Shiyin CHEN, Zhiyu MA

Management College of Guangdong Ocean University, Zhanjiang 524088, China

Abstract The circulation of rural land is helpful to improving the allocation efficiency of land resources, increasing farmers’ income and promoting the development of modern agriculture. In this paper, we used the social economy, the main participants and the market environment of rural land circulation to make a qualitative analysis for the factor of rural land internal circulation. With the aid of principal component analysis, grey correlation model, and other methods to make a quantitative analysis for the factor of rural land internal circulation. The results show that the grey correlation degrees of the output value of secondary and tertiary industries as a proportion of GDP, the expenditure on science and education per capita, the expenditure on financial support for agriculture, the proportion of non-agricultural population and the standardization of rural land circulation contracts are 0.898 8, 0.838 2, 0.763 2 and 0.757 6 respectively, indicating that these factors are significantly related to the rural internal land circulation market.

Key words Rural land, Internal circulation market, Influencing factors, Guangdong Province

1 Introduction

Along with the acceleration of urbanization and the large-scale transfer of rural labor force, especially in 2008 and 2009, the No.1 central agricultural document has been promoting the development of rural land circulation market as an important part of China’s agricultural and rural development, making the rural land circulation market more active. In 2014, China also promoted the reform of "three rights and separate allocation" of rural land, aiming at activating the right to operate rural land, stabilizing farmers’ contractual rights and promoting the circulation of the right to operate rural land through improving the system design. Scholars at home and abroad have made extensive researches on the causes, legal system, social security, performance evaluation, influencing factors and countermeasures of rural land circulation[1-13], while for rural internal land circulation, relevant research results are rare[14-18]. The rural land internal circulatio is the paid, orderly and reasonable transfer of land use rights among different subjects without changing the agricultural use of the land. Its purpose is to expand the scale of land management, improve the level of land benefits and fully employ laborers. At present, the degree of rural land circulation is low, and most of them are still in a state of small-scale and decentralized management. Therefore, it is undoubtedly of great social significance to systematically study various influencing factors of rural land circulation to promote the development of rural land circulation. This paper takes Guangdong Province as the research object, through the evaluation and analysis of the influencing factors of the rural land internal circulation market, and based on the qualitative analysis and quantitative research, puts forward the adjustment strategy of the agricultural internal structure, so as to provide the basis for the efficient utilization of rural land and the sustainable development of agriculture and social economy in Guangdong Province.

2 Overview of rural land internal circulation in Guangdong Province

Guangdong Province (20°09′-25°31′ N and 109°45′-117°20′ E) is located in the southernmost part of the mainland of China. The total land area of the province is about 179 700 km2, accounting for 1.87% of the total land area of China. The length of the continental coastline is about 4 114.3 km, ranking first in the country. There are 1 963 islands with a total area of 1 513.2 km2and a coastline of 2 378.1 km. Guangdong Province includes 21 prefecture-level cities (2 sub-provincial cities Guangzhou and Shenzhen), 20 county-level cities, 34 counties, 3 autonomous counties and 64 municipal districts. As of 2017, Guangdong Province has a total registered population of 93.169 million, of which 33.674 million are agricultural, accounting for 47.79% of the total population. The gross domestic product reached 8 970.523 billion yuan, up 11.20% over the previous year, and the per capita gross domestic product reached 80 932 yuan, up 9.6% over the previous year. Among them, the output value of the primary industry was 336.144 billion yuan, the output value of the secondary industry was 380.806 billion yuan, and the output value of the tertiary industry was 480.573 billion yuan, up 3.17%, 8.26%, and 14.34% respectively from the previous year. The ratio of the three industrial output values to the gross national product was 4.03∶42.37∶53.60 respectively, and the industrial structure was further optimized. In 2017, the total rural land in Guangdong Province was 14 899 300 ha, including 2 847 700 ha of cultivated land, 996 800 ha of garden land, 10 310 800 ha of forest land, 27 200 ha of grassland and 896 900 ha of other types of rural land. Construction land covers 1.776 9 million ha, including 1.445 million ha for residential areas and independent industrial and mining areas, 120 100 ha for transportation and 211 100 ha for water conservancy and hydraulic construction. Unused land is 1.305 million ha, including 702 200 ha of unused land and 602 900 ha of other lands. Per capita arable land is about 0.026 6 ha, less than 1/4 of the national average. As of December 2017, the transfer area of contracted management right of rural land in Guangdong Province was 281 300 ha (an increase of 66 600 ha compared with 2003), accounting for 14.4% of the contracted area of rural households. Among them, the spontaneous circulation area of farmers was 97 300 ha, accounting for 34.6%. The circulation area approved by the farmers and entrusted by the collective was 184 000 ha, accounting for 65.4%; land circulation involves 2.02 million households, accounting for 18.2% of contracted households. Generally speaking, the rural land circulation in the study area is characterized by the diversification of rural land circulation uses, forms and regional differences.

3 Qualitative analysis of influencing factors of rural land internal circulation

3.1 Participants

3.1.1Farmers. The farmer household is not only an economic unit but also a social unit. As economic units, they are independent business entities that are responsible for their own profits and losses, pursuing maximum economic benefits or utility and minimizing costs. As a social unit, the pursuit of maximum economic benefits is not its only goal. It also needs to consider the protection issues of survival and employment. Farmers are the main providers of rural land circulation. Their non-agricultural income and the cultural level of family members have a great influence on their willingness and behavior of land transfer.

3.1.2Rural collective economic organizations. In China, rural collective land belongs to "farmer collectives". Village collective organizations or villagers’ committees are the representatives of land ownership, the link between individual farmers and grass-roots administrative organizations, and the connection point between various rural collective situations and various national rural policies. Therefore, the attitude and behavior of village organizations have a direct impact on the transfer of rural land.

3.1.3Government organizations. Governments at all levels are providers of the rural land circulation system. The government regulates the micro-decision-making direction of various economic entities by formulating relevant laws, regulations, rules, policies and other measures,i.e. whether to transfer farmland, how much to transfer, in which way to transfer and so on. The economic behavior of Chinese farmers is mainly restricted by the system. The appropriate system leads to the rational supply behavior of farmers. The appropriate system generally has a clear property rights structure, low transaction cost and good incentive mechanism and supervision mechanism. However, the inappropriate system has vague property rights structure, high transaction cost, low incentive mechanism, and high supervision cost.

3.2 Social and economic factors

3.2.1The development of non-agricultural industries and the impact of non-agricultural population changes. According to the statistics of the research area, the gross domestic product was 18.585 billion yuan in 1978 and 8 970.523 billion yuan in 2017, an increase of 482.67 times and an annual average increase of 12.07%. Great changes have taken place in the proportion and position of the output value of the three industries in the national economy. The proportion of the secondary and tertiary industries is constantly rising, and the proportion of the primary industry is greatly reduced. With the transfer of labor force to secondary and tertiary industries, the proportion of employees in the tertiary industries has also changed accordingly. The proportion of the non-agricultural population in the total population is increasing, from 23.65% in 1990 to 69.85% in 2017. The increase of the non-agricultural population promotes the development of rural land circulation.

3.2.2The impact of agricultural comparative benefits. If the ratio of output value of rural land per hectare to output value of construction land per hectare is used to reflect the benefit difference between agriculture and non-agricultural industries, the pearl river delta region has the highest comparative benefit in the investigated research area, which is 0.024 1,i.e. the benefit of rural land is only 2.41% of that of construction land. On average, the utility of rural land is less than 2% of that of construction land.

3.3 Market factors

3.3.1Rent. In the transaction of rural land circulation, the rent is an important factor that affects the completion of the transaction. As rational people, when making decisions on land circulation, both parties to the transaction should collect and process relevant information and make judgments on future benefits and risks. Although farmers are in a weak position in the process of participating in land transfer transactions, they have the same market reaction ability as other economic entities and pursue maximum benefits. The higher the direct income from transferring land, the higher the enthusiasm of farmers to participate in the rural land circulation, and the more effective the supply quantity of rural land circulation will also increase.

3.3.2Land circulation intermediary organizations. There is a lack of intermediary organizations in the transfer of farmland. Especially in economically underdeveloped areas, due to the lack of intermediary service agencies for land transfer, the information on land transfer is not smooth, resulting in large areas of abandoned land not being contracted for development in some places, while some local contractors need farmland but cannot find available resources, accordingly affecting the rational flow and effective allocation of land resources.

3.3.3Land circulation procedures. Land circulation is a kind of economic activity, it must perform legal procedures such as signing contracts, contracts, judicial notarization,etc. in accordance with the law, and standardize the operation. Contract management is one of the conditions to ensure the smooth progress of rural land circulation. The absence of written contracts or non-standard written contracts may affect the supply or demand of land and leave hidden dangers for future disputes over land circulation. For example, if no written contract is signed but only an oral agreement is made, the binding force on both sides of the transfer is very poor, farmers have the possibility to take back the transferred land at any time, and the transfer period of rural land is very unstable, which affects the enthusiasm of land transferees and restricts the smooth transfer.

4 Quantitative analysis of influencing factors of rural land internal circulation

4.1 Principal component analysis

4.1.1Principal component analysis and evaluation indicator system. A principal component analysis is a mathematical method of multivariate analysis, it is mainly used to simplify data structure, find comprehensive factors and sort samples. In the analysis of influencing factors of land transfer, there are many indicators affecting the transfer of rural land, and there are varying degrees of correlation between the indicators, which makes the supplied information overlap and overlap, bringing difficulties to the analysis. Principal component analysis just provides us with the possibility of analysis. It transforms the original multiple indicators with certain mutual relations into a few independent comprehensive indicators, thus it can more clearly reflect the internal laws of the analyzed things through the analysis of a few comprehensive indicators. Based on the qualitative analysis of the above factors affecting the transfer of farmland use rights and referring to the literature on land transfer research, 13 factors (Table 1) of 3 categories that have direct or indirect effects on the transfer of farmland are selected, and the principal components are extracted from the cross-sectional data of counties (districts and cities) surveyed in 2017. Among them, it is difficult to quantify the impact of government and rural collective economic organizations on rural land circulation behavior. Therefore, this paper did not include it into the quantitative study of influencing factors. Specific indicators and their data sources are as follows:

Table 1 Indicator system of rural land internal circulation market

FactorIndicatorEconomic factorsPer capita GDP, ratio of secondary and tertiary industry output to GDP, ratio of agricultural output, di-rect cost index of rural land circulation, and comparative benefits of rural landSocial factorsProportion of employees in secondary and tertiary industries, per capita expenditure on science and educa-tion, Engels coefficient in rural areas, normative quality of land transfer contract management, and pro-portion of fiscal expenditure on agricultureProduction factorsAverage area of arable land per worker, the average household expenditure on production costs, and the proportion of cash crop area to the total area of farmland

4.1.2Standardization of indicators. Usually, some economic indicators have different dimensions, and some indicators have great differences in magnitude. When applying principal component analysis, different dimensions and magnitudes will lead to new problems. Therefore, in order to eliminate some unreasonable influences that may be caused by dimensional differences, the data need to be standardized.

(1)

4.1.3General mathematical model of principal component analysis. According to the selected index and the determined main component influencing factors, the unit feature vectors μi are respectively obtained by adopting the comprehensive index method, and then the factors x affecting the land circulation of farmers are found out. letX=(x1,x2, …,xp), the covariance matrixσ>0,λ1≥λ2≥λ3≥λp>0,λIis the non-zero feature root ofσ,μiis the unit feature vector corresponding toλi, then the main component is

yi=μiX,i=1, 2, …,P

(2)

whereyirepresents a comprehensive index extracted through principal component analysis,i.e.yiis taken as the principal component ofx,x1,x2, …, andxp, which are the factors that affect farmers’ land circulation respectively.

4.1.4Results analysis. Using SPSS statistical software and principal component extraction (PCA), generally speaking, the cumulative contribution rate of the extracted principal component is more than 80%-85% and the result is satisfactory, so how many principal components need to be extracted can be determined accordingly. Based on the results of qualitative analysis and the basis of principal component extraction with a cumulative contribution rate greater than 90%, this paper carries out principal component extraction and analysis of various influencing factor indexes of rural land circulation.

Table 2 mainly reflects the total variance decomposition in the process of principal component analysis, from which it can be seen that the first four factors provide 94.965% of the information of the original data in the indicator analysis of influencing factors of rural land circulation, and most of the data have been fully summarized and the information contained in the original data has been better explained. Therefore, by selecting these four common factors, there is basically no loss to the total amount of information. In the initial factor load matrix, the different distribution of the load value of each common factor on each index variable is not obvious, and the typical representative variable of the initial factor is not prominent. In this paper, orthogonal rotation is used to rotate the factor load matrix, and each variable with similar factor load is placed under a common factor, so as to make a more reasonable explanation of the meaning of the factor, and obtain the factor load matrix Table 3 after orthogonal rotation.In the above quantitative analysis, the factors that have a greater impact on rural land circulation are put forward: the proportion of output value of secondary and tertiary industries to GDP, the proportion of non-agricultural population, per capita expenditure on science and education and government support management,etc., but the extent of impact of these main factors on rural land circulation is not revealed. Therefore, the following grey correlation quantitative analysis method is used to study the influence degree of the main factors.

Table 2 Flow factors affecting the characteristics of the common factor value and contribution

Common factorInitial eigenvalueEigenvalueVariance analysisrate∥%Cumulative resolutionrate∥%Sum of squares of extraction factorsEigenvalueVariance analysisrate∥%Cumulative resolutionrate∥%16.26948.21948.2196.26948.21948.21923.53727.21075.4303.53727.21075.43031.61412.41887.8471.61412.41887.84740.9257.11794.9650.9257.11794.96550.6555.035100.0063.820E-162.938E-15100.0072.468E-161.898E-15100.0082.028E-161.560E-15100.0091.661E-161.278E-15100.00102.467E-171.898E-16100.0011-1.915E-16-1.473E-15100.0012-3.039E-16-2.337E-15100.0013-1.270E-15-9.769E-15100.00

Note: The first four principal components were extracted based on the cumulative contribution rate >90%.

Table 3 Rotation factor loading matrix

IndicatorCommon factor (principal component)1234Ratio of output value to output value0.984-0.076-0.0440.110Percentage of employees0.2450.8840.3390.168Per capita GDP0.8890.3380.3060.052Engel coefficient-0.129-0.808-0.414-0.015Per capita expenditure on science and education0.4470.3430.929-0.191Average arable land per worker0.174-0.840-0.1160.105Household production expenses0.0850.7070.378-0.099Proportion of agricultural output val-ue-0.9070.2760.101-0.220Agricultural benefits-0.2760.5700.7650.121Circulation cost index0.4610.1900.8230.215Norm Index of Circulation Contract-0.0220.1270.3760.915Proportion of cash crop area to total farmland area0.7140.6870.028-0.071Proportion of fiscal expenditure on agriculture0.309-0.135-0.3370.854

Note: The value of factor load reflects the relative importance of theivariable to thejcommon factor,i.e. the closeness between each variable and the common factor.

4.2 Grey correlation analysis

4.2.1Grey correlation evaluation indicator system. In the analysis of the market factors of the internal circulation of rural land, the grey relational analysis method is used to select four main influencing factors. From Table 4, it can be seen that the influence degree of each influencing factor on the circulation of rural land is different.

4.2.2Standardization of evaluation indicators. The indicator quantity reflecting the scale of land circulation is defined as the characteristic variable (parent factor) of the system, denoted byy: (i=1,2,3, …,m),mdenotes the number of characteristic variables, various influencing factors are defined as relevant variables (sub-factors), denoted byxj(j=1,2, …,n), and n denotes the number of relevant variables. The grey correlation analysis method is to establish grey correlation matrix by calculating the correlation degree between characteristic variables and related variables of the system and obtain the primary and secondary relationships among various influencing factors. The calculation formula[13]of the correlation coefficient is:

(3)

whereξi(k) is the grey correlation coefficient ofxitoyiatk,ξis resolution coefficient, generally, the value is in the range of 0-1, and 0.5 is taken in this article.

4.2.3Evaluation model of correlation analysis. Multiple correlation coefficients are calculated through multiple samples, and the information is too scattered. In order to facilitate comparison, the method of finding a flat value is often used to process this information, that is, the correlation coefficient at each moment is converted into a value, called the correlation degree of the correlation factor, so that the correlation degree of each correlation factor can be compared and analyzed.

The general expression of correlation degree is[14]:

(4)

Because the data units of various variables are not consistent, even if some index units are the same, their actual meanings may be different. Therefore, the sample data sequence needs to be nondimensionalized. For each indicatorx, according to the formula:

x＇j=xj/x0(whenxjis a positive effect index)

(5)

x＇j=x0/xj(whenxjis a negative effect index)

(6)

wherex＇jis the dimensionless value of indexj,xjis the original value of indexj, andx0is the maximum value of indexj. Using the above formulas (3) and (4) to calculate the correlation degree of influencing factors of land circulation, the correlation matrix table (4) is obtained.

Table 4 Grey value

Grey valueProportion of value of secondaryand tertiary industriesProportion of non-agricultural populationPer capita expenditure onscience and educationFinancial expenditure onsupporting agricultureContractstandardizationGrey correlation coefficient (ζij)0.971 40.719 70.949 70.820 30.864 00.883 90.760 40.821 40.960 00.738 00.801 60.694 80.664 50.560 80.596 40.938 60.855 50.917 40.791 20.775 0∑ζij3.595 53.030 43.353 03.132 32.973 4Grey correlation degree (rij)0.898 80.757 60.838 20.783 00.743 3

Note: According to the magnitude ofRvalue, the correlation order is arranged according to the degree of closeness with farmland circulation:r1>r3>r4>r2>r5.

4.2.4Results. Grey relational analysis results show that the five main influencing factors have different degrees of influence on rural land circulation. The correlation coefficient between the ratio of an output value of secondary and tertiary industries to GDP and rural land circulation is the largest, reaching 0.837 0,i.e. the ratio of the output value of secondary and tertiary industries to GDP changes by one unit and the scale of rural land circulation changes by 0.837 0 units. This shows that the development of secondary and tertiary industries has a great influence on rural land circulation. The rapid development of secondary and tertiary industries is the basis for absorbing a large amount of surplus rural labor force and increasing the proportion of the non-agricultural population, as well as increasing financial support for agriculture.

5 Conclusions and discussions

In this paper, four main components are extracted through principal component analysis, and the order of the main influencing factors on the degree of rural land circulation is as follows: the proportion of output value of secondary and tertiary industries to GDP, the expenditure on science and education per capita, the proportion of financial expenditure on agriculture, the proportion of non-agricultural population and the standardization of rural land circulation contracts. The grey correlation degrees are 0.898 8, 0.838 2, 0.783 0, 0.757 6 and 0.743 3 respectively. Farmers are the main providers in the transfer of rural land-use rights. Their economic behavior and willingness are dominated by their economic rationality or the rationalization of family resource allocation. Pursuing utility or maximizing benefits is the internal economic power of the transfer of rural land, but it is also affected by other influencing factors. Therefore, the following countermeasures are specifically put forward.

(i) Vigorously developing non-agricultural industries and providing more and better employment opportunities for farmers. First of all, it is recommended to encourage the development of agricultural products processing enterprises, give full play to China’s abundant labor resources, vigorously develop fruit juice, jam, canned and other labor-intensive products, and vigorously develop the tertiary industry to provide more employment opportunities for the transfer of rural labor force. Secondly, develop small towns and promote the transfer of rural labor force. As a commodity distribution center and an economic center within a small rural area, the industrial structure of small towns is generally still dominated by labor-intensive industries, commerce and services due to the restrictions of economic basic conditions. The quality requirements for employees are generally not high and they are easily qualified by the rural labor force. At the same time, the construction of small towns can promote the integration of rural trade, industry and agriculture, break the dual structure of urban and rural areas and absorb more agricultural labor.

(ii) Improving the education level of the rural labor force. This can not only increase the human capital of the rural labor force and make it more competitive in the labor market, so as to increase the expected income of the transferred labor force in the city, but also enhance the ability of the untransferred labor force to obtain urban employment information and reduce the psychological cost of the transfer of the rural labor force.

(iii) Strengthening the support of the government and relevant departments. The transfer of rural land involves the coordination of the relations among farmers, owners and the government. Party and government departments at all levels and relevant departments should provide strong backing for the transfer of land, formulate feasible preferential policies, intensify the supporting construction of agricultural infrastructure, provide a good investment environment for the development of owners, such as transportation, communication, water conservancy, power grid, social security,etc., and provide support in terms of credit, technology, information, taxation,etc.; increase investment in agricultural science and technology to accelerate the promotion and application of new varieties and technologies. Governments at all levels should ensure the timely arrival of various funds for supporting agriculture in accordance with relevant policies. In particular, they should ensure the input of funds for scientific research related to agriculture, strengthen support for agro-industries, enable agricultural scientific research institutions to continuously research and develop various advanced and applicable agricultural production technologies, and establish and perfect the agricultural input mechanism.

(iv) Establishing a stable rural social security system and weakening the social security function of the land. One of the criteria for the mobility of rural land is whether the nature of land security has been weakened. If farmers have other social security methods independent of land and have more social employment channels, the conditions and timing for large-scale land mobility are ripe. The social security function of land to farmers is mainly manifested in the following aspects: First, the life security function. Land provides farmers with a guarantee of a basic livelihood. The land is the most basic means of agricultural production. People work on the land to produce food and other means of livelihood necessary for life. The second is the employment function. Most farmers take the land as their object of work, and land provides them with employment opportunities and workplaces. Third, the descendants of farmers have the right to inherit the land.

(v) Increasing investment in rural human capital and improving the quality of the rural labor force. Human capital refers to the knowledge, skills and capabilities condensed on laborers. Agricultural science and technology and farmer education are two major aspects of rural human capital investment, and human capital theory is the key to transform traditional agriculture.

(vi) Establishing the market organization of rural land circulation and standardizing the management of rural land circulation. According to the on-the-spot investigation of rural land circulation, the factors affecting the internal transfer of rural land are not only the wishes of the transfer subjects (suppliers and demanders), but also some problems that cannot be ignored, such as irregular procedures of rural land circulation, frequent land disputes, damage to the interests of both sides of the transfer, and are not conducive to the reasonable transfer of rural land.