**Land Financialization, Uncoordinated Development of Population Urbanization and Land Urbanization, and Economic Growth: Evidence from China**

#### **Yunyang Ji <sup>1</sup> , Xiaoxin Guo 2,\*, Shihu Zhong <sup>2</sup> and Lina Wu <sup>2</sup>**


Received: 10 November 2020; Accepted: 26 November 2020; Published: 29 November 2020 -

**Abstract:** In recent years, it has become common practice for Chinese local governments to inject land assets into financing platform companies and use them as mortgage or credit guarantees to obtain bank loans and issue urban investment bonds, which is known as "land financialization". This study investigates the impact and mechanism of land financialization on the uncoordinated development of population urbanization and land urbanization in China. Theoretical analysis and empirical analysis results based on the data of prefecture-level cities in China from 2006 to 2015 demonstrate that land financialization by local governments is a significant cause of the uncoordinated development of population urbanization and land urbanization, and the pressure of urban economic development will strengthen this negative impact. Extended analysis further reveals that in areas where population urbanization and land urbanization are uncoordinated, land financialization, while promoting urban spatial expansion, will lower land use efficiency and have an inverted U-shaped influence on economic growth due to a weak agglomeration effect. The above conclusion shows that urbanization driven by debt-based investment is unsustainable. Efforts should be made to establish a financialization system that propels sound urbanization and to build a stable input linkage between land financialization and the supply of urban public service.

**Keywords:** land financialization; uncoordinated development of population urbanization and land urbanization; pressure of urban economic development; land use efficiency; urban economic growth

## **1. Introduction**

Urbanization is a vital symbol showcasing economic development in a country and is the universal choice used by developing countries to promote economic development. Existing research shows that urbanization can boost economic growth through promoting the accumulation of elements and the spillover of knowledge, expanding consumption and investment and delivering an agglomeration effect and economies of scale [1–3]. Further, it has become a critical issue facing countries across the world to facilitate economic growth based on faster and better-quality urbanization.

As the largest developing country, China's urbanization level has soared over the past 40 years, with its urbanization rate growing from 17.92% in 1978, the fledgling years of China's reform and opening up, to 59.58% in 2018. The number of permanent residents in urban areas has reached 831.4 million (China Statistical Yearbook, 2018). Urbanization has become a gigantic engine, after industrialization, for China's economic growth [4,5]. However, there is no denying that some contradictions and problems appear along with China's urbanization. The major problem is that population urbanization

lags behind land urbanization [6,7] (China's New Urbanization Plan (2014–2020), 2014). According to the author's estimation based on data from the China Urban Construction Statistical Yearbook, the pace of urban land expansion in China measured by built-up area is 1.44 times that of the increase in permanent residents from 1990 to 2000. The difference between the two from 2000 to 2015 further expands to 1.94 times, far beyond the reasonable level of 1.12 [8]. Additionally, in terms of the annual average growth rate, the difference between the annual average growth rate of urban built-up area in China and that of urban population is 3.21% from 1990 to 2006. This figure climbs to 3.47% from 2006 to 2015. Meanwhile, among three regions in China, the difference between the increased rate of land urbanization and population urbanization in the western area is the largest, followed by the central and eastern area (see Figure A1).

Existing literature shows that the uncoordinated development of population urbanization and land urbanization will result in a series of long-term negative effects on socioeconomic development, such as an increasingly distorted economic structure [6,9] and a widening income gap among urban and rural residents [10]. Ultimately, this uncoordinated development will obstruct urban-rural economic sustainable development and the healthy development of the city [11,12]. The cases in point are mushrooming "ghost cities", "empty cities", and the low occupancy rate in some development zones in China [13]. Indeed, promoting the coordinated development of land urbanization and population urbanization has become a critical issue in encouraging future urbanization in China. Resolving this issue will require the examination of its internal logic.

What are the reasons for the uncoordinated development of population urbanization and land urbanization in China? Existing literature has focused on the effect of some institutional factors, including the hukou system's obstruction of population urbanization in China [14,15], urban spatial expansion facilitated by the land-dependent fiscal system [12,16], and land urbanization propelled by regional competition under the fiscal decentralization system [17,18]. Moreover, the urbanization model in China is different from those in Western countries, such as governance structures for farmland conversion [19], the hukou system, internal migration, the taxation system, and the key role of local government in development [20]. Therefore, the behavior and intention of local governments should be considered in order to understand urbanization in China [21]. The above literature laid the foundation for our analysis of the uncoordinated development of population urbanization and land urbanization, but the impact of the land financialization mode, which local governments rely on, on the development of urbanization has been, to some extent, ignored.

In actual fact, local governments in China have established a huge number of financing platform companies in recent years, which directly or indirectly assume the functions of land reserve, development, and transfer in various cities [22]. It has become common practice for Chinese local governments to inject land assets into financing platform companies and use them as mortgage or credit guarantees to obtain bank loans and issue urban investment bonds, which is known as "land financialization". This land financialization model greatly enhances the financing effect of land transfer [23]. Although they take the same form as land capitalization, land financialization differs from land transfer greatly, because the former is a borrowing behavior, which creates implicit debts, while the latter is a one-time deal. According to the statistics for 84 major cities in China, the area and revenue from land mortgages have continued to rise and gradually exceed those of land transfer since the market-orientated reform of industrial land in 2006 (see Figure A2). Large-scale land financialization provides funding support for urban construction and land development, forming a Chinese-style urban construction investment and financialization model characterized by positive feedback between land financialization and urban infrastructure investment [24].

Thus, the question must be asked, does land financialization by Chinese local governments affect land urbanization and population urbanization? If the impact exists, does this kind of financialization lead to the uncoordinated development of population urbanization and land urbanization? Moreover, in what way does urbanization propelled through land financialization by local governments affect urban economic growth? These answers are the mainly logic connection of this study.

In effect, urbanization propelled via land financialization by Chinese local governments is, in essence, designed to promote urban construction investment through borrowing. Land financialization, while accelerating urban construction, generates huge debts for local governments [25]. As of the end of 2017, the local debts released by the authority amounted to 16.47 trillion yuan. In addition, urban development in China follows a "supply-driven" model led by local governments, where urban construction predates the agglomeration of industry and people. This means that economic agglomeration and economies of scale will determine whether a city can realize sustainable development. If local governments fail to attract enough people and companies after the construction is completed, construction investment which relies on borrowing will not be translated into an effective tax base and land tax revenue, which will probably trigger fiscal risks. In particular, in cities where unbalanced development is noted, population urbanization which is lagging behind reflects the insufficient spatial conglomeration of the population. The large-scale "enclosure for cities" movement gives rise to a low efficiency in land use [26]. Economies of scale are stunted, thus obstructing sustainable economic development in China.

This study focuses on the impact of land financialization by local governments on the uncoordinated development of population urbanization and land urbanization in China and its underlying mechanism. The contributions of this study mainly include: first, from the research perspective, previous research proceeds from land financialization and examines its stimulating effect on urban spatial expansion, while our study explores the uncoordinated development of population urbanization and land urbanization during urban construction and land development funded by local governments' debt-based financialization. This study also puts under the microscope the moderating effect of urban development pressure on the uncoordinated development of population urbanization and land urbanization caused by land financialization. Second, by combining the realistic background of "debt-oriented" urbanization financing and "supply-oriented" urban construction, this study analyzes the potential negative effect of land financialization on urban economic development and its working mechanism. Lastly, as financing platform companies are the main carrier allowing local governments to conduct land financialization, this study calculates the land financialization scale through the interest-bearing debt of financing platform companies for empirical research. This constitutes a beneficial attempt in the absence of relevant data.

#### **2. Institutional Background and Hypotheses**

#### *2.1. The Formation and Evolution of the Financing of Urban Development in China*

Local governments are major players in urban construction investment and public service supply in China [27–29]. The fiscal revenue and spending caused by Chinese local governments have a huge impact on urban development [30]. Since China's tax-sharing reform in 1994, financial power has been transferred to the central government, while responsibilities and spending have been laid on the shoulders of local governments [31]. The budgetary fiscal deficit of local governments has grown with each passing year, pushing local governments to expand extra budgetary sources of revenue. In the meantime, the newly revised Land Management Law of 1998 made Chinese local governments the only monopoly in land supply. While the market-orientated reform of urban housing in 2000 and the "bidding, auction, and listing" land transfer system that started in 2002 have made market-orientated land transfer possible in China. These reform measures have bred the commercial value of land, which gradually rises as the important asset for local governments. In this stage, land-related fiscal revenue for local governments mainly includes three components: land transfer fees, taxes related to the construction industry and the real estate industry (including farmland occupancy tax, urban land use tax, land appreciation tax, deed tax, and property tax), and land mortgage loans. Therefore, the fiscal revenue of Chinese local governments and urban construction has become increasing dependent on land.

Originally, Chinese local governments mainly obtained land transfer revenue through selling land use rights in primary markets. According to the China Land and Resources Statistical Yearbook 2001 to 2014, land transfer fees, known as "the secondary fiscal revenue", soared to 4.37 trillion yuan in 2013 from 59.5 billion yuan in 2000. The share of land transfer revenue in local fiscal revenue has increased from 9.3% to 63%. In some cities, such as Nanjing, Hefei, and Hangzhou, etc., the dependence on land finance (the ratio of budget revenue to land transfer fees) even approaches 100%, and remains at that level. Along with the development of the real estate market, the relevant tax revenue accordingly increased rapidly. Land finance therefore came into place. While compensating for fund shortage in local governments, the revenue also exerted far-reaching impacts on socioeconomic development in China. Said revenue was utilized in urban infrastructure construction and provided a funding guarantee for urbanization [32].

However, in China, along with deepening regulations in the real estate market and the growing pressure on economic downturn, land transfer revenue and relevant tax fees could hardly keep up with the substantial spending in urban construction, which ushered in the tipping point of land finance. According to Research on Real Estate's Contribution to Fiscal Revenue 2015<sup>1</sup> , the tax revenue in real estate in 2015, including property tax, urban land use tax, deed tax, farmland occupancy tax, and land appreciation tax, amounted to around 1.3 trillion yuan, a decrease of 3.6% compared to 2014, the first-ever decline in the past 15 years. Land transfer fees in 2015 registered negative growth for the fourth time in the past 15 years. The land revenue of local governments fell by nearly one half. Against this backdrop, establishing a local financialization platform through mortgaging land to financial institutions or using land transfer revenue as a guarantee to issue urban investment bonds has become an alternative for local governments to obtain land financing. Since then, the financing of urban development has transformed from land finance to land financialization in China. Particularly, after the financial crisis in 2008, China encouraged the establishment of local financing platform companies in order to raise supporting capital for the "funds for the "four-trillion stimulus plan". The number of local financing platform companies surged to 8221 at the end of 2009 from 3000 in the second half of 2008. In 2009 alone, more than 2000 new financing platform companies were added. These platform companies raised 75% of the supporting capital [33]. Land, as the major asset, played a key role in fund collecting.

Essentially, land and land-related revenue are deeply involved, from the establishment of local financialization platforms and asset injection, guarantees, and mortgages in borrowing and issuing bonds, to the repayment of principle and interest in the future. Extensive empirical research has verified the guarantee function of land in the issuance of urban investment bonds and its mortgage function in obtaining loans from banks. For example, the research of Shu, Xie, Jiang, and Chen (2018) [16] and Zhong, Chen, and Huang (2016) [34] indicates that the greater the price of urban land transfer or revenue, the higher the possibility of issuing urban investment bonds. The scale of the bonds issued will also accordingly be larger. This is because land use rights are often used as the guarantee, and land transfer revenues are promised to pay back debt during the issuance of urban investment bonds. Zhang, Nian, and Liu (2018) [23] found that there was a significant positive relationship between land transfer revenue and urban investment bonds. According to the debt auditing report by the National Audit Office from 2011 to 2013, as of the end of 2010 the outstanding obligation that local governments promised to pay through land transfer revenue stood at 2.547 trillion yuan, amounting to 38% of the total liable debts. This figure grew to 3.49 trillion yuan at the end of 2012—an increase of nearly 37% within two years. The outstanding obligation promised to be paid through land transfer revenue is shown in Figure 1. We can find that, by the end of 2012, the proportion

<sup>1</sup> Shanghai E-House Real Estate Research Institute, Local government's dependence on Land Finance, 29 February 2016. https://finance.sina.com.cn/roll/2016-02-29/doc-ifxpvzah8335807.shtml.

of outstanding obligation promised to be paid through land transfer revenue in Zhejiang Province, Tianjin Municipality, and Beijing Municipality exceeds 60%.

**Figure 1.** Debts promised to be paid by land transfer revenue in Chinese provinces. Note: data were retrieved from the Local Debts Audit Report of provinces in 2014.

The above evidence shows that large-scale urban land expansion and land transfer revenue provide a credit basis for Chinese local governments to obtain debt financialization and thus play a catalytic role in the expansion of local government debt [35,36]. Against the backdrop of severe dependence on debt-based investment, local governments' passion for "operating city" and "operating land" will be galvanized through constructing various development zones, new areas, and new cities, turning agricultural land into construction land and ultimately triggering precocious urban construction. Following the ideas of Chang and Lu (2017) [37], as of early 2014, 272 out of 280 prefecture-level cities in China had new built-up cities. The number of cities with new cities under construction accounts for 90% of all prefecture cities in China—the area of which amounts to 66,300 km<sup>2</sup> .

On the other hand, the employment of debt-based capital through land financialization by local governments showcases an obvious orientation to land urbanization. The majority of the capital was invested in areas related to land urbanization, such as municipal construction, land purchasing and storage, and transportation, with a proportion of approximately 70.38%. Only 10.5% of the capital was, however, invested in areas relevant to population urbanization, such as education, science, culture, healthcare, and affordable housing (National Audit Report on Debt). This means that land financialization does not promote population urbanization in the way that it does in facilitating urban spatial expansion and "land urbanization". On the contrary, the rapid rises in urban land price and housing price caused by land financialization may even suppress population urbanization. Research Group on China's Economic Growth (2011) [38] points out that the land urbanization and land-based urbanization financialization model led by local governments will accelerate land discount, heightening issues such as soaring land prices and housing prices while also having a crowd-out effect on the population and industries.

*Land* **2020**, *9*, 481

Based on the above analysis, we propose the first hypothesis.

**Hypothesis 1.** *The stimulating e*ff*ect of land financialization activities by local governments on land urbanization is stronger than that on population urbanization, resulting in the uncoordinated development of population urbanization and land urbanization.*

China's special system of the political centralization of state power and the separation of economic power effectively resolves the incentives for local governments [39,40]. However, it also brings about "yardstick competition" among different regions [41,42]. An official government promotion mechanism focusing on economic performance, which has been gradually formed since the 1980s, leads to "competition for growth" among government officials at a local level. The competition for promotion has been turned into competition in economic growth among various regions [43,44], putting pressure on economic development. Li and Zhou (2005) [45] found, based on empirical research, that local government officials with better economic performance to their credit during their tenure do receive more promotion opportunities. Considering this, local governments tend to realize more public spending related to economic development within a short period of time, such as urban infrastructure construction and land development, to achieve excellent economic development performance. This move has also significantly distorted the fiscal expenditure structure of local governments, showcasing an emphasis on infrastructure and a neglect of human capital investment and public service [46]. Similarly, in the supply of public goods, local governments are passionate about providing public goods of an economic nature while overlooking those of a social nature [47] The research of Caldeira (2012) [48] demonstrates that there is competition in investment among prefecture-level cities in China. Large-scale infrastructure construction and government investment require ample funding support. Extrabudgetary debt funds from land financialization simply loosen budgetary constraints. Therefore, under the decentralized system and official government promotional mechanism, "yardstick competition" emerges in land financialization among local governments, which is indicated by greater passion about, and dependence on, land financialization in regions with larger pressure on economic development.

In comparison, land urbanization relies on government investment and infrastructure construction, while population urbanization is more dependent on the supply of public goods which are social in nature. The biased public spending structure originating from promotional incentives for local governments' officials will indirectly strengthen land urbanization orientation in spending the capital raised. A vicious cycle in the investment and financialization process centring on land has been formed, augmenting the uncoordinated development of population urbanization and land urbanization. Meanwhile, in cities with greater pressure on economic development, local governments would have preferred to follow a spending structure orientated towards land urbanization to obtain greater achievements.

Therefore, it can be inferred that, under the competition mechanism for the promotion of officials, local governments under great development pressure are more dependent on land financialization model to raise urban construction funds, and their expenditure is more inclined towards land urbanization, thus heightening the uncoordinated development of population urbanization and land urbanization. We therefore propose the second hypothesis.

**Hypothesis 2.** *The stimulating e*ff*ect of land financialization on the uncoordinated development of population urbanization and land urbanization is more prominent in cities with greater pressure on economic development.*

#### *2.2. Land Financialization, the Uncoordinated Development of Population Urbanization and Land Urbanization, and Economic Growth*

Although each city has formed its own features in the course of development, the urbanization of these cities usually includes the continuous conglomeration of industries and populations, which promotes economic growth in cities, increased job opportunities, the inflow of population, and the expansion of urban land construction. We refer to this model as a market-led "demand-driven" model. Under this model, land expansion in cities is based on industrial conglomeration and population growth. Economies of scale can therefore be generated, realizing relatively high land use efficiency and ensuring sustainable economic development. In other words, sustainable economic growth is based on alternative and coordinated development between population urbanization and land urbanization.

However, in the government-led "supply-driven" urban development model in China, investment and construction rely on land financialization. Companies and populations are then attracted to the region through preferential policies on land and taxation [49]. This means that income from investment based on land financialization is decided by the conglomeration effect of urban construction on population and industry. However, when urban differentiation and regional difference become increasingly prominent, not all cities are able to attract enough companies and labour to the region. This is particularly true in areas where population urbanization and land urbanization are uncoordinated. Lagging-behind population urbanization itself reflects inadequate population conglomeration, ultimately resulting in a low land use efficiency [50,51]. In the meantime, land use efficiency is critical to sustainable economic development [52]. If precocious land urbanization could not deliver "increasing return to scale", sustainable economic growth in cities would face severe challenges.

Additionally, in terms of the effect of the transmission mechanism of urbanization on promoting economic development, population urbanization facilitates economic growth through population agglomeration and increasing consumption, while land urbanization does so via increments of fixed asset investments. In recent years, investments' contribution to economic growth has continued to decline during the adjustment of the economy structure. Increasing residential consumption is the key to realizing sustainable economic development. If population urbanization lags behind land urbanization over a long period of time, the effect of the demand structure, characterized by high investment and low consumption, on economic structure will have a threshold value according to the law of diminishing return on investment. The effect will shift from positive to negative once the demand structure passes the threshold.

To summarize, urbanization lacking industrial and population support could be temporarily sustained through government efforts and debt-based capital. Long-term economic growth relies on the performance of economic conglomeration and population urbanization. Land financialization leads to the uncoordinated development of population urbanization as well as land urbanization and is detrimental to sustainable economic development. Therefore, we propose the third hypothesis.

**Hypothesis 3.** *In areas with the uncoordinated development of population urbanization and land urbanization, due to weak conglomeration, land financialization will, while promoting urban spatial expansion, lower land use e*ffi*ciency, generating an inverted U-shaped e*ff*ect on economic performance.*

#### **3. Model, Data and Variable**

#### *3.1. Econometric Model*

Based on previous literature concerning land financialization, population urbanization, and land urbanization, this study constructs the following econometrics model to test the impact of land financialization on the uncoordinated development of population urbanization and land urbanization:

$$
\text{land\\_urbm\_{il}} = \alpha\_1 + \beta\_1 \\
\text{land\\_financialization} \\
\mu\_{il} + \sum \gamma\_1 \mathbf{X}\_{il} + \mu\_l + \delta\_l + \varepsilon\_{il} \tag{1}
$$

$$pop\\_urban\_{it} = \alpha\_2 + \beta\_2 land\\_financialization\_{it} + \sum \gamma\_2 X\_{it} + \mu\_i + \delta\_t + \varepsilon\_{it} \tag{2}$$

$$
\text{numco\\_development}\_{\text{il}} = \alpha\_3 + \beta\_3 \\
\text{land\\_fiancalization}\_{\text{il}} + \sum \gamma\_3 \\
\text{X}\_{\text{il}} + \mu\_i + \delta\_l + \varepsilon\_{\text{il}} \tag{3}
$$

$$\text{umco\\_development}\_{\text{it}} = \alpha\_4 + \beta\_4\\\text{land\\_finiancialization}\_{\text{it}} + \text{qpressure}\_{\text{it}} + \epsilon$$

$$\text{pland\\_financialization}\_{\text{it}} \* \text{pressure}\_{\text{it}} + \sum \gamma\_4 X\_{\text{it}} + \mu\_i + \delta\_{\text{t}} + \varepsilon\_{\text{it}} \tag{4}$$

where the dependent variable in model 1 is *land*\_*urbanit*, representing the land urbanization in city *i* at year *t*, which is measured by the logarithm of the urban built-up area. The dependent variable in model 2 is *pop*\_*urbanit*, representing the population urbanization in city *i* at year *t*, which is measured by the logarithm of permanent residents in city districts. The dependent variable in models 3 and 4 is *unco*\_*developmentit*, indicating the dummy variable of the uncoordinated development of population urbanization and land urbanization in city *i* at year *t*. The value 1 demonstrates the existence of the uncoordinated development of population urbanization and land urbanization, or the value will be 0. In models 1-4, the independent variable is *land*\_ *financializationit*, representing land financialization scale in city *i* at year *t*. The subscripts *i* and *t* represent the *i*-th city and the *t*-th year, respectively. *Xit* is the set of control variables, as discussed above. Further, µ*<sup>i</sup>* represents the municipal fixed-effects and is used to control the unobservable but invariant characteristics of cities; δ*<sup>t</sup>* represents the year fixed-effects, and is used to control the systematic differences in cities over time. ε*it* represents other city-level natural endowments and socioeconomic factors that could potentially impact the uncoordinated development of population urbanization and land urbanization.

In models 1–3, we focus on the coefficients of β1, β2, and β3, which represent the net effect of the land financialization on land urbanization, population urbanization, and the uncoordinated development of population urbanization and land urbanization, respectively. In model 4, the moderating variable is *pressureit*, representing the pressure on urban economic development in city *i* at year *t*; we focus on the coefficient of η, which represents the moderating effect of urban economic development pressure on the uncoordinated development of population urbanization and land urbanization caused by land financialization.

The fixed-effect (FE) panel data method is first used to control factors that do not vary with time. However, there may be a reverse causality between land financialization and the uncoordinated development of population urbanization and land urbanization. Land financialization offers funding support for land development and spatial expansion and gives rise to the uncoordinated development of population urbanization and land urbanization. Meanwhile, increases in construction land further galvanize land-based mortgages and guarantees in cities with unbalanced development, adding fuel to land financialization. The Generalized Method of Moments (GMM) and two stage least square (2SLS) regression are therefore used to address this problem by introducing exogenous variables.

#### *3.2. Data Source and Variable Selection*

Our main data is drawn from the China Statistics Yearbook, the China Municipal Statistics Yearbook, the China Population and Employment Statistics Yearbook, the China Urban Construction Statistical Yearbook, and the China Land and Resources Statistical Yearbook between 2007 and 2016. Samples of Tibet and some other autonomous prefectures are excluded. Data on local financialization platforms comes from the Wind Economic Database (The Wind Economic Database pairs over 1.3 million macroeconomic and industry time series with powerful graphics and data analysis tools to give financial professionals the most comprehensive insights into China's economy). Missing values are filled using the interpolation method. It is important to note that, in the Chinese context, a city is often not a municipal unit (i.e., a large continuous urban area), but rather an administrative unit that with hierarchy ranking lower a province but higher a county in the Chinese administrative structure. A Chinese city

usually comprises a main central urban area (with the same name as the "city") and a much larger surrounding rural area [53]. In this study, only the information regarding the city's central urban (municipal) area is used. Thus, our analysis is not very sensitive to changes in the city's administrative boundaries. The variable definitions and statistical descriptions of samples used in the analysis will be recorded as shown below.

#### 3.2.1. Dependent Variables

The key dependent variables include: ln *land*\_*urbanit*, the logarithm of city-level built-up area, which is the important index of land urbanization; ln *pop*\_*urbanit*, the logarithm of city-level permanent residents, which is the important index of population urbanization; *unco*\_*developmentit*, the dummy variable of the uncoordinated development of population urbanization and land urbanization. In reference to the practice of Xie (2016) [54], this study employs the elastic coefficient of urban built-up area growth (i.e., the growth rate of urban built-up area/the growth rate of permanent residents in a municipal district) to measure the lagged-behind level of population urbanization relative to land urbanization. Currently, the internationally recognized appropriate value for the elastic coefficient is 1.12. Further, following the research of Gail (2003) [8], this study defines the uncoordinated development of population urbanization and land urbanization as Equation (5) below. When *growth rate o f urban built*-*up area growth rate o f permanent residents in municipal district* <sup>≤</sup> 1.12, *unco*\_*developmentit* will equal 0, which means that the land urbanization growth rate relative to the population urbanization growth rate is within an appropriate range, and the uncoordinated development of population urbanization and land urbanization does not exist. When *growth rate o f urban built*-*up area growth rate o f permanent residents in municipal district* > 1.12, *unco*\_*developmentit* will equal 1, which means that the population urbanization growth rate severely lags behind the land urbanization growth rate, and the uncoordinated development of population urbanization and land urbanization does exist. That is,

$$\text{umco\\_development}\_{\text{if}} = \begin{cases} 0, & \text{Growth rate of worm built-up area} \\ 1, & \text{Growth rate of permanent residuals in manipul distribution} \\ 1, & \text{Growth rate of uranium built-up area} \end{cases} \tag{5}$$

We have drawn up a map related to the development of population urbanization and land urbanization. This is shown as follows.

Figure 2 represent the lagged-behind level of population urbanization relative to the land urbanization of Chinese cities in 2015. Coordinated urbanization represents that the land urbanization growth rate relative to the population urbanization growth rate is within an appropriate range, and the uncoordinated development of population urbanization and land urbanization does not exist. Uncoordinated urbanization represents that the population urbanization growth rate severely lags behind the land urbanization growth rate, and the uncoordinated development of population urbanization and land urbanization does exist. We find that uncoordinated urbanization exists in most cities in China.

\_௧

௪௧ ௧ ௨ ௨௧ି௨ ௪௧ ௧ ௧ ௦ௗ௧௦ ௨ ௗ௦௧௧

\_

 

ln \_௧

ln \_௧

௪௧ ௧ ௨ ௨௧ି௨ ௪௧ ௧ ௧ ௦ௗ௧௦ ௨ ௗ௦௧௧

> 1.12 \_௧

,1 12.1 ,0 12.1

\_௧

≤ 1.12

(6)

ncoordinated development of population urbanization and land urbanization in Chinese cities. **Figure 2.** The uncoordinated development of population urbanization and land urbanization in Chinese cities.

#### 3.2.2. Independent Variable

The land financialization scale in prefecture-level cities is the key independent variable in this study. In China, local governments have no right to issue government bonds to raise funds for infrastructure construction and other public welfare projects, so local governments have built some financing platform companies for financing. Further, local governments could rely on the financing platform companies to obtain bank loans through land mortgages and to issue urban investment bonds by taking land transfer revenue as a guarantee. Considering this, the present study selects the interest-bearing debt of local financing platform companies, including current liability and long-term liability, as the proxy variable for the land financialization scale. The specific calculation formula is shown below.

*Land financialization level* = *short term liability* (*short term borrowing* + *notes payable* + *non current liabilities due within one year* + *other current liabilities* + *short term bond payable*)+ *long term liability* (*long term borrowing long term bond payable*)

#### 3.2.3. Moderating Variable

Referring to the existing literature, this study utilizes economic development catch-up pressure (including economic development level and fixed-assets investment etc.) to reflect the pressure of urban economic development. The calculation formula is shown below.

*Economic development catch up pressure* = *economic indicators o f the pre f ecture level city which is one place ahead in ranking in the province economic indicators in the respondent pre f ecture level city* (7)

where economic indicators include GDP per capita and the total investment in fixed assets as the proportion of GDP.

## 3.2.4. Control Variables

Control variables in the study mainly include factors affecting land urbanization and population urbanization, such as: (1) the economic development level (ln *GDPit*), which is measured by the logarithm of GDP per capita [55]; (2) industrial structure (*ind*\_2*it and ind*\_3*it*), which is represented by the ratio of the second and third industries' added value in GDP [14]; (3) population density (ln *pop*\_*densityit*), which is measured by the logarithm of the city-level population density [53]; (4) fiscal expenditure (ln *Fis*\_*expenditureit*), which is represented by the logarithm of local public expenditure per capita [56]; (5) economic openness (*eco*\_*opennessit*), which is measured by the ratio of accumulated foreign direct investment (FDI) in capital stock [57]; (6) fixed-asset investment (ln *fix*\_*investmentit*), which is measured by the logarithm of fixed-asset investment per capita [58].

**Table 1.** Descriptive statistics of the data for 277 Chinese cities during the period 2006–2015.

Descriptive statistics of the key variables are shown in Table 1.


#### **4. Measuring the Impact of Land Financialization on the Uncoordinated Development of Population Urbanization and Land Urbanization**

#### *4.1. Benchmark Results*

Table 2 presents the regression results regarding the impact of land financialization on land urbanization and population urbanization. As can be seen, in models 1 and 2, *land*\_ *financializationit* is significantly and positively correlated with ln *land*\_*urbanit*. This indicates that land urbanization significantly facilitates land urbanization. Additionally, in models 3 and 4 *land*\_ *financializationit* is positively correlated with ln *pop*\_*urbanit*, but this is not significant. This reveals that the impact of land financialization on population urbanization is not significant. Therefore, land financialization by local governments may give rise to the uncoordinated development of population urbanization and land urbanization.


**Table 2.** Estimation results for the impact of land financialization on land urbanization and population urbanization.

Notes: figures in parentheses denote the standard errors of the respective coefficients, while \*\*\*/\*\*/\* indicate significance at the 1%/5%/10% levels, respectively.

We further investigate the impact of land financialization on the uncoordinated development of population urbanization and land urbanization. Table 3 presents the regression results using the linear probability model (LPM), the probit analysis method (PROBIT), logistic regression analysis (LOGIT), IV-PROBIT, and GMM. According to the results of models 1–3, *land*\_ *financializationit* is significantly and positively correlated with *unco*\_*developmentit*. This implies that land financialization significantly leads to the uncoordinated development of population urbanization and land urbanization in China.

Moreover, what can be seen from model 2 is that there exists a negative relation between population density and the uncoordinated development of population urbanization and land urbanization, thus demonstrating that increasing population density helps ease the uncoordinated development of population urbanization and land urbanization. The relation between fiscal spending and the uncoordinated development of population urbanization and land urbanization is positive and significant, which is attributable to the economic development orientation of fiscal spending and the urban construction model being dependent on government investment. Meanwhile, growth in the proportion of secondary industry also fuels the uncoordinated development of population urbanization and land urbanization, which is associated with the competition in attracting businesses and investments among local governments and the construction of large-scale industrial parks.


**Table 3.** Estimation results for the impact of land financialization on the uncoordinated development of population urbanization and land urbanization.

Notes: figures in parentheses denote the standard errors of the respective coefficients, while \*\*\*/\*\*/\* indicate significance at the 1%/5%/10% levels, respectively.

Considering the estimation bias induced by the reciprocal causation that land financialization and the uncoordinated development of population urbanization and land urbanization always interact with each other, the spatial lagged term of land financialization as the instrumental variable is introduced, and the 2SLS method is employed to re-examine the relationships in our study. The result in model 4 shows that the coefficient of *land*\_ *financializationit* remains significantly positive. In addition, considering institutional inertia and path dependence, this study introduces the one-phase lagged term of *unco*\_*developmentit* as the control variable. The *Hansen* test in model 5 demonstrates the efficacy of the instrumental variables. The regression coefficient remains positive in model 5, verifying the robustness of the result.

In summary, the above regression result corroborates hypothesis 1—that is, that the enabling effect of land financialization by local governments on land urbanization is stronger than that on population urbanization, which results in the uncoordinated development of population urbanization and land urbanization. The reason for this is, as explained previously, that one of the features of land financialization is that it binds government debts with land. Land transfer fees are not only the reference of credit standing for local governments' current borrowing, but a vital source of capital in repaying local governments' debt. Therefore, local governments are highly motivated to channel debt-based capital into land reserve and development activities. This forms a continuous cycle which propels the rapid expansion of urban space. However, local governments fail to establish a stable investment linkage between public services in cities such as education, science, culture, healthcare, and land financialization. Coupled with rising land and housing prices, the citizenization of rural-to-urban migrants moves ahead slowly, leading to the uncoordinated development of population urbanization and land urbanization.

#### *4.2. Robustness Checks*

This study conducts robustness checks on benchmark regression results, including replacing measurement indicators of land urbanization and population urbanization, changing sample range, and increasing the number of control variables. First, this paper refers to the practice of Xiong and Gao (2012) [59] and replaces the city district area, which represents land urbanization, with the urban road area to calculate the uncoordinated development of population urbanization and land urbanization. Detailed regression results are shown in model 1. Second, we replace the total population in urbanized city districts, which denotes population urbanization, with non-agricultural population calculated through household registration to obtain the uncoordinated development of population urbanization and land urbanization. Detailed regression results are given in model 2. Third, this study excludes 58 cities which have undergone administrative upgrading from county to district so as to expel the influence of administrative region adjustment. The regression results in Table 4 reveal that the impact of land financialization on the uncoordinated development of population urbanization and land urbanization is significantly positive, showcasing the robustness of the benchmark regression results. Fourth, we only employ samples after 2008 for regression to avoid potential influence by the surge of financialization platforms after the financial crisis in 2008. Results are shown in model 4. Finally, this paper utilizes new land supply for construction (*lnland*) as a control variable. The expansion of the urban built-up area is affected not only by factors from the demand side, such as population and economy, but also factors from the supply side, such as land for construction. Of particular note is that land for construction is determined by the administrative distribution of government in China and is therefore of greater significance. The results of model 5 indicate robustness.


**Table 4.** Robustness checks on the impact of land financialization on the uncoordinated development of population urbanization and land urbanization.

Notes: figures in parentheses denote the standard errors of the respective coefficients, while \*\*\*/\*\*/\* indicate significance at the 1%/5%/10% levels, respectively.

#### *4.3. Moderating E*ff*ect of Urban Development Pressure on the Uncoordinated Development of Population Urbanization and Land Urbanization Caused by Land Financialization*

China has implemented an official selection mechanism focusing on officials' achievements. The indicator that can best reflect the achievement of an official is GDP per capita. Besides this, investment currently remains the major "carriage" driving China's economic growth. Under the pressure of urban economic development, local governments have the impulse to boost investment and regard it as a vital means to promote economic development. Therefore, this study takes the backwardness of cities in terms of GDP per capita and fixed-asset investment relative to their counterparts to measure development pressure.

Hypothesis 2 states that the stimulating effect of land financialization on the uncoordinated development of population urbanization and land urbanization in cities with greater development pressure is more prominent—i.e., the pressure of urban economic development regulates land financialization's stimulating effect on the uncoordinated development of population urbanization and land urbanization. In order to test this hypothesis, the present study constructs Equation 3. If η, the coefficient of interaction term between land financialization and development pressure, is positive, the stimulating effect of land financialization on the uncoordinated development of population urbanization and land urbanization will be more obvious in regions with greater development pressure. Last, under the yardstick competition mechanism, there may be interaction on strategies for land financing among different regions. Therefore, we constructed a Spatial Dubin Model (SDM) to investigate the spillover effect of competition on land financing among different regions. Then, we added the spatial lagged term of land financing size into the regression model to examine whether competition on land financing among different regions affects urbanization unbalance. In terms of weight matrix, we constructed an economic weight matrix based on the GDP per capita of cities from the same province.

According to the result in Table 5, the coefficients of interaction terms are significantly positive in five models. From this, development pressure is constructed based on the GDP per capita in models 1 and 2, while it is constructed based on the proportion of fixed-asset investment in models 3 and 4. Development pressure caused by lagging-behind GDP or fixed-asset investment will intensify the motivation and incentive of local governments to expand urban construction and land development though land financialization. Hypothesis 2 is therefore proved. The regression results in Model 5 and 6 demonstrate emulation strategies for land financing among cities, which further aggravates the degree of uncoordinated development of population urbanization and land urbanization.


**Table 5.** Estimation results for development pressure, land financialization, and the uncoordinated development of population urbanization and land urbanization.


**Table 5.** *Cont.*

Notes: figures in parentheses denote the standard errors of the respective coefficients, while \*\*\*/\*\*/\* indicate significance at the 1%/5%/10% levels, respectively.

#### **5. Land Financialization, the Uncoordinated Development of Population Urbanization and Land Urbanization, and Economic Growth**

This section analyzes the potential impact of land financialization, which stimulates the uncoordinated development of population urbanization and land urbanization, on urban economic sustainable development to examine the hidden risks behind the development model characterized by debt-based urbanization financialization and supply-driven urban construction.

The essence of urbanization driven by land financialization adopted by Chinese local governments is debt-based urban construction investment (Pan et al., 2017) [18]. During this process, the investment revenue for local governments comes mainly from economic growth due to population and industrial conglomeration. Currently, economic growth is indicated by the added value of secondary and tertiary industry. Therefore, this study, in reference to the practice of Lu (2011), divides the added value of secondary industry and tertiary industry by built-up area to obtain the land use efficiency and uses it to denote investment return on urban spatial expansion [50]. The basic logic here is that if land financialization decreases the land use efficiency, debt-based urban spatial expansion could not generate a scale effect and economic conglomeration. The return on investment is therefore insufficient. This study divides samples into the unbalanced group and the balance group. If land financialization causes a decline in land use efficiency in the unbalanced group compared to the balance group, hypothesis 3 is corroborated. Furthermore, we test whether there exists a threshold value for the effect of land financialization on economic growth—in other words, whether the effect of land financialization on economic growth turns to an inverted U shape.

To test hypothesis 3, we construct the following regression model.

$$\text{land\\_use}\_{it} = \alpha\_4 + \beta\_4 \\ \text{land\\_financialization}\_{it} + \sum \gamma\_4 X\_{it} + \mu\_i + \delta\_t + \varepsilon\_{it} \tag{8}$$

$$\text{growth}\_{\text{il}} = \alpha \mathfrak{z} + \beta \mathfrak{s} \text{land\\_f} \\ \text{animalization}\_{\text{il}} + \lambda \mathfrak{s} \text{land\\_f} \\ \text{finalization}\_{\text{il}}^2 + \sum \gamma \mathfrak{z} X\_{\text{il}} + \mu\_{\text{l}} + \delta\_{\text{l}} + \varepsilon\_{\text{il}} \quad \text{(9)}$$

where *land*use*it* and *growthit*. denote the land use efficiency and growth rate of GDP per capita, respectively. Control variables include city-level population density (ln *pop*\_*densityit*), human capital (*human\_rateit*), economic openness (*eco*\_*opennessit*), fiscal expenditure (ln *Fis*\_*expenditureit*), fixed-asset investment (ln *fix*\_*investmentit*), and industrial structure (*ind*\_2*it and ind*\_3*it*).

Table 6 displays the impact of geographical factors on land use efficiency and urban economic growth. According to the regression result of model 1 in Table 6, land financialization lowers the land use efficiency in cities with the uncoordinated development of population urbanization and land urbanization. This might be because land financialization does not generate economic conglomeration or increasing returns to scale. The return on investment is low. The regression results of model 3 indicate that the first-order term of land financialization is significantly positive, while its second-order term is significantly negative. This signifies that the effect of land financialization on economic growth in cities with the uncoordinated development of population urbanization and land urbanization showcases an inverted U shape. That is to say, after surpassing the threshold value, the effect of land financialization on economic growth will transit from a positive one to a negative one. These characteristics are not found in cities with the coordinated development of population urbanization and land urbanization.


**Table 6.** Estimation results for land financialization, the uncoordinated development of population urbanization and land urbanization, and sustainable development.

Notes: Figures in parentheses denote the standard errors of the respective coefficients, while \*\*\*/\*\*/\* indicate significance at the 1%/5%/10% levels, respectively.

#### **6. Conclusions and Discussion**

Nobel Prize-winning economist David Stiglitz has said that two events of the 21st century will have the greatest impact on the world: "America's high-tech industry and China's urbanization." The rapid development of urbanization in China cannot be separated from the promotion of local governments, and land financialization is an important means for the government to lead the urbanization process. For a long time, the gap between fiscal revenue and expenditure forces local governments to use land to obtain as much extrabudgetary income as possible, and this gradually forms the fiscal situation of relying on land. In recent years, the urbanization financing mode has been transformed from land transfer to land financialization, which has resulted in huge local government debts. By the end of 2019, the local government debt ratio has risen to 24.3%. What impact does this have on the pattern of urbanization?

In this paper, we investigate the effect and mechanisms of land financialization on the uncoordinated development of population urbanization and land urbanization in China for 277 Chinese cities during the period spanning 2006 to 2015. Moreover, the pressure of urban economic development is included as a mediation variable to measure how much it accounts for the effect of land financialization on the uncoordinated development of population urbanization and land urbanization. Finally, this paper examines the hidden risks behind the development model characterized by debt-based urbanization financialization and supply-driven urban construction.

The three main findings are that, first, land financialization significantly leads to the uncoordinated development of population urbanization and land urbanization. On the one hand, Chinese local governments' dependence on land-based urbanization financialization will intensify their motivation in land development and conveyance, leading to chaotic urban expansion. On the other hand, the expenditure structure of debt-based capital financed through land showcases an obvious orientation towards land urbanization and a weak "pushing" and "pulling" effect on the citizenization of rural-to-urban migrants. Population urbanization is relatively slow.

Second, the pressure of urban economic development positively regulates the stimulating effect of land financialization on the uncoordinated development of population urbanization and land urbanization. In cities with greater development pressure, the stimulating effect of land financialization on the uncoordinated development of population urbanization and land urbanization is more prominent.

Third, urbanization propelled by land financialization is unsustainable, because in regions with the uncoordinated development of population urbanization and land urbanization, land financialization, while promoting urban spatial expansion, lowers the land use efficiency due to weak conglomeration effect and exerts an inverted U-shaped influence on economic growth.

In the Chinese context, this finding is as expected. Since the financial crisis in 2008, local governments of China have established a huge number of financing platform companies, obtained bank loans and issued urban investment bonds through land mortgages or guarantees, and created large-scale invisible local government debts. This debt capital is mainly invested in urban public facilities and land development and becomes significant funding support for urbanization. A unique urbanization financialization model with Chinese characteristics has been gradually formed. This debt-based financialization model, which is highly reliant on land, further intensifies local governments' passion for "operating city" and "operating land", leading to a large-scale movement known as "enclosure for urbanization". Constructions for development zones, new cities, and new areas in various forms are fledgling. However, supply-driven urban construction without the due consideration of demand factors is destined to cause the uncoordinated development of population urbanization and land urbanization, which is unsustainable.

The conclusion of this study carries some policy implications. First, efforts should be made to explore financialization systems that facilitate sound urban development. A local tax revenue system with property tax being the main tax ought to be established during the early days to divert local governments from blind passion about land development. Besides this, a stable input linkage between land financialization and public service supply should be forged to deliver a pulling effect on the citizenization of rural-to-urban migrants. Furthermore, land, population, and industry are the most important elements in economic activities. Sustainable economic development can only be realized when land supply matches the trend of population and industrial conglomeration. The government should set up and improve cross-regional land resource regulating systems and land supply systems. Last, efforts should be made to tighten the budgetary constraints on local governments and to improve the utilization efficiency of debt capital and return on investment, while also establishing management systems that guard against and resolve local debt risks. On the whole, the key to new urbanization lies in population urbanization. The government should emphasize the quality of urbanization, promote integration between cities and industry, and support population conglomeration through enhanced public service to ensure the sustainable development of the urban economy.

Due to constraints in access to data, there are deficiencies in the research results which need further consideration. (1) Limitations in the measurement of variables: The existing studies on land financialization in China usually use urban investment bonds as a proxy variable, while we use the liabilities of local financing vehicles to estimate the scale of land financialization for the first time. There will still be a deviation from the real scale. In follow-up studies, additional micro-data of the land mortgage of local financing vehicles need to be compiled for further analysis. (2) Not considering the issue in an international context: It is a great challenge to define the boundaries of the urbanization

process in the world, since we do not have the data on urbanization and land financialization in the world. To clearly identify the boundaries of the urbanization process in the world needs a great deal of theoretical analysis, logical deduction, and empirical evidence. We therefore chose to study the impact and mechanism of land financialization by local governments on the uncoordinated development of population urbanization and land urbanization in the context of China, following the practice in the literature [4]. We also have added the Spatial Dubin Model (SDM) to investigate the spillover effect of competition on land financing among different regions. Studying urbanization and financialization in an international context needs to be explored and new solutions developed in follow-up research.

**Author Contributions:** Conceptualization, Y.J. and X.G.; methodology, Y.J., L.W., and S.Z.; validation, Y.J., X.G., and S.Z.; formal analysis, Y.J. and X.G.; data curation, Y.J. and S.Z.; writing—original draft preparation, Y.J., X.G., and S.Z.; writing—review and editing, Y.J., L.W., X.G., and S.Z.; visualization, Y.J. and X.G.; supervision, Y.J.; project administration, Y.J.; funding acquisition, X.G. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by Fundamental Research Funds for the Central Universities, grant number CXJJ-2019-363.

**Conflicts of Interest:** The authors declare no conflict of interest.

## **Appendix A**

24

0

10

20

30

40

50

60

13

16.31

16.7

22

21.7

29.15

25.82

**Figure A1.** The trends of urban population and built-up area.

33.39 32.28

1.32 1.8 2.59 3.53 4.8 5.95 7.76 9.51 11.33

30.08

36.7

40.39

34.87

27.73

45.1

22.49

49.08

1.25 <sup>1</sup> 1.6 2.71 3.15 2.69 4.2 4.26 3.25

2007 2008 2009 2010 2011 2012 2013 2014 2015

4.56

7.77

The whole sample of China

3.21

6.8

8.6

1.8

Eastern China

3.28 3.4

2.94

8.63

Western China

5.23

1990-2006 1990-2006 1990-2006 1990-2006 2006-2015 2006-2015 2006-2015 2006-2015

Annual average growth rate of population (%)

Annual average growth rate of built-up area during

The whole sample of China

6.23

Central China

(%)

2.14 2.01 1.88

5.61 5.14 5.28

Eastern China

Central China

3.47 3.13 3.39

3.05

Western China

7.78

4.73

**Figure A2.** Land transfer and mortgage from 2007 to 2015. Note: data were retrieved from Report on China's Land Resources 2008–2016.

#### **References**


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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## *Article* **Research on the Impact of Land Circulation on the Income Gap of Rural Households: Evidence from CHIP**

**Congjia Huo <sup>1</sup> and Lingming Chen 1,2,\***


**Abstract:** With the continued development of the economy, the income gap among Chinese rural households continues to widen. The land system plays a decisive role in developing "agriculture, rural areas and farmers" and land circulation is a factor in the increase in income inequality among farm households. Based on the 2013 China Household Income Project (CHIP), this article used the re-centered influence function (RIF) regression method to empirically test the impact of rural land circulation on the income gap of rural households in China in three regions: the central, eastern and western regions. The quantile regression tested the impact mechanism of income inequality of rural households from the perspective of labor mobility and land circulation. The empirical results showed that land circulation increases the income inequality of rural households. The theoretical mechanism test proved that the dynamic relationship between land circulation and labor mobility increases rural household income. However, this increase has a greater effect on rural households with a high income and a small effect on rural households with a low income, resulting in a further widening of the income gap. Therefore, while increasing the income of rural households through land circulation, the government should also consider income equity. Finally, this article puts forward the policies and opinions on land reform and provides a brief discussion on the future direction of development.

**Keywords:** land circulation; income gap; rural households income; re-centered influence function; quantile regression

## **1. Introduction**

Since the founding of New China, Chinese farmers have experienced changes in farmland, agricultural management and farmland property rights systems. With the implementation of the rural revitalization strategy, the development of urban and rural areas has been coordinated, reforms have been comprehensively deepened, and farmers' incomes have continued to increase. However, this increase in income has also been accompanied by a continuous expansion of the income gap within rural areas. The "Report on the Development of Rural Households in China (2018)" posited that rural household income inequality is rising in China. The Gini coefficient increased from 0.45 in 2011 to 0.535 in 2017, significantly higher than the internationally recognized warning line of 0.4 [1]. Figure 1 shows the Gini coefficient and Theil index estimated from quintile data of the per capita disposable income of rural households. These data came from the "China Yearbook of Household Survey" from 2005–2019.

**Citation:** Huo, C.; Chen, L. Research on the Impact of Land Circulation on the Income Gap of Rural Households: Evidence from CHIP. *Land* **2021**, *10*, 781. https://doi.org/10.3390/ land10080781

Academic Editors: Marina Cabral Pinto, Amit Kumar and Munesh Kumar

Received: 27 June 2021 Accepted: 22 July 2021 Published: 25 July 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

**Figure 1.** The Gini Coefficient and Theil Index of Per Capita Disposable Income of Rural Households in China from 2005 to 2019. Note: the data comes from the compilation and calculation of the Chinese Household Survey Yearbook.

onomy has taken too long to exceed people's expectations. There have been nomic transformation has become the eternal theme of "always on the road". This unbal-It can be seen from Figure 1 that the Gini coefficient of rural household income has risen steadily, and the Gini coefficients calculated by quintile subgroups exceed 0.35, with a higher rise in the Theil index. In 2019, the Gini coefficient and Theil index declined slightly. China continues to explore a reform of the rural system, but the transformation of the rural economy has taken too long to exceed people's expectations. There have been twists,stagnations, and even deviations in the reform process. Although this slow economic transformation avoids the risk of economic and social disorder, it has also gained time for the formation and growth of interest groups. With a lag of political reforms, economic transformation has become the eternal theme of "always on the road". This unbalanced transformation path is fully reflected in the field of income distribution. Although the income of rural households continues to increase, the income gap within rural areas continues to widen, as does the income gap between urban and rural areas. There have been strange phenomena such as the intertwining of reasonable and unreasonable income gaps and the coexistence of open and transparent distribution models and hidden distribution mechanisms. In contrast, inequality in rural areas restricts economic development, reduces the welfare generated by increased incomes, and affects social stability.

s. The land system plays a decisive role in the development of "a ture, rural areas and farmers". he enthusiasm of households' production, the government strictly prohibits There are many reasons for income inequality among rural households. Existing research mainly explores the physical capital, human capital and social capital owned by rural households. The land system plays a decisive role in the development of "agriculture, rural areas and farmers". The household contract responsibility system was implemented at the beginning of the founding of New China. Although it has greatly increased the enthusiasm of households' production, the government strictly prohibits the sale of land use rights. In recent years, the circulation system of land contract rights has become increasingly stable, and the government has liberalized the land circulation system. The process of urbanization and industrialization has accelerated, many rural laborers have flowed into cities and towns, and the relationship between people and land has been continuously adjusted. Figure 2 shows the change process of the land circulation scale in China from 1984 to 2014.

statistical report of China's rural policies and reforms and the statistics of the Ministry **Figure 2.** The scale of land circulation in China from 1984 to 2014. Note: calculated according to the annual statistical report of China's rural policies and reforms and the statistics of the Ministry of Agriculture, where the degree of land circulation is the proportion of the circulation land area to the total cultivable land area.

China. In 2003, the "Contracting Law" clarified million mu. According to the published data in the "Statistical Annual Report on China's " the area of rural land circulation accounted for 35.9% – changed the original distribution pattern of land, reconstructed farmers' livelihood As shown in Figure 2, in 1984, the degree of land circulation was less than 1% in China. In 2003, the "Contracting Law" clarified, for the first time, the specific measures for the circulation of land management rights to protect said rights. This figure has grown rapidly, and by 2012 this figure exceeded 10%. In 2014, the land circulation area was 403 million mu. According to the published data in the "Statistical Annual Report on China's Rural Policies and Reforms (2019)," the area of rural land circulation accounted for 35.9% of the total area of contracted land in China in 2019 [2]. The substantial increase in the area of land circulation is reshaping the pattern of rural income. Households who have transferred into land carry out large-scale production and reduce land fragmentation. The young and middle-aged farmers who have transferred out their land choose non-agricultural operations and migrant workers, and their income is also increasing. The increasing scale of land circulation has reshaped the new pattern of rural man–land relationships, changed the original distribution pattern of land, reconstructed farmers' livelihood modes, and directly affected the income distribution of rural households.

"hidden agricultural revolution". Population China is currently in the process of a "hidden agricultural revolution". Population pressure has caused the per capita arable land in rural areas to steadily decline, so that it is difficult for farmers to maintain their livelihoods; as such, they must rely on auxiliary labor to meet their normal living needs. The increase in non-agricultural employment in rural areas is conducive to increasing the income of rural households. At the same time, with the advancement of new urbanization, the scale of land circulation has become larger and larger, which has promoted the large-scale development of agriculture. Therefore, discussing the effects of land circulation and labor mobility on the income inequality of rural households and comprehensively grasping the income distribution effects of land system reform can help to better promote the integration of urban and rural areas and realize the strategy of rural revitalization. This article attempts to answer two questions: first, does land circulation further widen the income inequality of rural households? Second, how does land circulation affect the income inequality of rural households?

The remainder of this paper is arranged as follows: Section 2 introduces the institutional background of land circulation and summarizes relevant literature; Section 3 discusses the impact mechanism of land circulation on the income inequality of rural households; Section 4 uses the data from the 2013 China Household Income Project (CHIP) to empirically analyze the impact of land circulation on the income gap of rural households, and to test its theoretical mechanism; Section 5 summarizes the conclusions and provides recommendations, and looks forward to future research directions.

#### **2. Institutional Background and Literature Review**

#### *2.1. Institutional Background*

The prerequisite for land circulation is that rural households have the legal right to transfer. Before China's reform and opening up, a collectivized rural land system was implemented, but this method greatly inhibited farmers' enthusiasm for production, resulting in extremely low agricultural productivity. After the reform and opening up in 1978, China began to implement the household contract responsibility system, which greatly increased the enthusiasm of farmers [3]. The property rights system of agricultural land in China has realized the "separation of the two rights," and the full collection of land property rights has come under collective ownership. In the "Minutes of the National Rural Work Conference" in 1982, the sale and lease of land was explicitly prohibited. In 1984, the national government proposed that "the right to land contracted management remains unchanged for 15 years." With the circulation of rural labor and the increase in non-agricultural business practices, the separation of the contracting and management rights of agricultural land became more serious. In 1993, the law began to recognize the separation of land contracting and management rights, allowing the paid circulation of land use rights. In 2003, the "Contracting Law" was introduced to clarify the specific measures for the circulation of land management rights. By 2005, land circulation rights accounted for 5%–6% of the contracted arable land area, and the figure even reached 8%– 10% in developed coastal areas. With the rapid development of China's economy and the acceleration of urbanization, many young and middle-aged people from rural areas flocked to cities, further stimulating land circulation. According to statistics from the Ministry of Agriculture, the total area of contracted arable land was 228 million mu in China in 2011, accounting for 17.8% of the household contracted land area.

After preliminary exploration, the Ministry of Agriculture issued "Opinions" in 2011, and gradually began a nationwide pilot project on land right confirmation and registration. In 2014, China issued the document "Several Opinions of the State Council of the Central Committee of the Communist Party of China on Comprehensively Deepening Rural Reform and Accelerating the Advancement of Agricultural Modernization." "Separating ownership rights; contract rights; and the right to use contracted rural land" is the basic direction of the reform of the agricultural land property rights system in the new era. Therefore, this document has stabilized contract rights while allowing land management rights to be mortgaged to financial institutions for financing. In 2016, the government further proposed to equally protect the land management rights acquired by business entities following the circulation contract. This has ensured stable land management activities and has initiated a comprehensive reform of the "separating ownership rights; contract rights; and the right to use contracted rural land."

Land circulation can form a large-scale land operation, reduce the fragmented use of land [4], liberate rural productivity, and support urbanization. Therefore, the main purpose of the "separating ownership rights; contract rights; and the right to use contracted rural land" reform is to promote land circulation, improve agricultural productivity and competitiveness, and at the same time, to ensure the rights of operators. However, there are still significant limitations in the circulation of rural land. First of all, the definition of land property rights is unclear. The existing laws and regulations do not regulate the relationship between land circulation and land contracts, which has led to an increasing number of disputes about land contract rights, which virtually increases the cost of land circulation. Second is the structural limitation of urban and rural areas in China. Migrant workers and peasants who transfer out their land cannot obtain urban household registration and cannot enjoy complete education and medical benefits. Therefore, they tend to keep their land contract rights and entrust their relatives and friends to cultivate them instead. In

addition, there are also other reasons, such as the reluctance of the elderly to leave their homeland and their attachment to the land, which also restricts the land circulation.

#### *2.2. Literature Review*

The separation of the right to use and ownership of land generates land rent [5]. Moreover, with diminishing returns to land, the price of land circulation determines the amount of land rent. The circulation period is short, so the price of land circulation depends only on the average annual income of the land. At the same time, the conditions for the generation of land rent are related to the price of agricultural products, the fertility of the land, the geographical location and the relationship between supply and demand [6]. When the transaction cost is zero, market transactions can achieve an effective allocation of land resources [7], so scholars cannot think that land rent is suppressed [8]. The generation of land rent is the basis of land circulation. China has changed the land structure of contracting production to households and liberalized land circulation, and land distribution has changed from absolute equality to relative equality. The land was redistributed to the peasants with higher productivity [9]. The land system has a profound effect on the income distribution of rural households [10]. Before further reforming the land system, it is essential for the government to carefully consider the impact of the reform on the income of rural households and income inequality. Therefore, research on the impact of land circulation on the income inequality of rural households has gradually become a popular topic. The research mainly focuses on two aspects, namely the income effect of land circulation and the distribution effect of land circulation.

#### 2.2.1. Income Effect of the Land Circulation

The existing literature on land circulation and the income of rural households analyzes the mean effect of the impact of land circulation on the income of rural households under the framework of a linear model. There are two main points of view: first, the net income of peasants before and after land circulation has not changed significantly. There is a two-way causal relationship between the level of non-agricultural income of peasants and land circulation. The impact of early land circulation on the non-agricultural income of peasants is relatively weak [11]. Second, land circulation has generally increased the income of rural households, created income for rural households, and reduced poverty. Scholars have held this view in majority [12–14]. The land rent and income from migrant work brought about by land circulation accounts for most of the income growth of rural households, which is stable and sustainable [15,16]. The study by Xiao Han and Anlu Zhang [17] from the perspective of land circulation found that land circulation has a positive effect on the income of transfer-in rural households, but has no significant effect on the income of the transfer-out rural household. Fei Chen and Weijuan Zhai [18] pointed out that renting out land is beneficial for increasing the income of rural households and reducing the incidence of poverty. However, the welfare effect is significantly different between different family groups. Xiangyong Wang et al. [19] studied the changes in farmers' income before and after land circulation and found that land circulation increased farmers' property income.

In addition, the income effect of land circulation needs to be considered from two aspects. On the one hand, because of the characteristics and factor endowments of a rural household, the benefits they receive from the land circulation market are different [20]. Land circulation generally increased the income of rural households, but this may be the result of the pull of high-growth rural households, however, it exaggerates the role of land circulation. The results of testing that land circulation does not affect the income of rural households and may also be offset by increasing income and decreasing income. On the other hand, there is the problem of the "selection bias" of the sample. Whether a rural household participates in land circulation is a non-random "self-selection" behavior. However, this self-selection bias has not been corrected when examining the income effect of land circulation on the different types of rural households, which has also brought about estimation problems.

#### 2.2.2. Income Distribution Effect of the Land Circulation

An increase in the absolute income level does not imply that land circulation has a positive effect on income distribution. There are two main views on the income distribution effect of land circulation. First, land circulation has widened the income gap of rural households. Early research considered that land circulation was the choice and behavior of rural households with a high income [21]. In other words, only the powerful class can receive high returns on land circulation [22], while the interests of small farmers are sacrificed, leading to further widening of the income gap [23]. The constraints of credit rationing make it difficult for poor rural households to obtain benefits from the land rental market [24]. Möllers and Meyer used the PSM method to analyze the impact of labor migration on income inequality and poverty in rural Kosovo [25]. In recent years, some scholars have used quantile regression to analyze the effect of land circulation on the income gap of rural households. For example, Junping Guo [26] used a quantile regression model to investigate regional income, finding that the circulation of farmland has widened the income gap between rural households in the eastern and central regions. From the perspective of different income classes, the transfer inflow of farmland has promoted an increase in the income of poor and low-income households, resulting in some high-income households. Although land transfer inflow and outflow can increase income, land circulation exacerbates income inequality [27–29]. The research for Changliang Shi [30] found that the income-increasing effect of land circulation is heterogeneous for rural households with different income levels. Rural households with middle and high-income levels obtain greater benefits from land circulation than rural households with a low income. Second, land circulation can narrow the income gap between rural households [31]. Guanghua Wan [32] constructed a regression decomposition framework using rural household data to study rural income inequality in China, and found that the land circulation between poor rural households reduces income inequality. Land circulation increases the income level of rural households with low income and can alleviate the inequality caused by non-agricultural employment [33]. However, some scholars believe that the income distribution effect of land circulation has a selection effect among heterogeneous rural households, and the mechanism of action for a rural household in different income ranges is different [34]. The disadvantage is that most studies only compare the income effects of rural households with different income levels who participate in land circulation, and fail to answer quantitatively how land circulation widens the income inequality of rural households.

In general, the existing literature agrees that land circulation can effectively increase the income of rural households, but the perception of the income distribution effect of land circulation is still ambiguous. Previous studies have made more use of quantile regression. However, the data are too rough to infer any effect of land circulation on the income gap of rural households by relying solely on the difference in the regression coefficients in different quantiles. Moreover, this approach would ignore the internal mechanism of the income distribution effect of land circulation and the mechanism of the effect of other economic and social factors on the income distribution of rural households in the process of land circulation. There is almost no literature involved in the research on its influence mechanism and degree of influence. Shi, C.L., et al. [35] and Yang. Z et al. [36] estimate the contribution of land circulation to the income gap of rural households using a Fields decomposition. However, the decomposition method is strictly restricted by the form of the income equation and the measurement index of the income gap, and the decomposition of the constant term has not been well handled and explained. Liang Y et al. [37] discussed the effects of labor mobility and land circulation on the income of rural households, respectively. They use the propensity score matching (PSM) model to explore the effect of land circulation on the income of rural households. This can effectively alleviate the bias problem caused by the "self-selection" of the income effect, but it does not deeply explore the mechanism of the dynamic relationship between labor mobility and land circulation on the income distribution of rural households.

Compared to previous literature, there are two possible contributions of this article: first of all, it provides a new perspective to deepen the understanding of the impact of land circulation. The existing literature studies focused on the effect of land circulation on agricultural productivity and rural household income. There were not many studies on income distribution and inequality. This article has supplemented this aspect. Second, we analyze the causes of rural household income inequality from the perspective of labor mobility, and provide new connotations for income distribution theory. Existing studies rarely consider the impact of the dynamic relationship between labor mobility and land circulation on the income inequality of rural households. However, the contradiction between more people and less land has always been one of the main contradictions in China's agricultural development. The relationship between the two may have a more profound impact on income distribution than traditional economic factors such as material capital and family characteristics. Therefore, this article uses the form of interaction terms to analyze the contribution rate of labor mobility and land circulation to different income levels, to deconstruct the mechanism of land circulation on the income inequality of rural households, to provide a theoretical basis and decision-making participation for broadening farmers' income increase channels.

#### **3. Theoretical Mechanism**

To analyze the theoretical mechanism of land circulation in the income gap of rural households, it is necessary first to clarify peasants' motivation to engage in land circulation. The decision of land circulation is based on the "cost-benefit" principle. When nonagricultural productivity is greater than agricultural productivity, a rural household will choose to transfer the outflow of the land. When the benefits of land operation from rural households exceeds the opportunity cost of farming the land, a rural household will choose to transfer the inflow of the land and expand the production of land on a large scale. To study the effect of land circulation on the income inequality of rural households, we can start from the income function of rural households. Assuming that the income of a rural household *Y* is completely determined by the scale of land circulation *T*, the size of the non-agricultural labor force population *S*, and the family characteristics *Z*, then the income of rural households can be expressed as:

$$\mathbf{Y}\_{\mathbf{i}} = f(T, \mathbf{S}, \mathbf{Z}) \tag{1}$$

In order to obtain the income gap of rural households, now the variance of both sides of the equation is calculated simultaneously, and we can obtain:

$$Var(Y\_i) = \delta^2 Var(T\_{i\nu} \mathcal{S}\_{i\nu} Z\_i) \tag{2}$$

Here, we fixed family characteristics, then *δ* in Equation (2) is the income effect of land circulation and the non-labor scale. In theory, land endowments in a perfectly competitive land market will not cause an income gap, and X is a constant at this time. However, in reality, the land market is incomplete. At this time, *δ* will vary with region, rural family, climate and time. *δτ* is the income effect variable of the interaction term of land circulation and the non-labor scale. Assuming that the income effects of land scale, land circulation, and the non-labor scale are independent of one another, then the income gap can be expressed as:

$$
\mu\_\delta^2 Var(T\_{i\tau\nu} \mathcal{S}\_{i\tau\nu} Z\_{i\tau}) + \mu\_\tau^2 Var(\delta\_\tau) + Var(T\_{i\tau\nu} \mathcal{S}\_{i\tau\nu} Z\_{i\tau}) \cdot Var(\delta\_\tau) \tag{3}
$$

where *µ<sup>δ</sup>* is the expected value of the income effect, and *µ<sup>τ</sup>* is the expected value of the interaction term between the scale of land circulation and the scale of non-agricultural labor. From Equation (3), it can be seen that the income gap of rural households is not only related to the expected values of both, but also depends on the scale of land circulation and the scale of non-agricultural labor. When the expectation of the income effect is 0, the income

gap of rural households is also 0. When the expectation and the income effect are not 0, there will be an income gap in a rural household. Land circulation is the reallocation of land resources based on market-oriented means, focusing more on efficiency rather than fairness. Therefore, a rural household with different income levels faces unequal opportunities in the land circulation market and different benefits from land circulation. Analyzing the effect of land circulation from the perspective of non-agricultural labor mobility, the flow of labor is oriented: it only flows from low-income regions to high-income regions. For rural areas, the mobility of labor optimizes the allocation of resources and adjusts the structure of the agricultural industry. However, the flow of labor from agriculture to non-agricultural employment takes away the productivity of agricultural production, and most of the labor flow out is more competitive. In particular, many of the migrant workers who leave their hometowns are young and middle-aged. The elderly and children stay in their hometowns, and the remaining family members cannot afford excessive agricultural production. Therefore, rural households choose to transfer out their excess land to achieve optimal allocation of their household resources. This shows that there is a dynamic relationship between land circulation and labor mobility. When this dynamic relationship is higher, the wider the peasants' income channels, and the greater the impact on the income of rural households. The income gap of rural households is determined by the dynamic relationship between land circulation and labor mobility. From the characteristics of rural households with different incomes, for low-income families, they can only choose to cultivate the existing land, because they cannot afford to pay enough land rent and the cost of non-agricultural operations or migrant workers. In addition, compared to high-income households, low-income households are more dependent on land and are less willing to lease out the rights of using contracted land. Therefore, low-income rural households are easily excluded from the land circulation market. High-income rural households can avoid land fragmentation through land inflow, and large-scale agricultural production can further reduce costs and increase profits. As a result, the income of high-income rural households is becoming higher and higher, while the income of low-income rural households remains the same or rises slowly alongside economic development, meaning the income gap between rural households is further widening. Analyzing this mechanism specifically in terms of agricultural and non-agricultural operation productivity, it can be divided into two parts: on the one hand, in terms of agricultural productivity, highincome farmers are better able to afford the high cost of renting land and are more likely to acquire new technologies in the process of agricultural production. Combining the potential level of human capital and the ability to obtain market information, high-income rural households have higher returns on agricultural production. On the other hand, from the perspective of non-agricultural production activities, rural households with a low income have relatively weak anti-risk capabilities and experience more restrictions on employment in the non-agricultural market. For example, the education level of family members with a low income may be lower than the average. Meanwhile, rural households with a high income can integrate family resources through the land circulation to maximize their comparative advantages in non-agricultural fields. Since the 21st century, the process of urbanization has accelerated, the price of urban labor has become much higher than the income of agricultural production, and rural households with a high income have started moving to non-agricultural operations earlier. Therefore, although land circulation has increased the income level of most rural households, it has also widened the income inequality of rural households to a certain extent.

#### **4. Empirical Research**

#### *4.1. Model Construction*

The re-centered influence function (RIF) regression method proposed by Firpo [38] is different from other regressions methods in terms of the explained variables in said RIF regression. The explained variables in RIF regression can not only be the income level of residents or other statistics, but must also be the statistics of income inequality such as the quantile, variance and Gini coefficient obtained based on the influence function. Therefore, we can establish a direct relationship between the impact factors and the degree of income inequality. This article used RIF regression to discuss the effect of rural household land circulation on the rural household income gap. Considering that the Gini coefficient can better describe the degree of income inequality, this article used the Gini coefficient to measure the income gap in net income per capita of rural households. In the RIF regression framework, the benchmark regression model is constructed as follows:

$$Gini(inco) = \alpha\_0 cland + \alpha\_1 X + \varepsilon \tag{4}$$

where the explained variable *inco* is the per capita disposable income of rural households and *Gini* (*inco*) is the Gini coefficient of the disposable income of rural households; the explanatory variable *cland* is the land circulation area of rural households, which is the sum of the area of land transfer outflow and inflow; *X* is the control variable, which is used to mitigate the estimation error caused by the omitted variable(the selection of the control variable will be described in detail later); and *ε* is the random error term. The theoretical mechanism of land circulation affecting the income gap of rural households has been discussed above. Next, this article used quantile regression estimation to test this theoretical mechanism. Quantile regression was first proposed by Koenker and Bassett [39] in their systematic study, and it can accurately describe the effect of explanatory variables on the range of variation of the explained variables and the shape of the conditional distribution. Therefore, this article used quantile regression and established the following regression model:

$$Q\_{\tau}[\ln \dot{m} c o | \mathcal{Y}] = \beta\_{0,\tau} + \beta\_{1,\tau} blab \* sland + \sum \beta\_{i,\tau} CV + \omega\_{\tau} \tag{5}$$

where the explained variable *Qτ*[ln *inco*|*Y*] is the logarithm of the per capita annual disposable income of rural households at the *τ* quantile. The explanatory variable is the product of the proportion of household non-agricultural labor force *bland* and the land area *sland* transfer out from rural households, which represents the dynamic relationship between labor mobility and land circulation. *CV* refers to the other control variables, which are the same as the control variables in Equation (4), and *ω* is a random disturbance term.

#### *4.2. Data Source*

The Chinese Household Income Project (CHIP) conducted five household surveys in 1989, 1996, 2003, 2008 and 2014, and collected data of the income and expenditure of urban and rural households from 1988, 1995, 2002, 2007 and 2013, respectively. This article selected the data from the 2013 CHIP, which covers 18,948 household samples and 64,777 individual samples, selected from 234 counties and districts of 126 cities in 14 provinces, including 7175 urban household samples, 11,013 rural household samples, and 760 outdoor migrant workers samples. According to the research content of this article, only the data of the rural households in the questionnaire were retained, and missing values and unreasonable data were excluded, thus, a total of 10,262 valid data were obtained. These valid data were distributed across 14 provinces, namely, Shanxi, Henan, Anhui, Hubei, Hunan, Gansu, Yunnan, Sichuan, Chongqing, Beijing, Liaoning, Jiangsu, Shandong and Guangzhou. After sorting, we divided the data into the central, western, and eastern regions, with 3963, 2705, and 3594 data, respectively.

#### *4.3. Variables*

Explained variable: per-capita annual disposable income of rural households (*inco*); the unit is yuan/person. The CHIP data selected "2013 household disposable income" divided by "total household population". Disposable income mainly included wage income, net operating income, property income and transfer income.

Explanatory variable: land circulation area (*cland*); the 1st unit is *hm*<sup>2</sup> . We used the sum of the area of land transfer out (*sland*) and the area of land transfer in (*tland*) of rural households. From the CHIP data, we deleted the data of rural households who transferred the outflow and inflow of land at the same time. In addition, rural households were the only inflow and outflow of land.

The control variables mainly included two aspects, namely the characteristics of the head of the rural household and the characteristics of the family. The characteristics of the head of the household included:


Meanwhile, family characteristics included:



#### **Table 1.** Definitions of variables and descriptive statistics.

#### *4.4. Benchmark Regression Results*

Table 2 shows the estimated results of the RIF regression benchmark for the impact of land circulation on the income gap of rural households. The per capita annual disposable income of rural households was used as the explained variable, and land circulation was used as the explanatory variable. Columns (1)–(3) report the empirical results of the central, western, and eastern regions, respectively. Column (4) shows the empirical results of the national data without a fixed province effect, while Column (5) shows the empirical results of the national data after fixing the province effect. Comparing the results from Columns (1)–(6), it can be seen that the area of land circulation further widens the income gap of rural households.

From Column (5), after controlling for the provincial factors that do not affect the income gap of rural households over time, the larger the land circulation area in the country as a whole, the bigger the income gap of rural households. Moreover, comparing Columns (4) and (5), the coefficient increased from 0.0014 to 0.016 after controlling for the province. The specific impact mechanism will be discussed in detail in the next section. Among the control variables, the variables of whether to participate in a professional cooperative economic organization, family size, the size of the non-agricultural labor force, and the area of land operated by the family have a significant effect on the income gap of rural households. Among them, the variable of participation in a professional cooperative economic organization can widen the income gap of rural households. Meanwhile, the other variables can narrow the income gap of rural households. Families participating in professional cooperative economic organizations can obtain certain advantages in agricultural production, so this factor can widen the income gap of rural households. In the context of the one-child policy, the family population is limited; a large family size and a large non-agricultural labor force can narrow the income gap among rural households. The contracted land area can also reduce the income gap between rural households; this is because large-scale agricultural production reduces production costs. However, a rural household with less land typically chooses non-agricultural management to realize the optimal allocation of limited land resources, which increases the overall income level while also reducing the income inequality of rural households.

The national data on rural households were divided into three regions. Comparing Columns (1)–(3), it can be seen that the most significant effect of land circulation on the income gap of rural households was in the central region. This is because Henan and Hunan, the major grain-growing provinces, are in the central region. Before the emergence of large-scale migrant workers, the main economic source of income for a rural household was agricultural production. Cities in the eastern region are relatively more developed, relying mainly on a non-agricultural economy to drive employment. In particular, the eastern coastal cities have benefited from the reform and opening-up policy and no longer rely on agricultural production. Meanwhile, the population in the western region is relatively small, and the level of land rent is generally low; therefore, the ratio of land rent to the total income of rural households is relatively low. Most rural households are unable to achieve an increase in income in this way, so the effect of land circulation on income inequality among rural households was shown to be non-significant.


**Table 2.**Baseline estimation results of the impact of land circulation on the income gap of rural households.

Note:*t*-values in parentheses, \*\*\*, \*\*, and \* represent 1%, 5%, and 10% significance levels, respectively.

#### *4.5. Robustness Test*

The RIF regression program operates with robust standard errors by default; this can effectively weaken the endogenous problems caused by the omission of variables, etc., and avoid heteroscedasticity from interfering with the estimation results. In addition, the per capita net income of rural households and the behavior of land outflow and land inflow do not exist exactly in the same year. Therefore, the possibility of endogenous factors between land circulation and the net income of rural households was relatively slight. This paper uses a series of tests to confirm the robustness of the conclusions, such as changing the income gap measurement indicators, replacing explanatory variables and explained variables. The results are shown in Table 3.


Note: *t*-values are in parentheses, and \*\*\* and \* represent 1% and 10% significance levels, respectively.

Inequality is measured by variance. Variance is a widely used indicator in the issue of inequality, as well as the Gini coefficient. To verify the robustness of the empirical results, this article uses the variance of the logarithm of household disposable income per capita to replace the Gini coefficient. The regression results are shown in column (1) of Table 3. The core explanatory variable land circulation is positive at the 1% significance level, which is consistent with the result of the benchmark regression.

The income gap is measured using 80–20th quantile values. Quantile distance can better test the income gap between the highest and the lowest income group. This article uses the 80–20 quartiles to replace the Gini coefficient to test the robustness of the empirical results. The regression results are shown in column (2) of Table 3. *cland* is significantly positive at the 1% level, the coefficient of *cland* in the corresponding regression is 0.0223. This shows that when the area of land transfer to all rural households in the sample increases by 1 unit, the difference between the 80th quantile and the 10th quantile of the per capita disposable income of rural households will increase by 0.0223, an increase of 2.2%. After the replacement of the inequality measurement indicators, they are consistent with the benchmark results, indicating that the empirical conclusions of this article have not changed due to different income gap indicators.

Replacement of explanatory variables. The area of land circulation is composed of the area of land transfer outflow and inflow. After rural households have transferred inflow land, they can expand the scale of agricultural production and increase their income, which in theory can better reflect the further widening of the income gap. Therefore, this article replaces the explanatory variable with the area of land transferred inflow by rural households. The regression results are shown in Column (3) in Table 3. The estimated results are positive at the 10% significance level, which is consistent with the benchmark regression results.

Replacement of the explained variable. Compared with income, consumption is more stable and more reliable. It can better reflect the living conditions of rural households and is a more accurate indicator of inequality. Therefore, this article replaces the explained variable with the Gini coefficient of per capita consumption of rural households. The regression results are shown in Column (4) in Table 3. The core explanatory variables are significantly positive at the 10% level, which is consistent with the benchmark regression results, indicating that the conclusions of this article are not affected by the metrics of the explained variables.

#### *4.6. Analysis of the Influence Mechanisms*

The previous section mainly confirmed that land circulation increases the income gap among rural households. This part mainly focuses on analyzing the mechanism of the effect of land circulation. The government is continuing to further lift the restrictions on non-agricultural employment, is continuously improving the non-agricultural employment market, and is reducing the gap of registered residence between urban and rural areas, thereby providing more employment opportunities for young migrants workers. With the rapid economic development in developed cities, there is a greater labor shortage. The income from migrant workers and non-agricultural business income is significantly higher than that from agricultural production. More young and middle-aged laborers from families with a low income choose to give up their farmland and switch to non-agricultural operations or go out to work, which increases family income. Table 4 shows the regression results of the dynamic relationship between labor mobility and land transfer out on the per capita disposable income of rural households by region. The labor mobility indicator here was the ratio of non-agricultural labor over the total household population, and the per capita disposable income of rural households was processed in logarithm.

Column (1) in Table 4 shows the OLS estimation. Based on the results of this OLS estimation, it can be seen that the coefficients of the interaction terms between labor mobility and land outflow are significantly positive, and passed the 1% significance level test for both the national region and the central, western, and eastern regions. This shows that the interaction term of labor mobility and land outflow increases the income of rural households. Moreover, the dynamic relationship in the eastern region is significantly higher than that of the other two regions. This is because there are more developed cities and more non-agricultural employment opportunities in the eastern region. The estimation result of OLS was used to compare the result of the quantile regression. The quantile regression results of the different quantile points are given in Columns (2)–(6), respectively, which are the 10th, 30th, 50th, 70th, and 90th points. From the results of the quantile regression, as the degree of dynamic relationship increased, the per capita disposable income of rural households also increased. From the national data, it can be seen that the interaction term has the greatest promotion effect on middle-income families. However, the promotion effect of high-income households is significantly higher than that of lowincome households, which means that the benefits of "rich people" from land circulation are significantly greater than those of "poor people", which naturally further increases the income gap. In addition, these estimated coefficients are significant in the different quantiles, however the coefficients are not identical, indicating that rural households with different income levels do not benefit equally from land circulation. Combining the results of quantile regressions by regions, especially the western and eastern regions, the dynamic relationship between high-income households with labor mobility and land outflow has increased. The promotion effect on the per capita income of rural households is much higher than that of low-income households, with the coefficient even exceeding 0.1 in the highest quintile. Therefore, land circulation not only causes inequality in the allocation of agricultural land resources in villages, but also further aggravates this inequality through labor mobility, forming the "Matthew effect" where the rich get richer, leading to further widening of the income gap among rural households.


**Table 4.** Regression results of the dynamic relationship between labor mobility and land transfer outflow on the per capita disposable income of rural households by region.

Note: *t*-values in parentheses, \*\*\*, \*\*, and \* represent 1%, 5%, and 10% significance levels, respectively. The control variables are not listed due to space limitations.

#### **5. Conclusions and Recommendations**

The main purpose of China's current rural revitalization strategy is to promote rural development, increase farmers' income, and narrow the income gap of rural households. Under the background of "separating ownership rights; contract rights; and the right to use contracted rural land," the scale of land circulation is getting larger and larger, and stable land property rights are the foundation of rural development. Based on the 2013 China Household Income Project (CHIP), this article used the re-centered influence function (RIF) regression method to empirically test the impact of rural land circulation on the income gap of rural households in China in three regions: the central, eastern, and western regions. The final result were as follows.

First, as a result of the implementation of the "separating ownership rights; contract rights; and the right to use contracted rural land" by the government, the legitimate rights and interests of land operators are now protected. Land circulation has improved agricultural production efficiency and has liberated labor productivity. Surplus peasants are moving to cities to work and earn an income. Coupled with the acceleration of urbanization, the overall income of rural households has improved. For example, rural households with a low-income lack funds for agricultural production and have limited access to land, but have a surplus of labor. Thus, young and middle-aged people of low-income rural households choose to transfer out their land, and then go out for work or go into non-agricultural employment, thereby greatly increasing the total family income. Rural households with a high-income can increase their income by transferring in their land, expanding the scale of agricultural production and reducing the marginal costs. Therefore, the continuous increase in the scale of land circulation has greatly increased the income of rural households as a whole.

Second, land circulation widens the income inequality of rural households. The inequality of market opportunities leads to different amounts of land circulation by different income groups, resulting in income inequality within groups. In addition, the differences in the abilities and factor endowments between groups also leads to different income returns in land circulation among different income groups. From the central, western, and eastern regions, the region where land circulation has the most significant impact on the income gap of rural households is in the central region. There are several large agricultural provinces in the central region, where farmers are more dependent on land. The adjustment of income distribution is also more sensitive to changes in the land system.

Third, from the perspective of labor mobility, the impact mechanism shows that the interaction term of land outflow and the proportion of non-agricultural labor have a more significant effect on the income growth effect of high-income rural households. The "rich" gain from land circulation to a significantly greater extent than the "poor". On the one hand, the total value of agricultural output is limited, and the average income of each farmer is very small. The surplus of rural laborers can only choose to work in cities. However, farmers who originally owned land resources have expanded their production scale through land circulation. The increase in income of rural household migrant workers is smaller than that of rural households with large-scale production, which has led to a gradual widening in the income gap between rural households. On the other hand, land circulation not only causes inequality in the allocation of arable land resources, but also further contributes to the widening of the income gap among rural households through the "Matthew Effect" of the rich getting richer.

Land circulation has liberated rural surplus productivity, increased the scale of land production, and enabled many young adults to engage in non-agricultural operations, allowing effective allocation of land and human resources. Although land circulation has led to the widening of income inequality for rural households, it is unnecessary to give up land circulation. Instead, we should continue to promote land circulation and improve the land system. Based on the previous analysis and the above conclusions, this article proposes the following policy recommendations.

First, the government should further improve the land circulation market and the efficiency of land circulation, reduce the transaction cost of land circulation, and clarify land use rights. This requires establishing an information platform for the transfer market with transparent and open information to solve the problem of information asymmetry. At the same time, they should reduce the restrictions of non-market factors in land circulation so that farmers can become the real beneficiaries of land circulation.

Second, we should provide certain policy preferences to low-income farmers who do not have comparative advantages in land circulation, and we should strengthen the investment and technical training of farmers so that they can improve their competitiveness in non-agricultural employment. The overall education level of the labor force flowing into the cities and towns from rural areas is relatively low, and most of them can only perform simple labor with low wages. Therefore, the government needs to increase the technical training and improve the cultural quality of farmers. In this way, although rural households with a low-income lack the means of production, they can increase their income and stability by relying on their technology and cultural literacy to work outside the home, thereby increasing the income of the family. At the same time, the government should also improve the welfare protection measures for rural non-agricultural operations, so that lowincome farmers can engage in non-agricultural operations without worries and can further liberate productivity. For example, the government grants a quota of low-interest loans to farmers who switch from agricultural production to self-employment, and provides a series of policy supports such as tax cuts.

Third, the government should reform the household registration system and open up the social security system. A certain percentage of migrant workers cannot enjoy complete social security due to the restrictions of the household registration system. Thus, they do not dare to transfer out all of their contracted lands, instead only letting their relatives and friends cultivate or even abandon them. At the same time, household registration restrictions have resulted in farmers lacking a sense of belonging to a city, so land reform must also be coordinated with urban sector reforms. Cities and towns have further improved their medical and educational systems, allowing residents who work in said places to enjoy the same welfare protection as urban residents. In particular, the schooling problem of enrolling the children of migrant workers needs to be solved urgently, and the five social insurances and one housing fund should be fully implemented as soon as possible for migrant workers. The government should eliminate the worries that migrant workers have regarding having nowhere to stay in the city and should increase their sense of belonging to said city, so that land resources can be better allocated.

Finally, the value of total agricultural output on the technical level should be increased. Due to the scissors gap between the prices of industrial and agricultural products, the increase in grain prices lags behind the increase in the prices of agricultural materials and other industrial products, further shrinking the value of agricultural output. Therefore, the government needs to increase its support for rural production technology, the value of total agricultural output, and the capacity of the land for the strong rural labor force.

China is a largely agricultural country, and land policy involves all aspects. With the progress of urbanization and industrialization, the proportion of non-agricultural employment among farmers has gradually increased, as has the scale of land circulation. The study of rural household income inequality from the perspective of land circulation is only one aspect. After a significant increase in higher education, a new generation of farmers began to experiment with more income options. Next, we should study whether the combination of land circulation and education system affects agricultural productivity and the income gap of rural households. In addition, we can also explore the improvement of the land circulation market from the perspective of land circulation prices. Uncertainty in the boundaries of land property rights affects farmers' expectations of land use and also restricts potential land transferees; land right confirmation can eliminate this type of institutional risk. Limited by the availability and applicability of the data, this article only used the 2013 CHIP data. These data only span some provinces, so the research in

this article has certain limitations regarding depth and breadth. In future research, we will continue to focus on the inequality of rural household income, and strive to find more suitable data and methods to further improve this research.

**Author Contributions:** Conceptualization, C.H. and L.C.; methodology, C.H. and L.C.; software, C.H. and L.C.; formal analysis, C.H. and L.C.; resources, C.H. and L.C.; data curation, C.H. and L.C.; writing—original draft preparation, C.H. and L.C.; writing—review and editing, C.H., L.C.; C.H. and L.C.; supervision, C.H. and L.C..; project administration, C.H. and L.C.; funding acquisition, C.H., and L.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the youth Project of Philosophy and Social Science Foundation in Hunan Province (No.20YBQ048); Science and Technology Project of Jiangxi Provincial Department of Education (No.GJJ209923, GJJ171069).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data supporting the findings of the article is available in the 2013 China Household Income Project (CHIP). http://www.ciidbnu.org/chip/chips.asp?year=2013, accessed on 26 January 2021.

**Acknowledgments:** We would like to express our gratitude to all those who helped us during the writing of this article. Our deepest gratitude goes first and foremost to Guoan-Xiao and Muhua Liu, who are from the Hunan University of Science and Technology in China, for their constant encouragement and guidance. We also greatly appreciate James Johnston who is from the University of the West of Scotland in the UK, for his language polishing and constant encouragement.

**Conflicts of Interest:** The authors declare no conflict of interest.

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