivalent to the difference in quality of life as price levels and lifestyles vary greatly across regions. For example, the per capita disposable income was Rmb75,000 in Beijing in 2020, more than seven times that of farmers in Gansu. But considering the difference in prices, the gap in quality of life between the two areas may not be as large as the income gap. Nevertheless, we should not underestimate the importance of income in modern life. Money is the basis for economic choices. Although low incomes can allow farmers to meet their basic consumption needs under rural economic conditions, farmers’ economic choices are still greatly limited by their low incomes. A low income also limits the ability to save and protect against risk. In western rural China, although a monthly expenditure of Rmb800 can cover a farmer’s basic needs, the farmer may face financial hardship if emergencies such as serious illness or natural disaster occur, while households with higher incomes can cope more ably. In addition, low-income families cannot afford to invest in financial markets and human capital, making it more difficult for them to improve their economic situation.

The consumption gap between urban and rural areas also reflects the development gap. First, in terms of durable goods, although the penetration rate of refrigerators and TVs in rural areas is close to that of urban levels, the average household ownership of cars and air conditioners in rural areas in 2020 was only 59% and 49% of that in cities, respectively. Second, service consumption is lower in rural areas. In 2019, 39.7% of households’ total consumption in rural areas was spent on services, about 8.5 ppt lower than in urban areas, and this gap is widening over time.

1.3 Urban–Rural, Regional, and Intergenerational Disparities in China

1.3.1 Urban–Rural Disparity: Institutional Cost of Rural–Urban Mobility Should Be Reduced

The urban–rural disparity is one important component of income inequality in China. Since economic reforms and opening-up policies were launched in the late 1970s, China has transformed from a country that is heavily reliant on agriculture into an industrial economy. As part of this process, a large number of people working in agriculture moved into non-agricultural jobs. As spatial concentration of manufacturing and service sectors leads to positive spillover, urban areas are formed by the agglomeration of economic activities. Therefore, the transformation of agricultural workers into non-agricultural workers is usually accompanied by rural–urban migration, meaning that industrialization, urbanization, and economic growth coincide.³²

Free-flowing rural–urban migration is a key factor in bridging the urban–rural income gap. Theoretically, in the early stage of industrialization and urbanization, a certain degree of urban–rural income disparity may be difficult to avoid. However, higher urban wages should eventually attract more rural migrants to cities, reducing the urban–rural income gap. Also, mechanization of agriculture would mean fewer workers were needed in the sector, and more rural residents who previously worked in agriculture would seek jobs in cities. Meanwhile, those staying in rural areas can achieve larger-scale agricultural production and income growth as the rural population declines. Thus, in the later stage of industrialization, the urban–rural income gap is expected to narrow.³³ When the vast majority of rural residents move to cities, the agricultural population decreases significantly and urbanization is basically completed, and the labor productivity between urban and rural areas will equalize, reaching the so-called Lewis Turning Point.³⁴

Changes in the urban–rural income ratio have undergone three stages in China (Fig. 1.5). First, from 1978 to 1984, the de-collectivization reform (i.e., Household Contract Responsibility System) helped to raise farmers’ income and narrowed the urban–rural gap. Second, from 1985 to 2008, the urban–rural income gap in China continued to widen, reflecting the fact that a certain degree of increase in urban–rural income inequality was unavoidable in the early stage of industrialization and urbanization. Third, after 2008, the urban–rural income gap narrowed again. We see policies promoting urban–rural integration and increases in transfer payments to rural areas as important ways to narrow the urban–rural income gap.

Fig. 1.5

Source National Statistical Yearbook, CICC Global Institute

Urban–rural income gap in China has narrowed in the last decade.

In the future, reforms involving urban–rural integration will remain important in narrowing the urban–rural gap. After the founding of the People’s Republic of China in 1949, China concentrated national resources to promote industrialization under the planned economy system given capital scarcity.³⁵ In the late 1950s, China gradually established the urban–rural dual economic system in which mobility between these two sectors was restricted.³⁶ This dual economic system facilitated industrialization in that specific period. However, in recent decades, we think this dual economic structure has been detrimental to promoting urbanization, implying a need for further reform.

Before proceeding further, we shall explain the concept of hukou first. Hukou is the household registration system originally introduced in the 1950s in the Chinese mainland, under which the majority of people in China are classified into either agricultural households or non-agricultural ones (i.e., urban households). In most cases, the hukou status of a child is determined by his or her parents’ hukou rather than the birthplace. For workers originally from rural areas, working in cities does not necessarily mean switching from agricultural hukou to non-agricultural hukou. Access to social benefits is associated with one’s hukou status. For example, public pension and social health insurance for rural residents were introduced much later than those for urban residents.

Currently, the urbanization rate calculated according to hukou status is lower than that regardless of hukou status by nearly 20 ppt,³⁷ meaning that nearly one-fifth of China’s people still live and work in cities, but do not fully benefit from the urban social protections linked to urban household registration (hukou). For example, some migrant works have insufficient access to public services such as public education of their children in cities where they work as these services are usually tied to household registration status. These institutional barriers under the dual system have prevented some farmers from moving to cities and raising their household incomes, which may result in China reaching the Lewis Turning Point earlier than expected.³⁸

More importantly, it is difficult for migrant workers to settle in cities. Many middle-aged migrant workers often choose to return to rural areas. This career path and its expected returns do not tend to incentivize younger migrant workers to increase their human capital (i.e., pursue additional education), savings levels, or consumption.³⁹ In addition, some children of migrant workers cannot receive high-quality compulsory education in urban areas, causing an urban–rural educational gap by leaving some children behind. This forms inequality of opportunity and harms social mobility. Also, the large difference between urban and rural pension levels may widen the urban–rural income gap (Fig. 1.6). In short, the urban–rural dual system not only depresses the long-term potential growth rate of China’s economy, but also runs the risk of promoting class stratification. We think reform of the urban–rural dual system and reducing the costs of rural–urban labor mobility are important steps to improving market efficiency and raising the income of rural residents.

Fig. 1.6

Source Ministry of Human Resources and Social Security, CICC Research

Difference in annual pension between urban and rural pension schemes. Note Urban workers’ pensions and rural residents’ pensions are defined as the quotient of the total expenditure of the pension scheme divided by the number of retirees covered.

1.3.2 Regional Disparity: Effective Policy Interventions Help Improve Both Efficiency and Equality

Policy interventions in recent decades have significantly reduced the costs of factor mobility across regions and thus narrowed regional disparities. With large differences in landscape and culture, China has a significant cost of factor mobility across regions, generated by either natural conditions or regional governance. After the reform and opening up in 1978, and especially since 2000, construction of large-scale infrastructure has greatly removed the impediments to cross-regional factor mobility caused by natural conditions, improving resource allocation efficiency and reducing regional disparities.

Based on per capita GDP at the provincial level, we find that overall regional disparity has been decreasing with fluctuations since 1978. We summarize the changes in regional disparity in three stages. First, from 1978 to the early 1990s, the opening up policy led to rapid growth in Guangdong, Fujian, and other coastal provinces where the initial income levels were low; thus, the regional disparity narrowed. Second, from the early 1990s to 1999, coastal provinces that established export-oriented industrial systems achieved catch-up development and widened the development gap relative to inland provinces. Third, since 1999, China has implemented various projects to narrow the regional development gap, such as the Great Western Development Strategy and the Rise of Central China Plan (Fig. 1.7).

Fig. 1.7

Source NBS, CICC Global Institute

Regional income disparity in China has been decreasing in recent years. Note The measure of regional disparity is based on the measure of income disparity across individuals. The 31 provincial-level administrative units (including municipalities and autonomous regions) of the Chinese mainland are treated as independent individuals within the economy, and the Gini coefficient, Theil index, coefficient of variation (standard deviation/mean), and the ratio of the per capita GDP of China’s most-developed province to the per capita GDP of China’s least-developed province are used to portray the degree of inequality between regions.

In comparison to other countries, we see a lot of room for reduction in China’s regional disparities. In economies with established market mechanisms, the transaction costs of factor mobility across regions are lower, and both capital and labor tend to flow into regions with higher returns, achieving matching efficiency of factor market and economies of agglomeration. In areas with high industrial concentration, the population is also larger, which helps reduce the regional gap in terms of per capita income. The cross-regional Gini coefficient of aggregate GDP and resident population in China is lower than that in Europe, the US, and Japan. However, the Gini coefficient of per capita GDP in China is higher than in those countries, indicating that China’s population and industry may not be adequately clustered. This may have contributed to large per capita income gaps between regions.

Reducing regional disparities requires reduction in transaction costs caused by natural conditions, social governance, and other factors. By reducing such costs, free mobility of production factors should narrow the per capita GDP gap between regions through optimal allocation of resources. Although the cost of cross-regional factor mobility caused by natural conditions has decreased significantly in China, the transaction costs associated with regional governance are still large. For example, local governments can influence the allocation of financial resources, land supply, taxation, and licensing procedures. Considering these hidden transaction costs, the nominal return on capital in less developed regions may not be sufficient to effectively attract capital inflows. In other words, while reducing cross-regional transaction costs of factors caused by natural conditions is important in narrowing regional disparities (i.e., through infrastructure investment), it may be more important to reduce such costs caused by regional governance.

The next step in reducing factor transaction costs across regions may focus on reshaping the relationship between local governments and companies as well as improving the business environment. For developed regions, we think it is necessary to break down institutional barriers that restrict factor inflows, and to provide support for newly established businesses and migrants. One example of this would be creating a more inclusive public service system that equally benefits all residents in the area regardless of hukou status. For less developed regions, we believe the key is to attract capital inflow by reducing administrative barriers and improving the business environment, where industrial specialization should be determined by a region’s comparative advantages. At the same time, less developed regions should improve their employment and training programs, providing skills training, employment guidance, and other labor protection services for migrant workers, which would further facilitate labor mobility across regions.

1.3.3 Intergenerational Disparity: Urgent Need for Further Policy Intervention

There are two noteworthy intergenerational issues in China. The first is the intergenerational imbalance caused by aging of the baby boom generation.⁴⁰ Aging means that the burden of old-age support will increase for the younger generation, with fewer and fewer young people producing goods and services to support the growing number of elderly retirees. To balance intergenerational income distribution, there are several policy options. China could consider raising the social security retirement age in response to longer life expectancy. Also, the pension scheme needs to be reformed. Under the pay-as-you-go system, contributions from current workers are used to support the older generation, whose benefits were often determined when they were young. In the presence of a demographic dividend, pension benefits for the elderly are better. However, given population aging, the pay-as-you-go arrangement will impose a greater burden on the younger generation. We believe there is a need for fiscal reform to raise funding for pension schemes.

The other intergenerational issue related to population aging concerns property assets. From the perspective of a person’s life cycle, property transactions play an important role in intergenerational income transfer. When they are young, people usually accumulate savings and then purchase property. After retirement, people sell the property to younger generations in exchange for income for their own consumption in old age. If the demographic structure is balanced, such a mechanism usually operates smoothly. However, in the context of fast population aging, property assets accumulated by older generations may depreciate significantly by the time older people want to sell them as the number of young home buyers declines. This could be seen as a spontaneous market mechanism to rebalance wealth equality between generations. If policies intervene to keep property prices from falling, the younger generation would bear a heavier financial burden due to formation of real estate bubbles. Thus, this real estate issue is also about intergenerational equity and sustainable development.

Second, economic inequality within one generation can exacerbate inequality of opportunity in the next generation. Equality of opportunity requires that a person’s income is determined primarily by his or her level of effort. In reality, however, disparity in family wealth is an important factor in inequality of opportunity. If resources are unevenly distributed across families, the amount of resources received by children differs across families. As a result, younger generations will face unequal opportunities because of differences in the economic conditions of older generations. Over the last few decades, along with the rising inequality, intergenerational mobility has worsened in the US. Children born in the 1940s had a 90% probability of earning more than their parents, but for children born in the 1980s, that probability dropped to 50%.⁴¹ A similar situation exists in China, where those born in the 1980s have less upward mobility than those born in the 1960s or 1970s.⁴² Such intergenerational imbalances may de-incentivize young people from working hard, which could be detrimental to social equity and economic efficiency. We think investment in public education and redistribution policies should be emphasized in order to interrupt the intergenerational transmission of social stratification and reduce inequality of opportunity.

1.4 Income Distribution from a Macro Perspective

1.4.1 Two Features of China’s Income Distribution

At the macro level, we wish to highlight two features of China’s income distribution. One is the relatively low share of GDP received by the household sector. The flow of funds table published by the NBS provides data on China’s income distribution at the macro level. The share of the household sector in China’s national income distribution has been declining over the past 30 years. In 1996–2010, disposable income of the household sector as a share of GDP fell from 69 to 56%, though the ratio has risen slightly in the last decade. In 2019, China’s household income as a share of GDP was 60%, still lower than that of major developed countries and emerging market economies such as the US, Japan, and India, and only higher than South Korea (Fig. 1.8).

Fig. 1.8

Source China Statistical Yearbook, Haver, CICC Global Institute

Household disposable income as a share of GDP. Note Data for each country is from the latest available year, with 2021 data for the US; 2020 data for the UK, Germany, France, Japan, Brazil, and South Korea; 2019 data for China; and 2018 data for India.

Another feature of China’s income distribution is the high share of government income in the primary income distribution. According to the flow of funds table in 2019, the share of GDP distributed to the general government sector was 17.8% in China, compared to 3.4% in the US, 7.7% in Japan, 9.5% in Germany, 10.4% in the UK, and 10.3% in South Korea.⁴³ The main reason for the government’s high share of income is that taxes in China are dominated by indirect taxes such as VAT, which are directly derived from transactions in goods and real estate markets. Unlike direct taxes such as personal income tax, indirect taxes account for income of the government sector in primary distribution. In addition, Chinese governments receive income directly from economic activities, including profits from state-owned enterprises (SOEs) and revenue from selling state-owned land use rights. In 2021, the total profit of SOEs (including the financial sector) was Rmb4.5 trn, and revenue from leasing land use rights was Rmb5.6 trn. In comparison, total profits of industrial companies above a designated size in same year were Rmb8.7 trn.

1.4.2 Problems of the Primary Distribution

There are three main components of household income in the primary distribution, namely compensation of employees from the labor market, returns from the capital market, and housing rents from the real estate market. The low income share of household sector suggests that these aforementioned markets fail to adequately distribute national income to households.

1.4.2.1 Low Labor Income Share in GDP

Labor compensation is the main source of household income. From the perspective of return on factor, the low income share of the household sector in GDP indicates that labor compensation makes up a relatively low share among factor income. Three sets of data can be used to measure the labor income share in GDP in China. These are the flow of funds table, the input–output table, and GDP data measured by the income approach at the provincial level. Among the three, the flow of funds table shows the highest labor income share, similar to the estimate provided by the International Labor Organization. The flow of funds table shows that labor income as a share of GDP has gradually declined in China since 1992, though it has gradually rebounded after reaching a low point in 2011, standing at 52% in 2019. Meanwhile, capital income as a share of GDP has fallen back from its peak in the early 2010s and has stabilized between 36 and 38% in recent years.

For international comparisons, we use the ratio of labor compensation to the sum of labor compensation and capital income.⁴⁴ The share of labor compensation in China is lower than that in most developed economies in the last 20 years (Fig. 1.9), which we attribute to two factors. First, the share of the secondary sector in GDP is much higher in China than in other countries. The high capital intensity of the secondary sector leads to a higher share of capital income and consequently, to a lower share of labor compensation. Over the past decade, as the share of the secondary sector in GDP has declined and the share of the tertiary sector has increased, the labor income share in GDP has also rebounded. Second, China still faces a serious challenge in terms of under-employment among the rural working-age population. The 2010 National Population Census showed that the urbanization rate of the 40–49 age group was 7 ppt lower than that of the 20–29 age group, which implies that middle-aged rural residents had difficulty moving to cities. These working-age people in rural areas remain subject to “hidden unemployment”, which can impede their progress in increasing in labor income.

Fig. 1.9

Source Wind, ILO, CICC Global Institute

The ratios of labor compensation to the sum of labor compensation and capital income in the enterprise sector. Note The International Labor Organization (ILO) adjusts income for each country by harmonizing self-employment income data.

It can be difficult for middle-aged rural workers who are included in the hidden unemployment category to find work in either the manufacturing or service sectors and settle in cities. Labor demand in the manufacturing industry is skewed toward young workers, and middle-aged workers have difficulty in performing physically demanding assembly line jobs. At the same time, the rapidly expanding service sector in cities generally requires workers to have higher education and professional backgrounds, and therefore does not do a good job of absorbing middle-aged rural workers who exit the manufacturing industry. Low-skilled service jobs in cities can absorb some middle-aged workers from rural areas, but this is conditional on labor mobility between urban and rural areas. The current urban labor market still has various barriers for rural migrants, and thus middle-aged rural surplus labor cannot easily move to the service sector in cities.

We think the labor market requires policy interventions to increase the share of labor income. The biased income distribution between capital and labor is the fundamental inequality in factor markets. The unequal bargaining power between capital and labor is reflected in the degree of concentration of factor. In general, capital supply is relatively concentrated, while labor supply is highly decentralized. Without institutional protection such as labor unions, labor is inevitably at a bargaining disadvantage relative to capital. In addition to bargaining factors, we believe China can enhance labor protection in the following ways. First, labor market discrimination based on rural or regional backgrounds should be eliminated by equalizing social protection and public services. Second, to address the structural mismatch between labor supply and demand, measures such as guiding employment preferences and providing skills training should improve the matching efficiency in the labor market. In particular, China can explore a worker protection system that is compatible with flexible employment patterns (e.g., gig workers), enabling labor protection keep up with emerging new business sectors.

1.4.2.2 Capital and Real Estate Markets

Over the past 20 years, the average return on capital was about 15% for industrial companies in China. However, the rate of return on household savings was relatively limited. One reason is that the capital market is still underdeveloped, and deposits dominate the financial assets of most households in China. The saving rate in the household sector is high, and the deposit interest rate is much lower than the return on capital. The other reason is the low dividend payments of Chinese enterprises. The flow of funds table shows that the household sector receives only a small portion of the operating surplus of the corporate sector. The dividend payout ratio of listed companies in China is lower than that in other major economies. From 2019 to 2020, the average dividend payout ratio of profitable companies in China’s CSI 300 constituents was about 32%. In comparison, the average dividend payout rate of profitable companies in S&P 500 constituents was 40% in 2019 and 54% in 2020.⁴⁵

In the real estate market, the dramatic rise in urban housing prices has increased the household wealth of many urban families. However, because the urban and rural real estate markets are not unified, the vast majority of rural households do not benefit from the urban housing market boom. A large number of migrant workers return to rural areas and build homes using their accumulated income, but do not generally benefit from housing price appreciation. Because of the high housing price-to-income ratio in Chinese cities, most urban households purchase housing for living in. Only a small number of households engage in housing speculation, but they receive extremely high returns from rising housing prices. Meanwhile, the high housing price-to-income ratio means relatively low returns on rents for landlords, resulting in relatively slow development of urban residential rental markets. High housing prices greatly increase the book value of household wealth, but do not necessarily lead to continuously growing income flows for urban households.

The difficulty in allocating factor returns to the household sector is partly related to institutional constraints. In the labor market, the institutional constraints mainly relate to the urban–rural dual structure and the intertwined problems of unequal social services related to employment, education, healthcare, and pensions. In the financial market, one problem is that large SOEs have easier access to credit from banks, but the profits of SOEs do not flow directly to the household sector. In the real estate market, problems mainly stem from the segmentation of urban and rural construction land markets, the monopoly in the primary land market, as well as the resulting land finance system of local governments. By transferring land-use rights, local governments receive high revenue in the primary income distribution, which is often used for government-led investments that circulate between governments, the real estate market, and the financial sector, rather than flowing directly to the household sector.

1.4.3 Insufficient Effects of Redistribution

The high share of the government sector in the primary distribution undermines the effect of fiscal redistribution. First, indirect taxes such as VAT account for a large proportion of the government’s revenue in the primary distribution. Some indirect taxes such as consumption tax are regressive and thus lack redistributive effect because the marginal propensity to consume is higher for low-income people. Given that there is almost no difference between pre-tax and post-tax Gini coefficients in China, the redistributive effect of taxation is limited.

Second, direct fiscal transfers to households play a major role in redistribution, but in China, government investment accounts for a large proportion of fiscal expenditure, while the share of direct transfers to households is relatively low. This is partly because land finance is an important source of local government revenue. This part of government revenue is usually invested in enterprises or the financial system, instead of being directly transferred to households or paid to civil servants. In the flow of funds table, this allocation result is reflected in the relatively low income share of the household sector after both the primary distribution and fiscal redistribution.

Finally, excessive policy interventions in the market may adversely affect market efficiency by inducing rent-seeking and misallocation of resources. Without effective law enforcement, rent-seeking activities are usually associated with corruption, which is detrimental to economic equality as well as equality of opportunity. It is an obstacle on the road to achieving common prosperity.