The Impact of Digital Finance on Rural Land Transfer: Dynamic Spillover Effects and Mechanism Examination

The Impact of Digital Finance on Rural Land Transfer: Dynamic Spillover Effects and Mechanism Examination | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of Digital Finance on Rural Land Transfer: Dynamic Spillover Effects and Mechanism Examination Tao Chen, Lun Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6736992/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Digital inclusive finance provides financial capital and digital services for agricultural production, which has the necessary conditions to promote rural land transfer and improve the rural factor market. This paper constructs a theoretical analytical framework for the impact of digital financial inclusion on rural land transfer from both direct and indirect roles; adopts the dynamic spatial Durbin model to empirically test the hypothesized spillover effect and impact mechanism. The results indicate that: (1) digital inclusive finance facilitates rural land transfer and generates long-term spillover effects; (2)the mediating effects of agricultural infrastructure, rural labor force, and agricultural mechanization in the process of digital financial inclusion affecting rural land transfer are significant and decreasing in order; (3)the differences in the agricultural industrial base and geographic endowment in central and western China are the main factors that cause regional heterogeneity. Finally, we propose three suggestions to promote the moderate-scale operation of agriculture by expanding the coverage and service depth of digital inclusive finance, promoting the double aggregation of rural population and industry, and making up for the short boards of agricultural production in the western region. Digital financial inclusion land transfer dynamic spatial Durbin model impact mechanisms 1. Introduction Land is the basic means of agricultural production and a key factor in agricultural modernization. Since the implementation of the rural household contract responsibility system, the long-term decentralized and fragmented agricultural production and management mode has restricted the process of agricultural modernization in China. Promoting rural land transfer is the inevitable way to achieve moderate scale agricultural management. It produces two effects of marginal output leveling and transaction income, that is, improving the efficiency of resource allocation and the enthusiasm of farmers for land investment, which is conducive to the increase of farmers' income, agricultural efficiency and rural industry development [ 1 ]. Since the promulgation of the Measures for the Management of the Transfer of Contracted Rural Land Management Rights in 2005, the transfer area of contracted rural land in China has increased from 54 million mu to 530 million mu in 2020. The land transfer policy has realized effective radiation and diffusion at the geographical and spatial level. However, due to the flow and allocation of land elements, the objects and interests involved are complicated. The imperfect and unsound land transfer market has greatly constrained the expansion of scale operation of rural households. In the context of the current rapid development of digital economy, the connection between digital elements and agricultural development is continuously strengthened. Digital inclusive finance can not only effectively address farmers' financing difficulties and high financing costs, provide financial channels and credit guarantee for farmers' land transfer, but also reduce transaction costs by promoting the development of digital agriculture [ 2 ]. To a certain extent, the information asymmetry of the agricultural land transfer market has been alleviated, thus accelerating the pace of rural land transfer and promoting the process of agricultural modernization[ 3 ]. The 2024 Central Committee’s No. 1 Document positions "developing rural digital inclusive finance" as an important channel to improve the diversified investment mechanism of rural revitalization, and point out that the primary measure of the next stage of rural reform and innovation is "improve the formation mechanism of land transfer price". How to realize the supporting role of digital inclusive finance in promoting rural land transfer in rural reform and innovation has become an important issue in the field of "agriculture, rural areas" at present. At this stage, rural land transfer is restricted by many factors. First, agricultural funds are restricted. Land rent accounts for a large proportion of agricultural funds in agricultural production and operation, and agricultural funds are mainly derived from agricultural production and operation. The second constraint is land fragmentation, which is not conducive to mechanized operations and difficult to improve agricultural production efficiency [ 4 ]. Moreover, due to the scarcity of agricultural labor force, large-scale agricultural production cannot be satisfied. When large agricultural households expand the scale of production and operation, they will face problems such as increased production cost and reduced ability to prevent natural risks, thus impeding land transfer[ 5 ]. The third is the restriction of the transaction market. Under the conditions of the traditional rural land transfer market, a series of costs such as information collection, negotiation and decision-making, supervision and performance of the contract generated in the process of land transfer are not conducive to land transfer. Some scholars proposed to establish a land intermediary trading platform to reduce land transaction costs, and the main body responsible for the construction of land transaction platform can be composed of local governments and agricultural enterprises[ 6 ]. In addition, some scholars analyzed the influencing factors of farmers' willingness to transfer land from the micro level. In the process of urbanization, rural labor force is separated from traditional agriculture and engaged in non-agricultural labor to obtain wage income, which has a positive effect on farmers' willingness to transfer land. Moreover, as farmers' dependence on land decreases, the willingness to transfer farmland is further promoted [ 7 ]. Non-agricultural employed farmers and large agricultural households have differentiated land use modes, and have strong willingness to transfer and transfer land transfer respectively[ 8 ]. On the other hand, due to the substitution of rural labor force by agricultural machinery, the restriction of the reduction of rural labor force on agricultural production and management has been overcome. At the same time, the development of agricultural mechanization has a positive effect on optimizing the input of agricultural production factors, reducing agricultural production costs, and increasing the willingness of large agricultural households to expand production and obtain economies of scale. The above constraints on rural land transfer can be summarized as: a single source of agricultural funds, land dispersion is not conducive to scale management, the impact of unsound land trading market on farmers' land transfer ability, as well as rural labor force and agricultural mechanization the impact on farmers' land transfer willingness. Digital inclusive finance can directly or indirectly have a positive effect on rural land transfer. On the one hand, digital inclusive finance can effectively alleviate the lack of rural financial resources, improve the rural credit evaluation system through digital technology[ 9 ], reduce transaction costs and other ways to lower the threshold for farmers to obtain financial support to help farmers get rid of the restrictions of "acquaintance society" and traditional financial institutions on raising funds for land transfer [ 10 , 11 ]. On the other hand, digital inclusive finance regulates the financing process and scope of use of agricultural production organizations. It is conducive to the establishment of a risk prevention mechanism for agricultural production organizations through digital technology [ 12 ], and the structural mismatch between the extensive credit demand and financial supply in the agricultural machinery operation service market can also be eliminated under the role of digital inclusive finance[ 13 ]. Provide convenience for agricultural production [ 14 ]. In addition, at the micro level, digital financial inclusion can stimulate farmers' entrepreneurial willingness by improving their financial literacy and sharing entrepreneurial risks and sharing entrepreneurial risks (He Guangwen et al., 2019) [ 15 , 16 ]. Moreover, the information platform provided for entrepreneurs is conducive to enriching the social network of entrepreneurs and making up for the disadvantage of poor information[ 17 ]. At the same time, the improvement of entrepreneurial environment and the adjustment of local industrial structure of digital inclusive finance are conducive to the activity of rural entrepreneurship[ 18 ]. Its supporting effect on county economy is conducive to regional industrial development and guarantees financing channels for entrepreneurs and small and micro enterprises. It provides more employment opportunities for rural labor force and also provides a stable employment environment for the return of labor force[ 19 ]. To sum up, the digital technological advantages of the digital inclusive finance institute can effectively improve the breadth and depth of financial coverage in rural areas, and directly affect micro-entities such as farmers and agricultural enterprises to improve their financial availability. It promotes rural population transfer, agricultural mechanization and farmers' entrepreneurial behavior, and indirectly creates favorable conditions for rural land transfer. It can be seen that digital inclusive finance is a key factor to promote rural land transfer. Only studies on the mechanism of digital inclusive finance affecting rural land transfer are mainly discussed from the micro perspective of financial services and financial literacy, focusing on the direct impact of digital inclusive finance on rural land transfer, and lack of mechanism analysis based on the macro level. This paper intends to sort out the logical route of digital inclusive finance's impact on agricultural production factors and thus on rural land transfer, re-examine the main influencing factors of rural land transfer based on the macro level, and conduct an empirical study on the direct, indirect and spatial spillover effects of digital inclusive finance's promotion of rural land transfer. Finally, Put forward important measures to promote rural land transfer and countermeasures and suggestions to play the supporting role of digital inclusive finance. The marginal contribution and innovation of this paper have two aspects: First, build a theoretical framework of digital inclusive finance's impact on rural land transfer, discuss its direct role, spatial spillover effect and intermediary mechanism, highlight the direct and indirect action mechanism of digital inclusive finance in promoting rural land transfer, so as to better understand the supporting potential of digital inclusive finance in promoting rural land transfer. To provide new ideas for improving the rural land transfer factor market; Second, this paper retested the influencing factors of rural land transfer from a macro perspective, supplemented the limitations of existing studies in the research perspective, adopted instrumental variable method and dynamic spatial Durbin model to control the endogeneity of the model, conducted robustness test and heterogeneity test, and finally combined causality analysis and stepwise regression to verify the assumed intermediary mechanism. To ensure the reliability of the empirical results, and provide a factual basis for further exploring the important role of digital inclusive finance in rural reform and innovation. 2. Theoretical analysis and research hypothesis 2.1. The direct impact of digital inclusive finance on rural land transfer In the process of rural land transfer, while digital inclusive finance provides financial support for land transferers, the development of digital trading platforms reduces the transaction costs of land transfer[ 20 ]. Based on the analysis of farmers' intention and ability of land transfer, digital inclusive finance establishes a farmer's credit evaluation system and lowers the threshold for farmers and agricultural production organizations to obtain financial capital. With the advantage of digital technology, it improves the scope of financial services and provides a new way for the information collection channel of land transfer market, making it more convenient for land transferers to obtain agricultural funds and land transaction information, thus enhancing their willingness to transfer to land. For land transferers, the financial information and services provided by digital inclusive finance improve farmers' financial literacy and make them more willing to transfer part of their land, engage in non-agriculture, and obtain property income and wage income. In terms of enhancing the ability of rural land transfer, digital inclusive finance provides financial support for farmers, so that the land transfer party has sufficient agricultural funds to expand the planting area, and rural land is guaranteed by the financial guarantee of digital inclusive finance The enhanced transaction capacity of land transfer market is of great significance for promoting the appropriate scale operation of agriculture and supporting the development of rural industries[ 21 , 22 ]. In general, digital inclusive finance has played a positive role in promoting rural land transfer. Hypothesis 1 Digital inclusive finance has a positive impact on rural land transfer. China's digital inclusive finance has typical convergence characteristics and positive agglomeration spatial effect, which indirectly produces spillover effects on other related provinces mainly through facilitating mobile payment, expanding credit and improving insurance and other ways[ 23 , 24 ]. The spillover effect is mainly manifested in three aspects: First, the diffusion effect. Compared with the traditional financial model, digital inclusive finance has obvious technical advantages, and digital information technology can cover rural areas faster, more extensively and more accurately. On the one hand, digital inclusive finance spreads from the urban center to the surrounding towns and villages, driving the development of local rural areas. It spreads from areas with economic development advantages to backward areas and drives the economic development of surrounding regions. The second is the agglomeration effect. Digital inclusive finance can promote the agglomeration effect of agricultural industry through financial support, technical support and talent support [ 25 ]. Digital inclusive finance first takes effect in economically developed areas, promoting non-agricultural employment of the local rural population and promoting the agglomeration effect of large-scale agricultural operation, which is conducive to the upgrading of rural industries and the incubation of new industries. Third, mutual feed effect [ 26 ]. Digital inclusive finance improves the financial literacy of rural residents, and various regions and departments can exchange and learn from each other through digital platforms in a timely manner to absorb advanced development experience, thus realizing knowledge sharing and coordinated development. Hypothesis 2 Digital financial inclusion has a spatial spillover effect. 2.2. Indirect effects of digital inclusive finance on rural land transfer 2.2.1. The intermediary effect of rural labor force Rural land transfer is affected by the employment structure and age structure of rural labor force. The employment modes of rural labor force in China can be divided into pure agriculture, part-time employment and non-agriculture. Farmers who are fully engaged in agricultural production have a strong demand for land transfer and hope to acquire more land to produce scale effect. The attitude of part-time farmers towards land transfer depends on the local employment environment. In a good employment environment, part-time farmers tend to engage in non-agriculture and transfer most of their land out. Those who are fully engaged in non-agricultural farming do not want their land to be abandoned, but are more willing to transfer their land and get land rent. In terms of age structure, the young and middle-aged rural labor force mainly obtains income through non-agriculture, while the old farmers have no desire to expand their business by transferring to land due to labor force limitation. Digital inclusive finance has an impact on the employment mode of rural labor[ 27 ]. On the one hand, financial support for large agricultural households enhances their willingness and ability to transfer land, and at the same time, it creates a better employment environment for part-time farmers and enhances their willingness to transfer land. On the other hand, the financial products and pension insurance provided by digital inclusive finance can provide more choices for the old-age lifestyle of the rural elderly labor force, so that some elderly farmers can completely give up or reduce agricultural activities and transfer the remaining land. In addition, digital inclusive finance supports the development of rural industries, promotes the upgrading of rural industrial structure, generates more rural employment opportunities, and thus attracts the return of rural labor force [ 28 ]. However, this part of the returned rural labor force is accustomed to non-agricultural production and continues to choose rural nonagricultural employment in rural areas. However, it has no significant impact on land circulation. In short, digital inclusive finance is conducive to non-agricultural employment of rural labor force and indirectly promotes rural land transfer, while digital inclusive finance is conducive to the return of rural labor force, which is shown in the following aspects in terms of the number of rural labor force: Digital inclusive finance promotes the increase of the total rural labor force and promotes non-agricultural employment of rural households, thus playing a positive role in rural land transfer[ 29 ]. Hypothesis 3 The rural labor force plays an intermediary role in the process of digital inclusive finance affecting land transfer. 2.2.2. The intermediary effect of agricultural mechanization Rural land transfer is closely related to the transformation of agricultural production mode. Traditional agriculture mainly relies on agricultural population, and if the expansion of agricultural operation scale requires more agricultural labor force, there are defects in factor allocation, supervision and prevention of natural risks, and the production efficiency is low. Agricultural mechanization makes up for the deficiency of traditional agriculture in terms of production efficiency, and the allocation of production factors is more reasonable, the timeliness of agricultural production is stronger, and natural risks can be effectively avoided, which makes large agricultural households more willing to expand production and obtain economies of scale. The replacement of labor force by mechanical action promotes the transfer of part of rural labor force to non-agricultural sectors, thus generating surplus land for large agricultural households to expand production scale. Agricultural mechanization enhances the land transfer willingness of both the land transfer party and the land transfer party. The impact of digital inclusive finance on agricultural mechanization is mainly in the two aspects of agricultural machinery holdings and agricultural machinery services. For large agricultural households, The purchase of agricultural machinery is conducive to improving production efficiency, and the financial support provided by digital inclusive finance improves the ability of farmers to purchase agricultural machinery; Some farmers choose agricultural machinery services out of consideration of economic applicability. Digital inclusive finance plays a role in providing financial and technical support to local agricultural machinery enterprises, which promotes the agricultural machinery service market to serve farmers efficiently [ 30 ]. Digital inclusive finance promoted agricultural mechanization and indirectly promoted rural land transfer[ 31 ]. Hypothesis 4 Agricultural mechanization plays an intermediary role in the process of digital inclusive finance affecting land transfer. 2.2.3. The mediating effect of agricultural infrastructure For a long time, land fragmentation is the main factor restricting the transfer of rural land. In agricultural large-scale production, land fragmentation causes obstacles to all aspects of production, such as land ploughing, planting, management and protection, and harvest. Agricultural infrastructure includes water conservancy facilities, transportation facilities and other aspects[ 32 ]. While agricultural water conservancy facilities facilitate agricultural water conservancy irrigation, land fragmentation is somewhat alleviated. On the one hand, agricultural infrastructure promotes land agglomeration, which is conducive to large-scale production after land transfer; on the other hand, agricultural infrastructure facilitates agricultural production, reduces part of the production cost of large agricultural households in the process of production and management, and enhances farmers' willingness to transfer to land[ 33 ]. Funds for agricultural infrastructure construction are mainly subsidized by the government or self-raised by rural collective economic organizations[ 34 ]. China's agricultural infrastructure investment and financing has long been restricted by insufficient credit investment and immature financial system[ 35 ]. By improving the medium and long-term credit mechanism of policy-based financial institutions and commercial financial institutions for rural infrastructure construction projects, giving full play to the digital advantages of digital inclusive finance, innovating medium and long-term credit products and models, and improving the supervision, assessment and evaluation mechanism of financial business, It is conducive to expanding effective investment in agriculture and rural areas, promoting the construction of agricultural infrastructure, and indirectly promoting the transfer of rural land[ 36 , 37 ]. Hypothesis 5. Agricultural infrastructure plays an intermediary role in the process of digital inclusive finance affecting land transfer. 3. Research and design 3.1. Model setting In order to verify the above analysis, considering the spatial spillover or time lag of the influence of various influencing factors on rural land transfer, this paper constructs a dynamic spatial Durbin model to test the research hypothesis [ 38 ]. The Spatial Durbin model : $${Y_{i,t}}=\lambda +\sum\limits_{k} {{\alpha _k}{X_{i,t}}+\varphi W{Y_{i,t}}+\eta L \cdot } W{Y_{i,t}}+\sum\limits_{k} {{\beta _k}} W{X_{i,t}}+{\sigma _{i,t}}$$ 1 In this paper, panel model (mixed effect, random effect, fixed effect), spatial Durbin model and dynamic spatial Durbin model were used to empirically test the influencing factors of rural land transfer. When φ, η and β in Eq. ( 1 ) are all 0, it is the basic panel model; When η is 0, formula (1) represents the static space Durbin model; When none of the coefficients is 0, formula (1) represents the dynamic spatial Durbin model. (1) In the formula \(\:{Y}_{i,t}\) is the explained variable, \(\:{X}_{i,t}\) is the explanatory variable, W is the geographical weight matrix, \(\:\lambda\:\) is the constant term, α k is the regression coefficient of each explanatory variable, which directly reflects the influence degree of the explanatory variable on the explained variable; \(\:{\beta\:}_{k}\) is the regression coefficient of the interaction term between the weight matrix and the explanatory variable, indicating the spillover effect of the explanatory variable on the explained variable in the surrounding area; φ is the regression coefficient of the interaction term between the weight matrix and the explained variable; η is the time delay term of the interaction term between the weight matrix and the explained variable, \(\:{\sigma\:}_{i,t}\) is the random disturbance term. In order to further analyze the mechanism of digital inclusive finance affecting rural land transfer, this paper mainly examines the intermediary effects of rural labor force, agricultural mechanization and agricultural infrastructure. In order to solve the deficiencies of causality tests in the process of step-to-step testing of intermediary effects, the author first based on the correlation evidence of causality demonstration in existing literature[39]. Then, through the stepwise method test, the intermediary effect of the above analysis is tested twice, in order to improve the credibility of the empirical process. In this paper, the spatial Durbin model is used to estimate the mediating effects. Mediation Effects model : $${Y_{i,t}}={\theta _1}+c\ln dig+\sum\limits_{k} {{\rho _k}Contro{l_{i,t}}+{\sigma _{i,t}}}$$ 2 $${M_{i,t}}={\theta _2}+\alpha \ln di{g_{i,t}}+\sum\limits_{k} {{\rho _k}Contro{l_{i,t}}+{\sigma _{i,t}}}$$ 3 According to the previous analysis, it is necessary to examine the three intermediary paths in the process of digital inclusive finance affecting rural land transfer in turn. (2) To test the direct impact of digital inclusive finance on rural land transfer, \(\:{Y}_{i,t}\) is rural land transfer, \(\:{X}_{i,t\:}\) is digital inclusive finance, \(\:{Control}_{i,t}\:\) is the control variable, \(\:{\rho\:}_{k}\) coefficient of each control variable, ɵ is the constant term, c is the coefficient of direct effect, \(\:{\sigma\:}_{i,t}\) is the random disturbance term; (3) Formula tests the influence of digital inclusive finance on the intermediary variables, where \(\:{M}_{i,t}\) and tare the intermediary variables, namely rural labor force, agricultural mechanization and agricultural facilities, and a is the influence coefficient of digital inclusive finance on the intermediary variables; (4) Formula is the comprehensive impact of digital inclusive finance and intermediary variables on rural land transfer, c is the direct impact coefficient of digital inclusive finance on rural land transfer after controlling intermediary variables, and b is the impact coefficient of intermediary variables on rural land transfer. In this paper, the intermediation effect was tested using the intermediation test process defined by Baron and Kenny, and the pre-processing Variable was added to the model: The rural fixed asset investment and traffic level were taken as control variables to optimize the possible endogeneity problem in the model to a certain extent. The mediation effect size was measured by c-c‘. 3.2. Variable description This paper aims to study the internal mechanism of digital inclusive finance affecting rural land transfer. The explained variable is rural land transfer, measured by the total area of household contracted arable land transfer, the core explanatory variable is digital inclusive finance, measured by digital inclusive finance index, and the intermediary variables are rural labor force, agricultural mechanization, and agricultural facilities, respectively. The control variables are fixed asset investment, pension insurance and transportation level of rural households. In order to eliminate possible endogenous problems in the model, financial digitalization is selected as the instrumental variable. Logarithmic processing was carried out for each indicator, and the processing process of the indicator was shown in Table 1 . Table 1 Variable selection and index processing. Variables Symbols Indicator processing Depenent variable Land flow lnflc ln Total area of Cultivated land under household contract (mu) Mediating variables Rural labor lnfrl Number of rural employed in ln (10,000) Agricultural mechanization lnfam Total power of ln agricultural machinery (thousand kilowatts) Agricultural facilities lnfaf Effective irrigated area in ln (thousand hectares) Independent variable Digital finance lndig ln Digital Financial Inclusion Index Control variable Endowment insurance lnfei ln Number of urban and rural residents enrolled in social pension insurance (10,000) Investment in fixed assets of agricultural households lnfha ln Rural Household Fixed Asset Investment Completion (billions of dollars) Transportation levels lntla Total length of ln postal routes (km) Instrumental variable Digitization of finance lndis Ln Financial Inclusion Digitalisation Index Table 2 Descriptive statistics result. Variable Symbols Obs Mean Std.Dev Min Max Land transfer lnflc 310 6.715 1.177 2.801 8.839 Digital finance lndig 310 5.213 0.674 2.909 6.068 Rural labor lnfrl 310 4.655 1.316 1.375 7.419 Mechanization of agriculture lnfam 310 7.637 1.125 4.543 9.499 Investment in fixed assets of agricultural households lnfha 310 5.352 1.118 1.099 6.874 Farm facilities lnfaf 310 7.227 1.073 4.694 8.729 Pension insurance lnfei 310 6.905 1.126 4.329 8.567 Transportation levels lntla 310 10.819 1.084 6.983 12.275 Digitization of finance lndis 310 4.483 1.102 2.026 6.136 4. Analysis of empirical results 4.1. basic regression analysis Based on the basic panel model of formula (1), basic regression analysis was conducted to empirically test the main influencing factors of rural land transfer from the macro level. The data used for each variable passed the LLC test and IPS test, showing stable panel data. The regression results are shown in Table 3 . Hausman test confirmed the selection of fixed effect model for estimation, and the result (1) is the estimation result of individual fixed effect. The results show that: digital inclusive finance and rural labor have a significant positive effect on rural land transfer; Rural households' investment in fixed assets has a significant negative impact on rural land transfer. The results of basic regression are basically consistent with theoretical analysis: the development of digital inclusive finance, rural labor force and agricultural infrastructure in China is conducive to rural land transfer, among which digital inclusive finance and agricultural infrastructure have positive effects on farmers' land transfer ability and transfer intention, while rural labor force and agricultural mechanization mainly affect farmers' land transfer intention. Fixed asset investment of rural households consumes agricultural funds to a certain extent, and does not have a positive effect on the intention of land transfer of rural households, which is manifested as restriction of land transfer.4.1.1. Endogeneity test For further analysis, in order to better identify the relationship between digital inclusive finance and rural land transfer and eliminate possible endogeneity problems, this paper further constructed instrumental variables to re-estimate the model. In relevant studies, many scholars used Internet penetration rate as the instrumental variable of digital inclusive finance[ 40 ]. Some scholars also constructed "digital technology application index" as an instrumental variable of digital inclusive finance [ 41 ]. In this paper, "Digitalization degree" published in 2011–2020 Peking University Digital Financial Inclusion Index (PKU-DFIIC) is selected to represent the level of financial digitalization as an instrumental variable of digital financial inclusion. This index is measured by the four dimensions of mobility, affordability, credit and facilitation [ 42 ]. On the one hand, the development of digital inclusive finance benefits from the extensive penetration of digital information technology, while the level of financial digitalization reflects the public's application level of digital technology and the diffusion and popularity of information technology among residents. Therefore, there is a close relationship between the two; On the other hand, after controlling a series of relevant variables, there is no direct correlation channel between the level of financial digitalization and rural land transfer. Therefore, it is valid to select the level of financial digitalization as an instrumental variable in this paper. Result (2) is the estimation result of 2SLS after adding the instrumental variables, and the positive and negative and significance of the estimation results of each variable are basically consistent with that of result (1). Meanwhile, the Hausman test shows that the original model has no endogeneity problem, and the difference is that agricultural infrastructure has a positive impact on rural land transfer at the confidence level of 10%. Table 3 Basic regression results of influencing factors of rural land circulation. (1) (2) (3) OLS 2SLS 2SLS(Missing variables) lndig 0.387*** 0.358*** 0.367*** (14.51) (10.92) (10.77) lnfrl 0.112*** 0.122*** 0.121*** (4.52) (4.76) (4.72) lnfam -0.0874 -0.0915 -0.0805 (-1.25) (-1.30) (-1.15) lnfha -0.0916* -0.0949** -0.0955** (-1.91) (-1.98) (-2.00) lnfaf 0.234 0.246* 0.260* (1.57) (1.65) (1.75) lnfei -0.109 -0.0423 -0.0369 (-1.29) (-0.44) (-0.39) lntla 0.211** 0.241*** 0.248*** (2.54) (2.82) (2.93) lnent -0.110* (-1.76) _cons 2.115 1.399 2.014 (1.51) (0.95) (1.30) R value 0.8556 0.8293 0.7489 Individual fixation Yes Yes Yes Time fixed effect No No No Overrecognition test - Yes Yes Hausman - 0.9359 0.8904 First stage F number - 78.47 78.97 N 310 310 310 The symbols *, **, and *** indicate significant at 1%, 5%, and 10% confidence levels, respectively 4.1.2. Robustness test Result (3) is a robustness test. 2SLS estimation is performed by adding possible missing variables (the number of enterprises on the gauge). The positive and negative values and significance of result (3) are consistent with those of model (2), that is, the model passes the robustness test. The fitting degree of model (2) is higher than that of model (3), and instrumental variables are added on the basis of model (1) to eliminate the endogeneity problem. Therefore, the estimated results of model (2) are selected for analysis. This paper explains the regression results as follows: The development of digital inclusive finance provides capital guarantee and technical support of transaction information channel for land transfer, enhances the transfer ability of land transfer party, and enhances the transfer willingness of land transfer party, which is conducive to rural land transfer. It is worth noting that the measurement of the variable of rural labor force in this paper is reflected by the number of rural employees, rather than the number of agricultural labor force, which can more intuitively analyze the impact of changes in rural labor force on rural land transfer. Rural employment can be divided into agricultural, non-agricultural and part-time employment. Some studies have suggested that non-agricultural employment is beneficial to land transfer[43], while the preliminary regression results of this paper show that rural labor is beneficial to land transfer, and the two are not in conflict, which is closely related to the employment structure and age structure of rural labor force. At present, the number of rural labor force is on the rise. This phenomenon is mainly caused by the return of the migrant labor force[44]. These returning rural labor force are accustomed to non-agricultural production, and considering the rarity of agricultural production technology and the current situation of low income in agricultural production, their employment mode is often part-time. Part-time farmers can obtain higher income. Under the driving effect of returning farmers on rural part-time employment, more small farmers accelerate land transfer. Thus, at this stage, the promotion effect of increasing the number of rural labor force on rural land transfer is essentially the driving effect of rural labor return on rural industry and the demonstration role of part-time employment. The dual effect has a positive impact on land transfer. The substitution effect of agricultural mechanization on agricultural labor force is conducive to the production of economies of scale in agricultural scale operation, which is conducive to the willingness of large agricultural households to expand the operation area. At the same time, due to the extrusion effect of agricultural machinery on agricultural surplus labor force, the non-agricultural employment of rural labor force is accelerated. These farmers who are engaged in non-agricultural employment are more likely to transfer their land out. However, due to the influence of topographic factors, regional heterogeneity makes the estimated impact of agricultural mechanization on rural land transfer biased to a certain extent, thus showing no significant effect. The development of rural infrastructure has integrated fragmented land into plots, guaranteed the efficiency of large-scale agricultural production and management, and enhanced the willingness of large agricultural households to transfer to land. The fixed assets investment of rural households is the capital for agricultural production and operation of rural households produce consumption, is not conducive to farmers into the land; As for the land transfer side, farmers' pension insurance does not reduce its dependence on the function of rural residents' land pension, and their willingness to transfer out of land does not increase.4.1.3. Heterogeneity test There is a big difference between the level of regional economic development and agricultural modernization in China. In order to further analyze the influencing factors of rural land transfer in different regions, 31 provinces were divided into eastern regions, central regions and western regions according to the statistical caliber of the National Bureau of Statistics, regional heterogeneity test was conducted, and 2SLS adding instrumental variables was selected for estimation (Table 4 ). In the eastern region, digital inclusive finance and rural labor force have a positive effect on rural land transfer, while agricultural mechanization inhibits rural land transfer. The explanation of this paper is as follows: In the eastern region of China, the mechanization level of agricultural machinery is higher, and the transportation is developed, and the agricultural mechanization service market is ahead of the central and western regions. Convenient agricultural machinery service brings more choices for the agricultural production mode in the eastern region, such as the agricultural trusteeship mode, which does not produce land transfer, but makes non-agricultural farmers have the willingness to recover land and increase agricultural operating income. In the central region, digital inclusive finance and agricultural mechanization have a positive impact on rural land transfer, while rural household pension insurance is not conducive to land transfer, and the impact of rural labor force on rural land transfer is not significant. The explanation is as follows: the economic level and agricultural modernization level in the central region are relatively high. Digital inclusive finance and agricultural mechanization enhance the ability and willingness of farmers to transfer land from the role of financial support and labor substitution respectively. The consumption of agricultural funds by farmers' pension insurance inhibits rural land transfer; The rural labor force in the central region also shows a growing trend, but due to the restriction of economic development level in the central region, its township industry is still in the initial stage and provides few rural non-agricultural jobs, resulting in the return of rural labor force has no significant impact on land transfer. In the western region, digital inclusive finance and agricultural infrastructure accelerate the process of rural land transfer, and the impact of rural labor force and agricultural mechanization on rural land transfer is not significant. The explanation of this paper is as follows: Affected by topographic factors and economic level, the level of agricultural modernization in western China is not high[ 45 ]. The development of digital inclusive finance provides funds and technical support for farmers. Meanwhile, the construction of agricultural infrastructure improves agricultural production efficiency and is conducive to rural land transfer; The western region is sparsely populated and the rural labor force is scarce, showing a trend of decreasing rural labor force in general. Farmers who go out to engage in non-agricultural activities are affected by the land situation and hope to transfer their land; However, there are more mountainous areas in the western region, and the production efficiency of small agricultural machinery suitable for mountainous areas is low. It is difficult for large agricultural households left in rural areas to expand their production and management area, resulting in the phenomenon that rural farmers do not want the land to be abandoned and are willing to give up the right to use the land free of charge. This process has no positive effect on land transfer. In the western region, agricultural mechanization is limited by geographical conditions, which has limited effect on the improvement of agricultural production efficiency, and has no obvious effect on the growth of the ability and willingness of large agricultural households to expand production and management area. In conclusion, pratt &whitney financial to the positive role of rural land circulation is not subject to regional restriction (hypothesis 1 ). The impact of agricultural mechanization on rural land transfer is different in the eastern and western regions. For the eastern region, the rapid development of agricultural mechanization has promoted the smooth operation of the agricultural machinery service market and the land trustement model, and made farmers in the eastern region hope to recover the transferred land in order to obtain more agricultural productive income, which shows that the development of agricultural mechanization is not conducive to land transfer. For the western region, the effect of agricultural mechanization on the improvement of agricultural production efficiency in the mountainous environment is not good, and it is difficult to improve the willingness of large agricultural households to transfer to land. It is worth noting that only the increase of rural labor force in the eastern region has a positive effect on rural land transfer. It also indicates that the return of rural labor force in the eastern region has sufficient rural non-agricultural jobs, and drives local farmers to engage in non-agriculture, which is conducive to farmers' willingness to transfer out of land. Agricultural infrastructure in western China has a significant positive impact on rural land transfer industry, and the land in less developed areas is more dispersed and less contiguity, so strengthening the construction of agricultural infrastructure is the focus of promoting rural land transfer in western China. Table 4 Analysis results of regional heterogeneity of influencing factors of rural land transfer. (4) (5) (6) East Central West lndig 0.256*** 0.537*** 0.384*** (4.34) (7.65) (8.40) lnfrl 0.146** 0.0257 0.0524 (2.33) (0.59) (1.42) lnfam -0.452*** 0.221** -0.278 (-2.96) (2.49) (-1.59) lnfha -0.154** -0.0647 -0.0910 (-2.18) (-0.74) (-0.88) lnfaf 0.228 -0.196 0.833*** (0.92) (-0.56) (3.06) lnfei -0.0684 -0.657*** 0.0697 (-0.53) (-3.15) (0.46) lntla 0.819*** 0.597*** -0.0820 (3.86) (3.36) (-0.77) _cons -1.337 2.896 1.562 (-0.56) (0.88) (0.61) R value 0.6953 0.1954 0.5303 Individual fixation Yes Yes Yes Time fixed effect No No No Overrecognition test Yes Yes Yes Hausman 0.4552 0.7475 0.9994 First stage F number 65.40 6.28 47.15 N 110 80 120 The symbols *, **, and *** indicate significant at 1%, 5%, and 10% confidence levels, respectively 4.2. Spatial econometric analysis The spatial correlation test of the core explanatory variable digital financial inclusion is shown in Table 5 . As measured by Moran Index, Moran 's I is between 0.105 and 0.155, all of which are significant under 1% confidence interval. There is positive spatial dependence of digital financial inclusion in all regions, and the spatial correlation is increasing year by year. The above analysis further shows that digital inclusive finance has the characteristics of spatial agglomeration, so the analysis of the impact mechanism of digital inclusive finance on rural land transfer needs to consider the spatial spillover effect. Table 5 pratt &whitney financial global correlation test results (geographic weighting matrix). Year Digital Universal Finance Year Digital Universal Finance Moran΄s I P value Moran΄s I P value 2011 0.116 0.000 2016 0.132 0.000 2012 0.138 0.000 2017 0.140 0.000 2013 0.137 0.000 2018 0.150 0.000 2014 0.135 0.000 2019 0.155 0.000 2015 0.105 0.000 2020 0.161 0.000 4.2.1. Spatial model selection In this paper, the optimal spatial measurement model is selected through LM test, LR test, Wald test, Hausman test and other diagnostic tests, and the results are shown in Table 6 . LM test is significant in geographical weight matrix, economic weight matrix and economic geography nested weight matrix, indicating the existence of spatial effects; Both LR test and Wald test show that spatial Durbin model (SDM) has stronger explanatory power than spatial lag model (SAR) and spatial error model (SEM). According to the Hausman test, if the model chooses geographic weight matrix or economic weight matrix, the fixed effects estimation should be used; if the model chooses economic geography nested weight matrix, the random effects estimation should be used. When geographical weight matrix and economic weight matrix are selected in this paper, the fixed effects estimation of spatial Durbin model (SDM) is carried out. The random effects of spatial Durbin model (SDM) are estimated when economic geography nested weight matrix is selected. Considering that there is time lag in the influence of explanatory variables on rural land circulation, the time and space lag term is added to the model, and finally the static spatial Durbin model and dynamic spatial Durbin model with fixed time and space are selected for estimation. Table 6 Results of relevant diagnostic tests for spatial model selection (divided by weight matrix). Weight Matrix Geographic Matrix Economic Matrix Economic Geography nested matrix STATISTICS Test results P value Test results P value Test results P value LMERR test 375.365*** 0.0000 383.358*** 0.0000 194.434*** 0.0000 LM(Robust)ERR test 271.563*** 0.0000 273.881*** 0.0000 122.417*** 0.0000 LMLAG test 120.035*** 0.0000 124.418*** 0.0000 88.790*** 0.0000 LM(Robust)LAG test 16.233*** 0.0000 14.941*** 0.0000 16.864*** 0.0000 LR Test ERR 23.32*** 0.0015 22.61*** 0.0020 15.45** 0.0307 LR Test LAG 20.45*** 0.0047 19.25*** 0.0074 17.37** 0.0152 Wald Test 23.57*** 0.0014 23.28*** 0.0015 16.65** 0.0247 Hausman test 34.75*** 0.0027 27.18** 0.0273 12.69 0.6264 4.2.2. Dynamic spatial Durbin model This article selects the space durbin test in the influence factors of rural land circulation, the regression results in Table 7 . Result (7) is the estimation result of the static spatial Durbin model under the geographical weight matrix. The results show that digital inclusive finance, rural labor force, agricultural mechanization and agricultural facilities have significant positive impacts on rural land transfer; Rural household fixed asset investment and pension insurance have a significant negative impact on rural land transfer. Digital inclusive finance gives financial support to land transfer transferers, which directly promotes rural land transfer. The return of rural labor force accelerates the development of rural industry, and enhances the willingness of the land transfer party under the role of higher nonagricultural income. By changing the mode of agricultural production, agricultural mechanization makes it possible for farmers to further expand the scale of agricultural operation. The development of agricultural facilities is conducive to the contiguity of land and enhances the willingness of land transferers to expand the scale of agricultural operation. On the other hand, fixed asset investment and pension insurance of rural households consume their funds to a certain extent, and the total amount of funds used for agricultural production and operation decreases, which has a negative effect on rural land transfer. Results (8) and (9) are the estimates of static spatial Durbin model under the economic weight matrix and economic geographic weight matrix respectively. The estimated results are basically consistent with those of (7), that is, through the robustness test, the static spatial Durbin model of economic weight matrix is selected as the best fit among the three weight matrices. Exist in the process of considering the influence of time lag, joined by variable time lag of rural land circulation, dynamic space durbin test model. Results(10) are estimated by the dynamic spatial Durbin model under the geographical weight matrix. The regression results show that: the influence coefficient of digital inclusive finance and agricultural infrastructure construction on rural land transfer increases, showing a significant positive effect; Rural labor force for the promotion of rural land circulation effect decreased; The influence coefficient of agricultural mechanization on rural land transfer is basically unchanged;The obstructing effect of fixed asset investment of peasant households on rural land transfer is increasing, while the influence of peasant household pension insurance on rural land transfer is not significant. The above results can be explained as follows: Digital inclusive finance can provide long-term stable financial support for rural households, and agricultural infrastructure is beneficial to the improvement of agricultural production efficiency in the long run, so both digital inclusive finance and agricultural infrastructure have a positive impact on rural land transfer in the long run; The promotion effect of rural labor force growth on rural land transfer is mainly guided by non-agricultural employment of returning farmers, and in the long run, non-agricultural employment opportunities in rural areas tend to be saturated, thus reducing the promotion effect on rural land transfer. Investment in fixed assets of rural households is a large expenditure for rural households. In the long term after investment in fixed assets, rural households will face the dilemma of tight funds or even debts, and their ability to transfer to land will decline, thus increasing the hindrance to rural land transfer in the long term. Models (11) and (12) are the dynamic spatial Durbin mode estimation under the economic weight matrix and the economic geographic weight matrix respectively. The regression results are basically consistent with those of (10), and the spatial-temporal lag terms of the explained variables are significant, among which the geographical weight matrix has the highest degree of fit.The analysis of spatial spillover effects in the following paper mainly focuses on the estimation results under the geographical weight matrix. Table 7 Estimation results of spatial Durbin model. Models Static space Durbin model Dynamic spatial Durbin model Result weig (7) (8) (9) (10) (11) (12) ht matrix Geography Economy Economic Geography Geography Economy Economic Geography lndig 0.472** 0.476** 0.379 0.721** 0.814** 1.106** (2.41) (2.29) (1.37) (2.06) (2.18) (2.03) lnfrl 0.181*** 0.166*** 0.190*** 0.0731* 0.0591 0.186*** (4.83) (4.49) (5.73) (1.93) (1.52) (5.24) lnfam 0.441*** 0.362*** 0.537*** 0.446*** 0.371*** 0.615*** (4.43) (3.46) (4.92) (4.35) (3.40) (5.09) lnfha -0.459*** -0.411*** -0.304*** -0.767*** -0.614*** -0.337*** (-7.25) (-6.67) (-5.23) (-10.97) (-9.09) (-5.23) lnfaf 0.546*** 0.587*** 0.424*** 0.689*** 0.646*** 0.407*** (7.22) (7.67) (5.08) (8.94) (8.27) (4.63) lnfei -0.242*** -0.226** -0.195** -0.130 -0.119 -0.149 (-2.67) (-2.43) (-2.20) (-1.41) (-1.25) (-1.53) lntla 0.578*** 0.568*** 0.441*** 0.640*** 0.645*** 0.348*** (8.74) (8.42) (5.72) (9.63) (9.32) (4.12) L.W. lndig -6.098*** -4.856*** -1.350*** (-10.10) (-8.36) (-3.03) W.lndig 0.233 2.074 0.149 4.498* 1.391 4.166* (0.18) (0.84) (0.12) (1.86) (1.30) (1.94) W.lnfrl 0.788*** 1.283*** 0.479* 0.816*** 0.386** 0.429** (2.60) (4.10) (1.79) (2.95) (2.37) (2.24) W.lnfam -1.326 -1.338 -1.027 -2.097*** 2.886*** 2.567*** (-1.56) (-1.59) (-1.27) (-2.59) (4.01) (3.33) W.lnfha -2.212*** -4.477*** -1.366*** -2.103*** -0.431 -1.285*** (-4.53) (-8.27) (-3.16) (-4.58) (-1.38) (-3.30) W.lnfaf 3.513*** 9.127*** 3.069*** 8.682*** -1.757*** -0.499 (4.20) (9.74) (3.97) (8.99) (-3.05) (-0.70) W.lnfei -3.148*** -3.650*** -2.540*** -4.634*** 0.462 0.577 (-4.04) (-4.65) (-3.54) (-5.91) (0.92) (0.96) W.lntla 3.804*** 5.867*** 2.483*** 4.636*** -1.196*** -0.345 (6.32) (9.24) (4.35) (7.35) (-2.99) (-0.68) rho -0.779** -0.566** -0.169 0.0203 0.0410 0.0217 (-2.56) (-2.05) (-0.87) (0.08) (0.16) (0.10) sigma2_e 0.158*** 0.168*** 0.187*** 0.148*** 0.161*** 0.198*** (12.19) (12.32) (12.49) (13.12) (13.12) (13.12) R value 0.8278 0.8431 0.7712 0.7866 0.5433 0.6145 The symbols *, **, and *** indicate significant at 1%, 5%, and 10% confidence levels, respectively 4.2.3. Spatial spillover effect analysis Regarding the spillover effects of each influencing factor, the spillover effects of the regression results (7) of static spatial Durbin model and the regression results (10) of dynamic spatial Durbin model under the geographical weight matrix were analyzed respectively. The results showed that the pratt &whitney financial to surrounding areas of rural land circulation in long-term significant positive spillover effect, assumption 2 certificate; Rural labor force and agricultural infrastructure have significant spillover effects on the surrounding areas; The spillover effect of peasant household pension insurance on the surrounding areas is a significant negative effect. The explanation of this paper is as follows: The spillover effect of digital inclusive finance is mainly generated by its diffusion effect on rural finance and industrial economy in the surrounding areas, in addition, it also includes the learning effect of financial institutions in the surrounding areas to the developed areas of digital inclusive finance. The spillover effect of rural labor force and agricultural infrastructure is mainly due to its support for the development of rural industries, forming a demonstration effect, speeding up the development of rural industries in the surrounding areas, and thus promoting the transfer of rural land in the surrounding areas.However, in the previous analysis, peasant household pension insurance is not conducive to rural land transfer. Its demonstration effect drives farmers in the surrounding areas to attach importance to the pension insurance, and thus produces negative spillover effects on rural land transfer in the surrounding areas. As different geographical conditions have a great influence on the spillover effect of agricultural mechanization, the geographical weight matrix constructed by latitude and longitude alone cannot reflect its real spillover effect well. The spillover effect of agricultural mechanization can be obtained from the estimation result (11) of the dynamic spatial Durbin model under the economic weight matrix, showing a significant positive spillover effect. There are two main reasons for this. The first is the learning effect of the surrounding areas to the developed areas of agricultural mechanization; the second is the diffusion effect of agricultural machinery services in the developed areas of agricultural mechanization to the surrounding areas, which improves the operation capacity of agricultural machinery in the surrounding areas, and thus produces a positive spillover effect on the land transfer in the surrounding areas. 4.2.4. Decomposition of spatial effect The decomposition of spillover effects in this paper is shown in Table 8 . Direct effects represent the direct impact of a certain explanatory variable on rural land circulation in the local region, including the impact of the explanatory variable on neighboring areas and the effect on the local region (feedback effect). Indirect effects represent proximity the indirect effect of a regional explanatory variable on rural land circulation in the region; Total effect represents the average influence of an explanatory variable in a certain region on rural land transfer in all regions. According to the model fitting effect, this paper selects the estimated results under the geographical weight matrix to analyze the long-term and short-term effects of the spillover effect decomposition respectively. Table 8 Estimation results of spatial Durbin model. Long term Short term Direct effect Spillover effect Total Effect Direct effect Spillover effect Total Effect lndig 0.486** -0.130 0.356 0.723** 2.637 3.360 (2.19) (-0.16) (0.51) (2.11) (0.76) (0.96) lnfrl 0.161*** 0.395** 0.556*** 0.0834* 1.443** 1.526** (4.57) (2.14) (2.83) (1.86) (2.17) (2.20) lnfam 0.496*** -0.977* -0.481 0.441*** -1.466 -1.024 (4.82) (-1.86) (-0.95) (4.18) (-1.31) (-0.90) lnfha -0.411*** -1.124*** -1.535*** -0.786*** -5.024** -5.810** (-7.35) (-3.45) (-4.54) (-7.37) (-2.32) (-2.57) lnfaf 0.457*** 1.835*** 2.292*** 0.731*** 10.16** 10.89** (6.00) (3.56) (4.47) (3.98) (2.39) (2.47) lnfei -0.158* -1.785*** -1.943*** -0.155 -4.126** -4.281** (-1.68) (-3.45) (-3.55) (-1.28) (-2.08) (-2.07) lntla 0.482*** 2.026*** 2.508*** 0.670*** 6.644** 7.313** (6.82) (4.08) (4.85) (5.02) (2.22) (2.35) The symbols *, **, and *** indicate significant at 1%, 5%, and 10% confidence levels, respectively In the long run, rural land transfer is directly and positively affected by the rural labor force and agricultural infrastructure in the region, and its indirect effect and total effect are significantly positive, indicating that the change of rural labor force and the development of agricultural infrastructure are conducive to rural land transfer in the long run, and show a good spatial spillover effect. Pratt &whitney financial and agricultural mechanization of rural land circulation, there is only direct effects of its spatial spillover effect is not obvious, the reason is that pratt &whitney financial barriers, exists between regional financial services for the spread of the surrounding area effect is not strong; Agricultural mechanization is limited by geographical factors, and it is difficult for agricultural machinery technology and agricultural machinery services to exert diffusion effect. In the short term, rural labor force and agricultural infrastructure also have direct effects and spillover effects on rural land transfer. From the analysis of impact coefficient, the direct impact of rural labor force is stronger in the long term, while the direct effect of agricultural infrastructure is more obvious in the short term.However, the spillover effects of both on rural land transfer show a weakening trend in the long run. The direct and spillover effects of fixed assets investment and pension insurance of rural households on rural land transfer show significant negative effects in the long and short term, because the investment in fixed assets and the purchase of pension insurance of rural households restrict the expansion of production and management scale of rural households to a certain extent. 4.3. Intermediary effect analysis As for the testing process of intermediary effect, this paper mainly adopts the suggestion of Jiang Tian (2022) on the testing process of intermediary effect,focusing on the analysis of the causal relationship between intermediary variables and dependent variables, and re-tests the intermediary effect of rural labor force,agricultural mechanization and agricultural facilities in the process of digital inclusive finance affecting rural land transfer through the stepwise analysis method. Table 9 Estimation results of intermediary effect. (14) (15) (16) (17) (18) (19) (20) lnflc lnfrl lnflc lnfam lnflc lnfaf lnflc lndig 0.432*** 0.461** 0.413*** 0.242*** 0.429*** 0.140*** 0.365*** (4.96) (2.07) (4.79) (3.11) (4.90) (3.55) (4.09) lnfrl 0.0806*** (3.54) lnfam 0.197*** (2.96) lnfaf 0.506*** (5.24) Control Yes Yes Yes Yes Yes Yes Yes lntla 0.375*** 0.393*** 0.325*** 0.245*** 0.373*** 0.131*** 0.299*** (5.06) (2.82) (4.35) (3.44) (5.38) (3.79) (4.35) _cons -7.517** -13.52* -3.423 -1.454 -3.570 1.599 -6.197* (-2.31) (-1.70) (-0.95) (-0.50) (-1.09) (1.01) (-1.66) rho 0.607*** 0.399*** 0.533*** 0.631*** 0.412*** 0.384*** 0.613*** (7.38) (3.20) (5.49) (6.97) (3.78) (2.76) (7.30) lgt_theta -2.879*** -2.169*** -2.887*** -3.049*** -2.680*** -3.807*** -2.378*** (-18.42) (-13.88) (-18.31) (-18.82) (-15.99) (-27.02) (-13.89) sigma2_e 0.0224*** 0.145*** 0.0214*** 0.0177*** 0.0218*** 0.00454*** 0.0230*** (11.59) (11.76) (11.59) (11.45) (11.57) (11.71) (11.51) N 310 310 310 310 310 310 310 The symbols *, **, and *** indicate significant at 1%, 5%, and 10% confidence levels, respectively About the intermediary variable and the discussion of the causal relationship of rural land circulation, academics have respectively demonstrates the rural labor force, agricultural infrastructure, agricultural mechanization,the positive role on the rural land circulation; About pratt &whitney financial directly impact on the rural land circulation, this paper USES space doberman model stepwise regression (Table 9 ), result (14) are consistent with previous argument by causality: pratt &whitney financial has significant positive effect on rural land circulation,49 [ 10 ], influence coefficient c is 0.432; Results (15)(17) (19), respectively, for the rural labor force, agricultural mechanization, agricultural infrastructure directly impact on the rural land circulation, all show the positive influence[ 37 , 46 – 49 ]. As for the causal relationship between digital inclusive finance and various intermediary variables, many scholars have conducted in-depth discussions on the causal relationship between digital inclusive finance and rural labor force, agricultural mechanization and agricultural infrastructure[ 25 – 28 , 32 , 33 , 43 , 45 , 50 ].The stepwise method selected in this paper does not carry out a secondary test. The above analysis shows that rural labor force, agricultural mechanization and agricultural infrastructure have significant intermediary effects in the process of digital inclusive finance affecting rural land transfer. In order to further quantify the influence of the above three intermediary effects, the stepwise regression method is used to estimate. Results (16), (18) and(20) respectively show the comprehensive impact of digital inclusive finance and various intermediary variables on rural land transfer, and each influence coefficient is significant under 1% confidence interval, indicating that there is no masking effect, and the intermediary variables of rural labor force,agricultural mechanization and agricultural facilities have significant intermediary effects. Hypotheses 3, 4 and 5 are confirmed. In order of intensity, the mediating effects were agricultural infrastructure, rural labor force and agricultural mechanization. Explain about the mediation mechanism, this article as follows: one is the digital pratt &whitney finance by accelerating rural industry development produce more of the rural non-agricultural employment opportunities, make rural labor backflow can continue to non-agricultural, to a certain extent solved the rural labor force concerns about income home, and not competition existing agricultural land resource allocation; On the one hand, the rural labor force continues to expand the rural industry and provide more nonagricultural employment opportunities for farmers; on the other hand, it plays an exemplary role in driving the left-behind rural labor force and enhancing its willingness to transfer land out. Second, pratt &whitney financial funds for farmers through direct asset purchase of agricultural machinery, indirectly promote the development of agricultural machinery technology and market, promote the local agricultural mechanization level, to enhance agricultural large into land.Third, digital inclusive finance provides financial support for the construction of agricultural infrastructure, and the improvement of agricultural infrastructure is conducive to agricultural scale management, thus promoting farmers' land transfer. 5. Conclusions and countermeasures 5.1. Research Conclusion Based on basic regression analysis, regional heterogeneity analysis, spatial spillover effect analysis and intermediary mechanism analysis, this paper analyzes the action mechanism and regional heterogeneity of influencing factors of rural land transfer, as well as the intermediary effects of rural labor force, agricultural mechanization and agricultural infrastructure in the process of digital inclusive finance affecting rural land transfer in an all-round way. The main research conclusions are as follows: (1) Digital inclusive finance is beneficial to rural land transfer. This positive effect is influenced by the regional economic level and agricultural modernization level, and the regional heterogeneity is stronger in the central region than in the western region and the western region than in the eastern region. Moreover, due to the existence of intangible barriers between regions in the development of digital inclusive finance in China, the spillover effect of digital inclusive finance on rural land transfer is weak. In this paper, it is only significant in the dynamic spatial Durbin model under the geographical weight matrix, indicating that digital inclusive finance can produce diffusion effect in the long run. The direct impact of digital inclusive finance on rural land transfer mainly depends on the enhancement of farmers' willingness to transfer to land by capital and technology. In addition,farmers' investment in fixed assets and rural old-age insurance consumes agricultural funds and hinders the process of rural land transfer. It can be inferred that rural old-age care still depends on the income from agricultural production and operation. The coverage of digital inclusive finance in rural production and life is insufficient. (2) The causal relationship between intermediary variables and rural land circulation. The positive effect of rural labor force on rural land transfer is not restricted by region.At present, the increase in the number of rural labor force in China is mainly caused by the return of rural labor force. The author mainly analyzes the mechanism of its influence on rural land transfer from the perspective of the employment structure of rural labor force. On the other hand, the non-agricultural employment or entrepreneurial behavior of returning farmers can promote the development of rural industries, and at the same time, promote non-agricultural employment and concurrent employment in rural areas, and promote rural land transfer. The overall effect of agricultural mechanization on rural land transfer is promoting. However, due to the prevalence of agricultural machinery service and land trusteeship mode in eastern China, the higher the level of agricultural mechanization is, it is not conducive to farmers' willingness to transfer out of the land. The construction of agricultural infrastructure is conducive to enhancing the willingness of farmers to expand the scale of operation, and thus has a positive effect on rural land transfer. (3) Digital inclusive finance -- intermediary variable -- the mechanism of rural land transfer. The intermediary mechanism of digital inclusive finance affecting rural land transfer is composed of agricultural infrastructure, rural labor force and agricultural mechanization, and its intermediary effect is decreasing. First, the implementation and construction of agricultural infrastructure developed rapidly with the financial support of digital inclusive finance, which enhanced the willingness of large agricultural households to expand the scale of agricultural production and operation; Second, the improvement of the rural non-agricultural employment environment by digital inclusive finance accelerates the return of rural labor force, and the employment structure of rural labor forces shifts to non-agricultural, forming a positive feedback effect on the development of rural industries. The trend of non-agricultural employment enhances the willingness of farmers to transfer land and promotes the transfer of rural land. Third, the development of agricultural mechanization depends on the financial support of digital inclusive finance for farmers and agricultural machinery market, and its role in improving agricultural production efficiency and substituting rural labor force enhances farmers' willingness to transfer to land. 5.2. Countermeasure (1) Expand the coverage of financial services for digital financial inclusion and remove regional barriers. Promote the breadth and depth of digital inclusive financial services,continue to guide financial institutions to use digital inclusive financial services to sink financial services, invest financial resources and services more comprehensively in rural production and life, and establish a sound digital credit evaluation system for the main links of agricultural production and important expenditures in rural life. To improve the coverage and availability of financial services for rural residents; Give full play to the digital technological advantages of digital inclusive finance, improve the mechanism for the formation of rural land transfer prices, establish a hierarchical coordination mechanism for financial institutions, and form a multi-level digital inclusive financial system. On the demand side of inclusive financial services, through the publicity of offline financial institutions and the popularization of digital financial platforms, improve the financial literacy of rural residents, promote the transformation of financial services into a "buyer's market", customize financial service products according to the needs of rural residents, such as credit, investment, wealth management, insurance and other aspects, and improve the depth of inclusive financial services. In addition, the geographical restrictions of digital financial inclusion should be weakened, its diffusion effect on surrounding areas should be enhanced, and the balanced development of digital financial inclusion should be promoted. (2) Promote the development of rural industries and non-agricultural employment and entrepreneurship of returning farmers to form new quality productivity in rural areas.In areas with developed rural industries, we will strengthen rural industrial planning, focus on undertaking the transfer of non-agricultural industries, extend the agricultural industrial chain, and increase rural employment Carrying capacity can attract rural labor to return to their hometown for employment and entrepreneurship, further promote the development of rural industries,and form a virtuous circle of industrial agglomeration[ 51 ]. In areas with underdeveloped rural industries, planning guidance and policy support should be strengthened, characteristic industries such as green agriculture, traditional handicraft industry and rural tourism should be developed according to local conditions, and financial resources and digital platforms of digital inclusive finance should be utilized to provide long-term and stable financial services for the initial stage of rural industrial development[ 52 ]. Finally, efforts should be made to enhance the income-increasing role of non-agricultural industries in rural areas, promote the appropriate scale operation of agricultural industries, strengthen the transformation of scientific and technological achievements and the introduction of talents in rural areas, improve the production level of rural industries, and form new quality productivity in rural areas. (3) Raise the level of agricultural mechanization in the central and western regions and continue to strengthen agricultural infrastructure construction. Give full play to the role of digital universal benefit financial support for agricultural machinery and agricultural infrastructure, promote agricultural machinery and equipment suitable for the central and western regions,establish agricultural machinery operation service system, and enhance the radiation effect of agricultural production services on the surrounding areas; To promote the construction of high-standard farmland through rural infrastructure in irrigation, transportation and other aspects, is conducive to the popularization of agricultural mechanization and moderate scale management in the central and western regions. In addition, strengthening agricultural technology research and development and production mode innovation is an important way to improve agricultural production efficiency in the central and western regions. In terms of agricultural machinery technology, the coverage rate of agricultural machinery operation in the central and western regions can be improved from the aspects of agricultural machinery improvement and special crop machinery innovation, which is conducive to transforming agricultural production mode and speeding up the process of rural land transfer. To further promote the appropriate scale management of agriculture and the development of rural industries. Declarations Author Contributions: Conceptualization, T.C.; methodology, software, investigation, and writing—original draft preparation, T.C. and L.L.; writing—review and editing, T.C. and L.L.; project administration, T.C.; funding acquisition, T.C. and L.L. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Research on 2023 Major Project of Philosophy and Social Science Research in Hubei Higher Education Institutions “Research on Digital Economy Empowering the Integration of Urban and Rural Development in Hubei Counties”(23ZD114) Data Availability Statement: The data generated in this study are described in Section 3; they are available from the corresponding author on reasonable request. Acknowledgments: The authors thank all research members who provided support and assistance in this study Conflicts of Interest: The authors declare no conflicts of interest. Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. References Chen S Analysis of Policy Performance and Influencing Factors of Land Transfer–A Comparative Study Based on Three Places in East, Central and West China[J]. Social Sci ,2011,5,48–56.[CrossRef] Huang Z, Wang P The role of digital inclusive finance in the development of digital agriculture[J]. Agricultural Economic Issues ,2022,5,27–36.[CrossRef] Xiong Q, Guo XYJDF, Inclusion Land Circulation High-Quality Dev Agriculture[J] Sustainability ,2024,16(11).[CrossRef] Yang H, Li Y, Han X et al (2019) Has land fragmentation increased the cost of agricultural production for large-scale farmers? --A micro survey based on 776 family farms and 1,166 large professional households across China[J]. 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Economics(Quarterly) 17(4):1557–1580 [CrossRef] Liang B, Zhang J (2019) Can digital inclusive financial development incentivize innovation? --Evidence from Chinese cities and SMEs[J]. Contemp Economic Sci 41(5):74–86 [CrossRef] Guo F, Wang J, Wang F et al (2020) Measuring the development of digital inclusive finance in China:indexing and spatial characterization[J]. Economics(Quarterly) 19(4):1401–1418 [CrossRef] Qian L, Hong M, Non-farm, Employment Land Transfer and Agricultural Production Efficiency Changes-An Empirical Analysis Based on CFPS[J]. China Rural Econ, 2016,(12):2–16. [CrossRef] Kang J, Yan Z,Wu F Rural Labor Return, Employment Choice and Agricultural Land Transfer - An Empirical Study Based on a Thousand Villages Survey[J]. Southern Economy ,2021,(07):72–86. [CrossRef] Li P, Wu H (2022) A study on the spatial and temporal differentiation of the efficiency of agricultural machinery socialization services–evidence from Chinese provinces[J]. 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[CrossRef] Feng D, Gao M, Zhou L (2020) Digital financial inclusion and resident entrepreneurship:Evidence from a survey of labor dynamics in China[J]. Res Financial Econ 35(1):91–103 [CrossRef] Xing Z, Zhong R (2023) Digital Financial Inclusion, Labor Mobility and Industrial Structure Optimization-An Empirical Analysis Based on the Perspective of New Economic Geography[J]. Explor Economic Issues, (4):142–156. [CrossRef] Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6736992","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":473078327,"identity":"386cf800-f8a9-4fa4-8e60-f36447a010fc","order_by":0,"name":"Tao Chen","email":"","orcid":"","institution":"Yangtze University","correspondingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Chen","suffix":""},{"id":473078328,"identity":"83b00390-4fcf-4f32-aa32-7e15019e6970","order_by":1,"name":"Lun Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIie3RMWsCMRTA8SeBTI9mTahcN+eI4OSHSRBuuoLjDYInJ+fQFlf7LRw7Xjl4XWJnt+ruoJuDqN0Vc9065De/P++FAATBP8RF/nXYYS8SUH2uTTr0Jw+SjJo3444aU1+vHfmTCBL9iL3KLirXUpsJq3EYkNGYsMZ74XhqMw5i+mLuJywvjXScCVzSyn40QbrlwrulbL8iV/PveGUdBy2ffUnSzuxJov7Zdge2YLWSDpSopS5dF+olkuJGhkarjPrSOELvW55mObEjnkez36/cH9JhJKZv95Mr+LfxIAiC4KYL0TdNvkkW2wkAAAAASUVORK5CYII=","orcid":"","institution":"Yangtze University","correspondingAuthor":true,"prefix":"","firstName":"Lun","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-05-24 05:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6736992/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6736992/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97883856,"identity":"56175b7e-024a-463f-93b8-7e33662e272c","added_by":"auto","created_at":"2025-12-10 12:54:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1803498,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6736992/v1/85097116-30bb-4dec-94ef-8d2ecc021810.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of Digital Finance on Rural Land Transfer: Dynamic Spillover Effects and Mechanism Examination","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eLand is the basic means of agricultural production and a key factor in agricultural modernization. Since the implementation of the rural household contract responsibility system, the long-term decentralized and fragmented agricultural production and management mode has restricted the process of agricultural modernization in China. Promoting rural land transfer is the inevitable way to achieve moderate scale agricultural management. It produces two effects of marginal output leveling and transaction income, that is, improving the efficiency of resource allocation and the enthusiasm of farmers for land investment, which is conducive to the increase of farmers' income, agricultural efficiency and rural industry development [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Since the promulgation of the Measures for the Management of the Transfer of Contracted Rural Land Management Rights in 2005, the transfer area of contracted rural land in China has increased from 54\u0026nbsp;million mu to 530\u0026nbsp;million mu in 2020. The land transfer policy has realized effective radiation and diffusion at the geographical and spatial level. However, due to the flow and allocation of land elements, the objects and interests involved are complicated. The imperfect and unsound land transfer market has greatly constrained the expansion of scale operation of rural households. In the context of the current rapid development of digital economy, the connection between digital elements and agricultural development is continuously strengthened. Digital inclusive finance can not only effectively address farmers' financing difficulties and high financing costs, provide financial channels and credit guarantee for farmers' land transfer, but also reduce transaction costs by promoting the development of digital agriculture [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. To a certain extent, the information asymmetry of the agricultural land transfer market has been alleviated, thus accelerating the pace of rural land transfer and promoting the process of agricultural modernization[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The 2024 Central Committee\u0026rsquo;s No. 1 Document positions \"developing rural digital inclusive finance\" as an important channel to improve the diversified investment mechanism of rural revitalization, and point out that the primary measure of the next stage of rural reform and innovation is \"improve the formation mechanism of land transfer price\". How to realize the supporting role of digital inclusive finance in promoting rural land transfer in rural reform and innovation has become an important issue in the field of \"agriculture, rural areas\" at present.\u003c/p\u003e \u003cp\u003eAt this stage, rural land transfer is restricted by many factors. First, agricultural funds are restricted. Land rent accounts for a large proportion of agricultural funds in agricultural production and operation, and agricultural funds are mainly derived from agricultural production and operation. The second constraint is land fragmentation, which is not conducive to mechanized operations and difficult to improve agricultural production efficiency [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, due to the scarcity of agricultural labor force, large-scale agricultural production cannot be satisfied. When large agricultural households expand the scale of production and operation, they will face problems such as increased production cost and reduced ability to prevent natural risks, thus impeding land transfer[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The third is the restriction of the transaction market. Under the conditions of the traditional rural land transfer market, a series of costs such as information collection, negotiation and decision-making, supervision and performance of the contract generated in the process of land transfer are not conducive to land transfer. Some scholars proposed to establish a land intermediary trading platform to reduce land transaction costs, and the main body responsible for the construction of land transaction platform can be composed of local governments and agricultural enterprises[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In addition, some scholars analyzed the influencing factors of farmers' willingness to transfer land from the micro level. In the process of urbanization, rural labor force is separated from traditional agriculture and engaged in non-agricultural labor to obtain wage income, which has a positive effect on farmers' willingness to transfer land. Moreover, as farmers' dependence on land decreases, the willingness to transfer farmland is further promoted [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Non-agricultural employed farmers and large agricultural households have differentiated land use modes, and have strong willingness to transfer and transfer land transfer respectively[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. On the other hand, due to the substitution of rural labor force by agricultural machinery, the restriction of the reduction of rural labor force on agricultural production and management has been overcome. At the same time, the development of agricultural mechanization has a positive effect on optimizing the input of agricultural production factors, reducing agricultural production costs, and increasing the willingness of large agricultural households to expand production and obtain economies of scale.\u003c/p\u003e \u003cp\u003eThe above constraints on rural land transfer can be summarized as: a single source of agricultural funds, land dispersion is not conducive to scale management, the impact of unsound land trading market on farmers' land transfer ability, as well as rural labor force and agricultural mechanization the impact on farmers' land transfer willingness. Digital inclusive finance can directly or indirectly have a positive effect on rural land transfer. On the one hand, digital inclusive finance can effectively alleviate the lack of rural financial resources, improve the rural credit evaluation system through digital technology[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], reduce transaction costs and other ways to lower the threshold for farmers to obtain financial support to help farmers get rid of the restrictions of \"acquaintance society\" and traditional financial institutions on raising funds for land transfer [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. On the other hand, digital inclusive finance regulates the financing process and scope of use of agricultural production organizations. It is conducive to the establishment of a risk prevention mechanism for agricultural production organizations through digital technology [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and the structural mismatch between the extensive credit demand and financial supply in the agricultural machinery operation service market can also be eliminated under the role of digital inclusive finance[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Provide convenience for agricultural production [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In addition, at the micro level, digital financial inclusion can stimulate farmers' entrepreneurial willingness by improving their financial literacy and sharing entrepreneurial risks and sharing entrepreneurial risks (He Guangwen et al., 2019) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Moreover, the information platform provided for entrepreneurs is conducive to enriching the social network of entrepreneurs and making up for the disadvantage of poor information[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. At the same time, the improvement of entrepreneurial environment and the adjustment of local industrial structure of digital inclusive finance are conducive to the activity of rural entrepreneurship[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Its supporting effect on county economy is conducive to regional industrial development and guarantees financing channels for entrepreneurs and small and micro enterprises. It provides more employment opportunities for rural labor force and also provides a stable employment environment for the return of labor force[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. To sum up, the digital technological advantages of the digital inclusive finance institute can effectively improve the breadth and depth of financial coverage in rural areas, and directly affect micro-entities such as farmers and agricultural enterprises to improve their financial availability. It promotes rural population transfer, agricultural mechanization and farmers' entrepreneurial behavior, and indirectly creates favorable conditions for rural land transfer. It can be seen that digital inclusive finance is a key factor to promote rural land transfer. Only studies on the mechanism of digital inclusive finance affecting rural land transfer are mainly discussed from the micro perspective of financial services and financial literacy, focusing on the direct impact of digital inclusive finance on rural land transfer, and lack of mechanism analysis based on the macro level. This paper intends to sort out the logical route of digital inclusive finance's impact on agricultural production factors and thus on rural land transfer, re-examine the main influencing factors of rural land transfer based on the macro level, and conduct an empirical study on the direct, indirect and spatial spillover effects of digital inclusive finance's promotion of rural land transfer. Finally, Put forward important measures to promote rural land transfer and countermeasures and suggestions to play the supporting role of digital inclusive finance.\u003c/p\u003e \u003cp\u003eThe marginal contribution and innovation of this paper have two aspects: First, build a theoretical framework of digital inclusive finance's impact on rural land transfer, discuss its direct role, spatial spillover effect and intermediary mechanism, highlight the direct and indirect action mechanism of digital inclusive finance in promoting rural land transfer, so as to better understand the supporting potential of digital inclusive finance in promoting rural land transfer. To provide new ideas for improving the rural land transfer factor market; Second, this paper retested the influencing factors of rural land transfer from a macro perspective, supplemented the limitations of existing studies in the research perspective, adopted instrumental variable method and dynamic spatial Durbin model to control the endogeneity of the model, conducted robustness test and heterogeneity test, and finally combined causality analysis and stepwise regression to verify the assumed intermediary mechanism. To ensure the reliability of the empirical results, and provide a factual basis for further exploring the important role of digital inclusive finance in rural reform and innovation.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2. Theoretical analysis and research hypothesis","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. The direct impact of digital inclusive finance on rural land transfer\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the process of rural land transfer, while digital inclusive finance provides financial support for land transferers, the development of digital trading platforms reduces the transaction costs of land transfer[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Based on the analysis of farmers' intention and ability of land transfer, digital inclusive finance establishes a farmer's credit evaluation system and lowers the threshold for farmers and agricultural production organizations to obtain financial capital. With the advantage of digital technology, it improves the scope of financial services and provides a new way for the information collection channel of land transfer market, making it more convenient for land transferers to obtain agricultural funds and land transaction information, thus enhancing their willingness to transfer to land. For land transferers, the financial information and services provided by digital inclusive finance improve farmers' financial literacy and make them more willing to transfer part of their land, engage in non-agriculture, and obtain property income and wage income. In terms of enhancing the ability of rural land transfer, digital inclusive finance provides financial support for farmers, so that the land transfer party has sufficient agricultural funds to expand the planting area, and rural land is guaranteed by the financial guarantee of digital inclusive finance The enhanced transaction capacity of land transfer market is of great significance for promoting the appropriate scale operation of agriculture and supporting the development of rural industries[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In general, digital inclusive finance has played a positive role in promoting rural land transfer.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 1\u003c/strong\u003e \u003cp\u003eDigital inclusive finance has a positive impact on rural land transfer.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eChina's digital inclusive finance has typical convergence characteristics and positive agglomeration spatial effect, which indirectly produces spillover effects on other related provinces mainly through facilitating mobile payment, expanding credit and improving insurance and other ways[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The spillover effect is mainly manifested in three aspects: First, the diffusion effect. Compared with the traditional financial model, digital inclusive finance has obvious technical advantages, and digital information technology can cover rural areas faster, more extensively and more accurately. On the one hand, digital inclusive finance spreads from the urban center to the surrounding towns and villages, driving the development of local rural areas. It spreads from areas with economic development advantages to backward areas and drives the economic development of surrounding regions. The second is the agglomeration effect. Digital inclusive finance can promote the agglomeration effect of agricultural industry through financial support, technical support and talent support [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Digital inclusive finance first takes effect in economically developed areas, promoting non-agricultural employment of the local rural population and promoting the agglomeration effect of large-scale agricultural operation, which is conducive to the upgrading of rural industries and the incubation of new industries. Third, mutual feed effect [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Digital inclusive finance improves the financial literacy of rural residents, and various regions and departments can exchange and learn from each other through digital platforms in a timely manner to absorb advanced development experience, thus realizing knowledge sharing and coordinated development.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 2\u003c/strong\u003e \u003cp\u003eDigital financial inclusion has a spatial spillover effect.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Indirect effects of digital inclusive finance on rural land transfer\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. The intermediary effect of rural labor force\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eRural land transfer is affected by the employment structure and age structure of rural labor force. The employment modes of rural labor force in China can be divided into pure agriculture, part-time employment and non-agriculture. Farmers who are fully engaged in agricultural production have a strong demand for land transfer and hope to acquire more land to produce scale effect. The attitude of part-time farmers towards land transfer depends on the local employment environment. In a good employment environment, part-time farmers tend to engage in non-agriculture and transfer most of their land out. Those who are fully engaged in non-agricultural farming do not want their land to be abandoned, but are more willing to transfer their land and get land rent. In terms of age structure, the young and middle-aged rural labor force mainly obtains income through non-agriculture, while the old farmers have no desire to expand their business by transferring to land due to labor force limitation. Digital inclusive finance has an impact on the employment mode of rural labor[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. On the one hand, financial support for large agricultural households enhances their willingness and ability to transfer land, and at the same time, it creates a better employment environment for part-time farmers and enhances their willingness to transfer land. On the other hand, the financial products and pension insurance provided by digital inclusive finance can provide more choices for the old-age lifestyle of the rural elderly labor force, so that some elderly farmers can completely give up or reduce agricultural activities and transfer the remaining land. In addition, digital inclusive finance supports the development of rural industries, promotes the upgrading of rural industrial structure, generates more rural employment opportunities, and thus attracts the return of rural labor force [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, this part of the returned rural labor force is accustomed to non-agricultural production and continues to choose rural nonagricultural employment in rural areas. However, it has no significant impact on land circulation. In short, digital inclusive finance is conducive to non-agricultural employment of rural labor force and indirectly promotes rural land transfer, while digital inclusive finance is conducive to the return of rural labor force, which is shown in the following aspects in terms of the number of rural labor force: Digital inclusive finance promotes the increase of the total rural labor force and promotes non-agricultural employment of rural households, thus playing a positive role in rural land transfer[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 3\u003c/strong\u003e \u003cp\u003eThe rural labor force plays an intermediary role in the process of digital inclusive finance affecting land transfer.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. The intermediary effect of agricultural mechanization\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eRural land transfer is closely related to the transformation of agricultural production mode. Traditional agriculture mainly relies on agricultural population, and if the expansion of agricultural operation scale requires more agricultural labor force, there are defects in factor allocation, supervision and prevention of natural risks, and the production efficiency is low. Agricultural mechanization makes up for the deficiency of traditional agriculture in terms of production efficiency, and the allocation of production factors is more reasonable, the timeliness of agricultural production is stronger, and natural risks can be effectively avoided, which makes large agricultural households more willing to expand production and obtain economies of scale. The replacement of labor force by mechanical action promotes the transfer of part of rural labor force to non-agricultural sectors, thus generating surplus land for large agricultural households to expand production scale. Agricultural mechanization enhances the land transfer willingness of both the land transfer party and the land transfer party. The impact of digital inclusive finance on agricultural mechanization is mainly in the two aspects of agricultural machinery holdings and agricultural machinery services. For large agricultural households, The purchase of agricultural machinery is conducive to improving production efficiency, and the financial support provided by digital inclusive finance improves the ability of farmers to purchase agricultural machinery; Some farmers choose agricultural machinery services out of consideration of economic applicability. Digital inclusive finance plays a role in providing financial and technical support to local agricultural machinery enterprises, which promotes the agricultural machinery service market to serve farmers efficiently [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Digital inclusive finance promoted agricultural mechanization and indirectly promoted rural land transfer[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 4\u003c/strong\u003e \u003cp\u003eAgricultural mechanization plays an intermediary role in the process of digital inclusive finance affecting land transfer.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. The mediating effect of agricultural infrastructure\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFor a long time, land fragmentation is the main factor restricting the transfer of rural land. In agricultural large-scale production, land fragmentation causes obstacles to all aspects of production, such as land ploughing, planting, management and protection, and harvest. Agricultural infrastructure includes water conservancy facilities, transportation facilities and other aspects[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. While agricultural water conservancy facilities facilitate agricultural water conservancy irrigation, land fragmentation is somewhat alleviated. On the one hand, agricultural infrastructure promotes land agglomeration, which is conducive to large-scale production after land transfer; on the other hand, agricultural infrastructure facilitates agricultural production, reduces part of the production cost of large agricultural households in the process of production and management, and enhances farmers' willingness to transfer to land[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Funds for agricultural infrastructure construction are mainly subsidized by the government or self-raised by rural collective economic organizations[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. China's agricultural infrastructure investment and financing has long been restricted by insufficient credit investment and immature financial system[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. By improving the medium and long-term credit mechanism of policy-based financial institutions and commercial financial institutions for rural infrastructure construction projects, giving full play to the digital advantages of digital inclusive finance, innovating medium and long-term credit products and models, and improving the supervision, assessment and evaluation mechanism of financial business, It is conducive to expanding effective investment in agriculture and rural areas, promoting the construction of agricultural infrastructure, and indirectly promoting the transfer of rural land[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Hypothesis 5. Agricultural infrastructure plays an intermediary role in the process of digital inclusive finance affecting land transfer.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Research and design","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Model setting\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn order to verify the above analysis, considering the spatial spillover or time lag of the influence of various influencing factors on rural land transfer, this paper constructs a dynamic spatial Durbin model to test the research hypothesis [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe Spatial Durbin model\u003c/b\u003e:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equ1\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$${Y_{i,t}}=\\lambda +\\sum\\limits_{k} {{\\alpha _k}{X_{i,t}}+\\varphi W{Y_{i,t}}+\\eta L \\cdot } W{Y_{i,t}}+\\sum\\limits_{k} {{\\beta _k}} W{X_{i,t}}+{\\sigma _{i,t}}$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn this paper, panel model (mixed effect, random effect, fixed effect), spatial Durbin model and dynamic spatial Durbin model were used to empirically test the influencing factors of rural land transfer. When φ, η and β in Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) are all 0, it is the basic panel model; When η is 0, formula (1) represents the static space Durbin model; When none of the coefficients is 0, formula (1) represents the dynamic spatial Durbin model. (1) In the formula \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Y}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e is the explained variable, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e is the explanatory variable, W is the geographical weight matrix, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\lambda\\:\\)\u003c/span\u003e\u003c/span\u003e is the constant term, α\u003csub\u003ek\u003c/sub\u003e is the regression coefficient of each explanatory variable, which directly reflects the influence degree of the explanatory variable on the explained variable; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{k}\\)\u003c/span\u003e\u003c/span\u003e is the regression coefficient of the interaction term between the weight matrix and the explanatory variable, indicating the spillover effect of the explanatory variable on the explained variable in the surrounding area; φ is the regression coefficient of the interaction term between the weight matrix and the explained variable; η is the time delay term of the interaction term between the weight matrix and the explained variable, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{i,t}\\)\u003c/span\u003e\u003c/span\u003eis the random disturbance term. In order to further analyze the mechanism of digital inclusive finance affecting rural land transfer, this paper mainly examines the intermediary effects of rural labor force, agricultural mechanization and agricultural infrastructure. In order to solve the deficiencies of causality tests in the process of step-to-step testing of intermediary effects, the author first based on the correlation evidence of causality demonstration in existing literature[39]. Then, through the stepwise method test, the intermediary effect of the above analysis is tested twice, in order to improve the credibility of the empirical process. In this paper, the spatial Durbin model is used to estimate the mediating effects.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMediation Effects model\u003c/b\u003e :\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equ2\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$${Y_{i,t}}={\\theta _1}+c\\ln dig+\\sum\\limits_{k} {{\\rho _k}Contro{l_{i,t}}+{\\sigma _{i,t}}}$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e \u003cdiv id=\"Equ3\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$${M_{i,t}}={\\theta _2}+\\alpha \\ln di{g_{i,t}}+\\sum\\limits_{k} {{\\rho _k}Contro{l_{i,t}}+{\\sigma _{i,t}}}$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e \u003cdiv id=\"Equ4\" class=\"Equation\"\u003e \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAccording to the previous analysis, it is necessary to examine the three intermediary paths in the process of digital inclusive finance affecting rural land transfer in turn. (2) To test the direct impact of digital inclusive finance on rural land transfer, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Y}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e is rural land transfer, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{i,t\\:}\\)\u003c/span\u003e\u003c/span\u003eis digital inclusive finance, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Control}_{i,t}\\:\\)\u003c/span\u003e\u003c/span\u003eis the control variable, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\rho\\:}_{k}\\)\u003c/span\u003e\u003c/span\u003e coefficient of each control variable, ɵ is the constant term, c is the coefficient of direct effect, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e is the random disturbance term; (3) Formula tests the influence of digital inclusive finance on the intermediary variables, where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{M}_{i,t}\\)\u003c/span\u003e\u003c/span\u003e and tare the intermediary variables, namely rural labor force, agricultural mechanization and agricultural facilities, and a is the influence coefficient of digital inclusive finance on the intermediary variables; (4) Formula is the comprehensive impact of digital inclusive finance and intermediary variables on rural land transfer, c is the direct impact coefficient of digital inclusive finance on rural land transfer after controlling intermediary variables, and b is the impact coefficient of intermediary variables on rural land transfer. In this paper, the intermediation effect was tested using the intermediation test process defined by Baron and Kenny, and the pre-processing Variable was added to the model: The rural fixed asset investment and traffic level were taken as control variables to optimize the possible endogeneity problem in the model to a certain extent. The mediation effect size was measured by c-c\u0026lsquo;.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Variable description\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis paper aims to study the internal mechanism of digital inclusive finance affecting rural land transfer. The explained variable is rural land transfer, measured by the total area of household contracted arable land transfer, the core explanatory variable is digital inclusive finance, measured by digital inclusive finance index, and the intermediary variables are rural labor force, agricultural mechanization, and agricultural facilities, respectively. The control variables are fixed asset investment, pension insurance and transportation level of rural households. In order to eliminate possible endogenous problems in the model, financial digitalization is selected as the instrumental variable. Logarithmic processing was carried out for each indicator, and the processing process of the indicator was shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariable selection and index processing.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSymbols\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIndicator processing\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepenent variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLand flow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elnflc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eln Total area of Cultivated land under household contract (mu)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMediating variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural labor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elnfrl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of rural employed in ln (10,000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgricultural mechanization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elnfam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal power of ln agricultural machinery (thousand kilowatts)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgricultural facilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elnfaf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEffective irrigated area in ln (thousand hectares)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndependent variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDigital finance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elndig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eln Digital Financial Inclusion Index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eControl variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndowment insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elnfei\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eln Number of urban and rural residents enrolled in social pension insurance (10,000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvestment in fixed assets of agricultural households\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elnfha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eln Rural Household Fixed Asset Investment Completion (billions of dollars)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTransportation levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elntla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal length of ln postal routes (km)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstrumental variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDigitization of finance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003elndis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLn Financial Inclusion Digitalisation Index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics result.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSymbols\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eObs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStd.Dev\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLand transfer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elnflc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.839\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital finance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elndig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural labor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elnfrl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.419\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanization of agriculture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elnfam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.499\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInvestment in fixed assets of agricultural households\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elnfha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.874\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarm facilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elnfaf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.729\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePension insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elnfei\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.567\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransportation levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elntla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e12.275\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigitization of finance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elndis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.136\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Analysis of empirical results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.1. basic regression analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on the basic panel model of formula (1), basic regression analysis was conducted to empirically test the main influencing factors of rural land transfer from the macro level. The data used for each variable passed the LLC test and IPS test, showing stable panel data. The regression results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Hausman test confirmed the selection of fixed effect model for estimation, and the result (1) is the estimation result of individual fixed effect. The results show that: digital inclusive finance and rural labor have a significant positive effect on rural land transfer; Rural households' investment in fixed assets has a significant negative impact on rural land transfer. The results of basic regression are basically consistent with theoretical analysis: the development of digital inclusive finance, rural labor force and agricultural infrastructure in China is conducive to rural land transfer, among which digital inclusive finance and agricultural infrastructure have positive effects on farmers' land transfer ability and transfer intention, while rural labor force and agricultural mechanization mainly affect farmers' land transfer intention. Fixed asset investment of rural households consumes agricultural funds to a certain extent, and does not have a positive effect on the intention of land transfer of rural households, which is manifested as restriction of land transfer.4.1.1. Endogeneity test\u003c/p\u003e \u003cp\u003eFor further analysis, in order to better identify the relationship between digital inclusive finance and rural land transfer and eliminate possible endogeneity problems, this paper further constructed instrumental variables to re-estimate the model. In relevant studies, many scholars used Internet penetration rate as the instrumental variable of digital inclusive finance[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Some scholars also constructed \"digital technology application index\" as an instrumental variable of digital inclusive finance [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In this paper, \"Digitalization degree\" published in 2011\u0026ndash;2020 Peking University Digital Financial Inclusion Index (PKU-DFIIC) is selected to represent the level of financial digitalization as an instrumental variable of digital financial inclusion. This index is measured by the four dimensions of mobility, affordability, credit and facilitation [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. On the one hand, the development of digital inclusive finance benefits from the extensive penetration of digital information technology, while the level of financial digitalization reflects the public's application level of digital technology and the diffusion and popularity of information technology among residents. Therefore, there is a close relationship between the two; On the other hand, after controlling a series of relevant variables, there is no direct correlation channel between the level of financial digitalization and rural land transfer. Therefore, it is valid to select the level of financial digitalization as an instrumental variable in this paper. Result (2) is the estimation result of 2SLS after adding the instrumental variables, and the positive and negative and significance of the estimation results of each variable are basically consistent with that of result (1). Meanwhile, the Hausman test shows that the original model has no endogeneity problem, and the difference is that agricultural infrastructure has a positive impact on rural land transfer at the confidence level of 10%.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic regression results of influencing factors of rural land circulation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOLS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2SLS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2SLS(Missing variables)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elndig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.387***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.358***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.367***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(14.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(10.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(10.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfrl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.112***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.122***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.121***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(4.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4.72)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e-0.0915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0805\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(-1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-1.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0916*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e-0.0949**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0955**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(-1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-2.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfaf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.246*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.260*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfei\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e-0.0423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0369\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(-0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-0.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elntla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.211**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.241***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.248***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(2.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(2.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(2.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.110*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-1.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.8293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7489\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual fixation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime fixed effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverrecognition test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHausman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.9359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8904\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst stage F number\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e78.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eThe symbols *, **, and *** indicate significant at 1%, 5%, and 10% confidence levels, respectively\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e4.1.2. Robustness test\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eResult (3) is a robustness test. 2SLS estimation is performed by adding possible missing variables (the number of enterprises on the gauge). The positive and negative values and significance of result (3) are consistent with those of model (2), that is, the model passes the robustness test. The fitting degree of model (2) is higher than that of model (3), and instrumental variables are added on the basis of model (1) to eliminate the endogeneity problem. Therefore, the estimated results of model (2) are selected for analysis. This paper explains the regression results as follows: The development of digital inclusive finance provides capital guarantee and technical support of transaction information channel for land transfer, enhances the transfer ability of land transfer party, and enhances the transfer willingness of land transfer party, which is conducive to rural land transfer. It is worth noting that the measurement of the variable of rural labor force in this paper is reflected by the number of rural employees, rather than the number of agricultural labor force, which can more intuitively analyze the impact of changes in rural labor force on rural land transfer. Rural employment can be divided into agricultural, non-agricultural and part-time employment. Some studies have suggested that non-agricultural employment is beneficial to land transfer[43], while the preliminary regression results of this paper show that rural labor is beneficial to land transfer, and the two are not in conflict, which is closely related to the employment structure and age structure of rural labor force. At present, the number of rural labor force is on the rise. This phenomenon is mainly caused by the return of the migrant labor force[44]. These returning rural labor force are accustomed to non-agricultural production, and considering the rarity of agricultural production technology and the current situation of low income in agricultural production, their employment mode is often part-time. Part-time farmers can obtain higher income. Under the driving effect of returning farmers on rural part-time employment, more small farmers accelerate land transfer. Thus, at this stage, the promotion effect of increasing the number of rural labor force on rural land transfer is essentially the driving effect of rural labor return on rural industry and the demonstration role of part-time employment. The dual effect has a positive impact on land transfer. The substitution effect of agricultural mechanization on agricultural labor force is conducive to the production of economies of scale in agricultural scale operation, which is conducive to the willingness of large agricultural households to expand the operation area. At the same time, due to the extrusion effect of agricultural machinery on agricultural surplus labor force, the non-agricultural employment of rural labor force is accelerated. These farmers who are engaged in non-agricultural employment are more likely to transfer their land out. However, due to the influence of topographic factors, regional heterogeneity makes the estimated impact of agricultural mechanization on rural land transfer biased to a certain extent, thus showing no significant effect.\u003c/p\u003e \u003cp\u003eThe development of rural infrastructure has integrated fragmented land into plots, guaranteed the efficiency of large-scale agricultural production and management, and enhanced the willingness of large agricultural households to transfer to land. The fixed assets investment of rural households is the capital for agricultural production and operation of rural households produce consumption, is not conducive to farmers into the land; As for the land transfer side, farmers' pension insurance does not reduce its dependence on the function of rural residents' land pension, and their willingness to transfer out of land does not increase.4.1.3. Heterogeneity test There is a big difference between the level of regional economic development and agricultural modernization in China. In order to further analyze the influencing factors of rural land transfer in different regions, 31 provinces were divided into eastern regions, central regions and western regions according to the statistical caliber of the National Bureau of Statistics, regional heterogeneity test was conducted, and 2SLS adding instrumental variables was selected for estimation (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In the eastern region, digital inclusive finance and rural labor force have a positive effect on rural land transfer, while agricultural mechanization inhibits rural land transfer. The explanation of this paper is as follows: In the eastern region of China, the mechanization level of agricultural machinery is higher, and the transportation is developed, and the agricultural mechanization service market is ahead of the central and western regions. Convenient agricultural machinery service brings more choices for the agricultural production mode in the eastern region, such as the agricultural trusteeship mode, which does not produce land transfer, but makes non-agricultural farmers have the willingness to recover land and increase agricultural operating income. In the central region, digital inclusive finance and agricultural mechanization have a positive impact on rural land transfer, while rural household pension insurance is not conducive to land transfer, and the impact of rural labor force on rural land transfer is not significant. The explanation is as follows: the economic level and agricultural modernization level in the central region are relatively high. Digital inclusive finance and agricultural mechanization enhance the ability and willingness of farmers to transfer land from the role of financial support and labor substitution respectively. The consumption of agricultural funds by farmers' pension insurance inhibits rural land transfer; The rural labor force in the central region also shows a growing trend, but due to the restriction of economic development level in the central region, its township industry is still in the initial stage and provides few rural non-agricultural jobs, resulting in the return of rural labor force has no significant impact on land transfer.\u003c/p\u003e \u003cp\u003eIn the western region, digital inclusive finance and agricultural infrastructure accelerate the process of rural land transfer, and the impact of rural labor force and agricultural mechanization on rural land transfer is not significant. The explanation of this paper is as follows: Affected by topographic factors and economic level, the level of agricultural modernization in western China is not high[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The development of digital inclusive finance provides funds and technical support for farmers. Meanwhile, the construction of agricultural infrastructure improves agricultural production efficiency and is conducive to rural land transfer; The western region is sparsely populated and the rural labor force is scarce, showing a trend of decreasing rural labor force in general. Farmers who go out to engage in non-agricultural activities are affected by the land situation and hope to transfer their land; However, there are more mountainous areas in the western region, and the production efficiency of small agricultural machinery suitable for mountainous areas is low. It is difficult for large agricultural households left in rural areas to expand their production and management area, resulting in the phenomenon that rural farmers do not want the land to be abandoned and are willing to give up the right to use the land free of charge. This process has no positive effect on land transfer. In the western region, agricultural mechanization is limited by geographical conditions, which has limited effect on the improvement of agricultural production efficiency, and has no obvious effect on the growth of the ability and willingness of large agricultural households to expand production and management area.\u003c/p\u003e \u003cp\u003eIn conclusion, pratt \u0026amp;whitney financial to the positive role of rural land circulation is not subject to regional restriction (hypothesis \u003cspan refid=\"FPar1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The impact of agricultural mechanization on rural land transfer is different in the eastern and western regions. For the eastern region, the rapid development of agricultural mechanization has promoted the smooth operation of the agricultural machinery service market and the land trustement model, and made farmers in the eastern region hope to recover the transferred land in order to obtain more agricultural productive income, which shows that the development of agricultural mechanization is not conducive to land transfer. For the western region, the effect of agricultural mechanization on the improvement of agricultural production efficiency in the mountainous environment is not good, and it is difficult to improve the willingness of large agricultural households to transfer to land. It is worth noting that only the increase of rural labor force in the eastern region has a positive effect on rural land transfer. It also indicates that the return of rural labor force in the eastern region has sufficient rural non-agricultural jobs, and drives local farmers to engage in non-agriculture, which is conducive to farmers' willingness to transfer out of land. Agricultural infrastructure in western China has a significant positive impact on rural land transfer industry, and the land in less developed areas is more dispersed and less contiguity, so strengthening the construction of agricultural infrastructure is the focus of promoting rural land transfer in western China.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis results of regional heterogeneity of influencing factors of rural land transfer.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEast\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elndig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.256***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.537***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.384***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(7.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(8.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfrl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.146**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0524\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.452***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.221**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-2.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-1.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.154**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0910\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-0.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfaf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.833***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-0.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfei\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.657***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0697\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-3.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elntla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.819***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.597***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0820\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(3.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-0.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.562\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-0.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual fixation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime fixed effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverrecognition test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHausman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9994\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst stage F number\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eThe symbols *, **, and *** indicate significant at 1%, 5%, and 10% confidence levels, respectively\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Spatial econometric analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe spatial correlation test of the core explanatory variable digital financial inclusion is shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. As measured by Moran Index, Moran 's I is between 0.105 and 0.155, all of which are significant under 1% confidence interval. There is positive spatial dependence of digital financial inclusion in all regions, and the spatial correlation is increasing year by year. The above analysis further shows that digital inclusive finance has the characteristics of spatial agglomeration, so the analysis of the impact mechanism of digital inclusive finance on rural land transfer needs to consider the spatial spillover effect.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003epratt \u0026amp;whitney financial global correlation test results (geographic weighting matrix).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eDigital Universal Finance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eDigital Universal Finance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMoran΄s I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMoran΄s I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e4.2.1. Spatial model selection\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn this paper, the optimal spatial measurement model is selected through LM test, LR test, Wald test, Hausman test and other diagnostic tests, and the results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. LM test is significant in geographical weight matrix, economic weight matrix and economic geography nested weight matrix, indicating the existence of spatial effects; Both LR test and Wald test show that spatial Durbin model (SDM) has stronger explanatory power than spatial lag model (SAR) and spatial error model (SEM). According to the Hausman test, if the model chooses geographic weight matrix or economic weight matrix, the fixed effects estimation should be used; if the model chooses economic geography nested weight matrix, the random effects estimation should be used. When geographical weight matrix and economic weight matrix are selected in this paper, the fixed effects estimation of spatial Durbin model (SDM) is carried out. The random effects of spatial Durbin model (SDM) are estimated when economic geography nested weight matrix is selected. Considering that there is time lag in the influence of explanatory variables on rural land circulation, the time and space lag term is added to the model, and finally the static spatial Durbin model and dynamic spatial Durbin model with fixed time and space are selected for estimation.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of relevant diagnostic tests for spatial model selection (divided by weight matrix).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight Matrix\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eGeographic Matrix\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eEconomic Matrix\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eEconomic Geography nested matrix\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTATISTICS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTest results\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTest results\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTest results\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLMERR test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e375.365***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e383.358***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e194.434***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM(Robust)ERR test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e271.563***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e273.881***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e122.417***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLMLAG test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120.035***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e124.418***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88.790***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM(Robust)LAG test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.233***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.941***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.864***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLR Test ERR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.32***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.61***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.45**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0307\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLR Test LAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.45***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.25***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.37**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWald Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.57***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.28***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.65**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0247\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHausman test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.75***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.18**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.6264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e4.2.2. Dynamic spatial Durbin model\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis article selects the space durbin test in the influence factors of rural land circulation, the regression results in Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Result (7) is the estimation result of the static spatial Durbin model under the geographical weight matrix. The results show that digital inclusive finance, rural labor force, agricultural mechanization and agricultural facilities have significant positive impacts on rural land transfer; Rural household fixed asset investment and pension insurance have a significant negative impact on rural land transfer. Digital inclusive finance gives financial support to land transfer transferers, which directly promotes rural land transfer. The return of rural labor force accelerates the development of rural industry, and enhances the willingness of the land transfer party under the role of higher nonagricultural income. By changing the mode of agricultural production, agricultural mechanization makes it possible for farmers to further expand the scale of agricultural operation. The development of agricultural facilities is conducive to the contiguity of land and enhances the willingness of land transferers to expand the scale of agricultural operation. On the other hand, fixed asset investment and pension insurance of rural households consume their funds to a certain extent, and the total amount of funds used for agricultural production and operation decreases, which has a negative effect on rural land transfer. Results (8) and (9) are the estimates of static spatial Durbin model under the economic weight matrix and economic geographic weight matrix respectively. The estimated results are basically consistent with those of (7), that is, through the robustness test, the static spatial Durbin model of economic weight matrix is selected as the best fit among the three weight matrices.\u003c/p\u003e \u003cp\u003eExist in the process of considering the influence of time lag, joined by variable time lag of rural land circulation, dynamic space durbin test model. Results(10) are estimated by the dynamic spatial Durbin model under the geographical weight matrix. The regression results show that: the influence coefficient of digital inclusive finance and agricultural infrastructure construction on rural land transfer increases, showing a significant positive effect; Rural labor force for the promotion of rural land circulation effect decreased; The influence coefficient of agricultural mechanization on rural land transfer is basically unchanged;The obstructing effect of fixed asset investment of peasant households on rural land transfer is increasing, while the influence of peasant household pension insurance on rural land transfer is not significant. The above results can be explained as follows: Digital inclusive finance can provide long-term stable financial support for rural households, and agricultural infrastructure is beneficial to the improvement of agricultural production efficiency in the long run, so both digital inclusive finance and agricultural infrastructure have a positive impact on rural land transfer in the long run; The promotion effect of rural labor force growth on rural land transfer is mainly guided by non-agricultural employment of returning farmers, and in the long run, non-agricultural employment opportunities in rural areas tend to be saturated, thus reducing the promotion effect on rural land transfer. Investment in fixed assets of rural households is a large expenditure for rural households. In the long term after investment in fixed assets, rural households will face the dilemma of tight funds or even debts, and their ability to transfer to land will decline, thus increasing the hindrance to rural land transfer in the long term. Models (11) and (12) are the dynamic spatial Durbin mode estimation under the economic weight matrix and the economic geographic weight matrix respectively. The regression results are basically consistent with those of (10), and the spatial-temporal lag terms of the explained variables are significant, among which the geographical weight matrix has the highest degree of fit.The analysis of spatial spillover effects in the following paper mainly focuses on the estimation results under the geographical weight matrix.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimation results of spatial Durbin model.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eStatic space Durbin model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eDynamic spatial Durbin model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResult weig\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(11)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(12)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eht matrix\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeography\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEconomy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEconomic Geography\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGeography\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEconomy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEconomic Geography\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elndig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.472**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.476**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.721**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.814**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.106**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(2.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(2.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(2.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfrl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.181***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.166***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.190***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0731*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.186***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(5.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(5.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.441***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.362***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.537***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.446***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.371***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.615***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(4.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(3.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(5.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.459***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.411***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.304***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.767***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.614***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.337***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-7.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-6.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-5.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-10.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-9.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-5.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfaf\u003c/p\u003e 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align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(8.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(8.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(4.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfei\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.242***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.226**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.195**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e 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align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.441***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.640***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.645***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.348***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(8.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(8.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(5.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(9.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(9.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(4.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL.W. lndig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-6.098***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.856***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.350***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-10.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-8.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-3.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eW.lndig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.498*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.166*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(1.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eW.lnfrl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.788***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.283***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.479*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.816***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.386**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.429**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(2.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(2.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(2.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(2.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eW.lnfam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.097***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.886***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.567***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-1.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-2.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(4.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(3.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eW.lnfha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.212***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.477***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.366***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.103***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.285***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-4.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-8.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-3.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-4.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-3.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eW.lnfaf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.513***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.127***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.069***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.682***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.757***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.499\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(9.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(8.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-3.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-0.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eW.lnfei\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.148***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.650***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.540***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.634***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.577\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-4.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-4.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-3.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-5.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eW.lntla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.804***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.867***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.483***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.636***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.196***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(6.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(9.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(4.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(7.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-2.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-0.68)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003erho\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.779**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.566**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0217\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-2.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-2.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-0.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esigma2_e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.158***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.168***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.187***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.148***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.161***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.198***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(12.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(12.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(12.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(13.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(13.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(13.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.6145\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eThe symbols *, **, and *** indicate significant at 1%, 5%, and 10% confidence levels, respectively\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e4.2.3. Spatial spillover effect analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eRegarding the spillover effects of each influencing factor, the spillover effects of the regression results (7) of static spatial Durbin model and the regression results (10) of dynamic spatial Durbin model under the geographical weight matrix were analyzed respectively. The results showed that the pratt \u0026amp;whitney financial to surrounding areas of rural land circulation in long-term significant positive spillover effect, assumption 2 certificate; Rural labor force and agricultural infrastructure have significant spillover effects on the surrounding areas; The spillover effect of peasant household pension insurance on the surrounding areas is a significant negative effect. The explanation of this paper is as follows: The spillover effect of digital inclusive finance is mainly generated by its diffusion effect on rural finance and industrial economy in the surrounding areas, in addition, it also includes the learning effect of financial institutions in the surrounding areas to the developed areas of digital inclusive finance. The spillover effect of rural labor force and agricultural infrastructure is mainly due to its support for the development of rural industries, forming a demonstration effect, speeding up the development of rural industries in the surrounding areas, and thus promoting the transfer of rural land in the surrounding areas.However, in the previous analysis, peasant household pension insurance is not conducive to rural land transfer. Its demonstration effect drives farmers in the surrounding areas to attach importance to the pension insurance, and thus produces negative spillover effects on rural land transfer in the surrounding areas. As different geographical conditions have a great influence on the spillover effect of agricultural mechanization, the geographical weight matrix constructed by latitude and longitude alone cannot reflect its real spillover effect well. The spillover effect of agricultural mechanization can be obtained from the estimation result (11) of the dynamic spatial Durbin model under the economic weight matrix, showing a significant positive spillover effect. There are two main reasons for this. The first is the learning effect of the surrounding areas to the developed areas of agricultural mechanization; the second is the diffusion effect of agricultural machinery services in the developed areas of agricultural mechanization to the surrounding areas, which improves the operation capacity of agricultural machinery in the surrounding areas, and thus produces a positive spillover effect on the land transfer in the surrounding areas.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e4.2.4. Decomposition of spatial effect\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe decomposition of spillover effects in this paper is shown in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. Direct effects represent the direct impact of a certain explanatory variable on rural land circulation in the local region, including the impact of the explanatory variable on neighboring areas and the effect on the local region (feedback effect). Indirect effects represent proximity the indirect effect of a regional explanatory variable on rural land circulation in the region; Total effect represents the average influence of an explanatory variable in a certain region on rural land transfer in all regions. According to the model fitting effect, this paper selects the estimated results under the geographical weight matrix to analyze the long-term and short-term effects of the spillover effect decomposition respectively.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimation results of spatial Durbin model.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eLong term\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eShort term\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDirect effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpillover effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal Effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDirect effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpillover effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal Effect\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elndig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.486**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.723**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(2.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(2.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfrl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.161***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.395**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.556***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0834*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.443**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.526**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(2.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(2.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(2.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.496***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.977*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.441***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-1.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-0.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.411***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.124***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.535***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.786***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-5.024**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-5.810**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-7.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-3.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-4.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-7.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-2.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-2.57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfaf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.457***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.835***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.292***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.731***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.16**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.89**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(4.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(3.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(2.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(2.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfei\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.158*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.785***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.943***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.126**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.281**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-1.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-3.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-3.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-2.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-2.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elntla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.482***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.026***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.508***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.670***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.644**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.313**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(6.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(4.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(5.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(2.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(2.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eThe symbols *, **, and *** indicate significant at 1%, 5%, and 10% confidence levels, respectively\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the long run, rural land transfer is directly and positively affected by the rural labor force and agricultural infrastructure in the region, and its indirect effect and total effect are significantly positive, indicating that the change of rural labor force and the development of agricultural infrastructure are conducive to rural land transfer in the long run, and show a good spatial spillover effect. Pratt \u0026amp;whitney financial and agricultural mechanization of rural land circulation, there is only direct effects of its spatial spillover effect is not obvious, the reason is that pratt \u0026amp;whitney financial barriers, exists between regional financial services for the spread of the surrounding area effect is not strong; Agricultural mechanization is limited by geographical factors, and it is difficult for agricultural machinery technology and agricultural machinery services to exert diffusion effect.\u003c/p\u003e \u003cp\u003eIn the short term, rural labor force and agricultural infrastructure also have direct effects and spillover effects on rural land transfer. From the analysis of impact coefficient, the direct impact of rural labor force is stronger in the long term, while the direct effect of agricultural infrastructure is more obvious in the short term.However, the spillover effects of both on rural land transfer show a weakening trend in the long run. The direct and spillover effects of fixed assets investment and pension insurance of rural households on rural land transfer show significant negative effects in the long and short term, because the investment in fixed assets and the purchase of pension insurance of rural households restrict the expansion of production and management scale of rural households to a certain extent.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Intermediary effect analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAs for the testing process of intermediary effect, this paper mainly adopts the suggestion of Jiang Tian (2022) on the testing process of intermediary effect,focusing on the analysis of the causal relationship between intermediary variables and dependent variables, and re-tests the intermediary effect of rural labor force,agricultural mechanization and agricultural facilities in the process of digital inclusive finance affecting rural land transfer through the stepwise analysis method.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimation results of intermediary effect.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(14)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(15)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(16)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(17)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(18)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(19)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(20)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003elnflc\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003elnfrl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003elnflc\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003elnfam\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003elnflc\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003elnfaf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003elnflc\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elndig\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.432***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.461**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.413***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.242***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.429***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.140***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.365***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(4.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(3.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(4.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(3.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(4.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfrl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0806***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.197***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(2.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elnfaf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.506***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(5.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elntla\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.375***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.393***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.325***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.245***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.373***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.131***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.299***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(5.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(4.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(3.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(3.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(4.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-7.517**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-13.52*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-6.197*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-2.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-0.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(-1.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003erho\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.607***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.399***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.533***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.631***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.412***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.384***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.613***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(7.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(3.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(5.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(6.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(3.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(2.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(7.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elgt_theta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.879***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.169***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.887***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.049***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.680***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3.807***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.378***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-18.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(-13.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(-18.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-18.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-15.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-27.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(-13.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esigma2_e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0224***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.145***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0214***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0177***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0218***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00454***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0230***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(11.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(11.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(11.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(11.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(11.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(11.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(11.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eThe symbols *, **, and *** indicate significant at 1%, 5%, and 10% confidence levels, respectively\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAbout the intermediary variable and the discussion of the causal relationship of rural land circulation, academics have respectively demonstrates the rural labor force, agricultural infrastructure, agricultural mechanization,the positive role on the rural land circulation; About pratt \u0026amp;whitney financial directly impact on the rural land circulation, this paper USES space doberman model stepwise regression (Table \u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e), result (14) are consistent with previous argument by causality: pratt \u0026amp;whitney financial has significant positive effect on rural land circulation,49 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], influence coefficient c is 0.432; Results (15)(17) (19), respectively, for the rural labor force, agricultural mechanization, agricultural infrastructure directly impact on the rural land circulation, all show the positive influence[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan additionalcitationids=\"CR47 CR48\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. As for the causal relationship between digital inclusive finance and various intermediary variables, many scholars have conducted in-depth discussions on the causal relationship between digital inclusive finance and rural labor force, agricultural mechanization and agricultural infrastructure[\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].The stepwise method selected in this paper does not carry out a secondary test. The above analysis shows that rural labor force, agricultural mechanization and agricultural infrastructure have significant intermediary effects in the process of digital inclusive finance affecting rural land transfer.\u003c/p\u003e \u003cp\u003eIn order to further quantify the influence of the above three intermediary effects, the stepwise regression method is used to estimate. Results (16), (18) and(20) respectively show the comprehensive impact of digital inclusive finance and various intermediary variables on rural land transfer, and each influence coefficient is significant under 1% confidence interval, indicating that there is no masking effect, and the intermediary variables of rural labor force,agricultural mechanization and agricultural facilities have significant intermediary effects. Hypotheses 3, 4 and 5 are confirmed. In order of intensity, the mediating effects were agricultural infrastructure, rural labor force and agricultural mechanization. Explain about the mediation mechanism, this article as follows: one is the digital pratt \u0026amp;whitney finance by accelerating rural industry development produce more of the rural non-agricultural employment opportunities, make rural labor backflow can continue to non-agricultural, to a certain extent solved the rural labor force concerns about income home, and not competition existing agricultural land resource allocation; On the one hand, the rural labor force continues to expand the rural industry and provide more nonagricultural employment opportunities for farmers; on the other hand, it plays an exemplary role in driving the left-behind rural labor force and enhancing its willingness to transfer land out. Second, pratt \u0026amp;whitney financial funds for farmers through direct asset purchase of agricultural machinery, indirectly promote the development of agricultural machinery technology and market, promote the local agricultural mechanization level, to enhance agricultural large into land.Third, digital inclusive finance provides financial support for the construction of agricultural infrastructure, and the improvement of agricultural infrastructure is conducive to agricultural scale management, thus promoting farmers' land transfer.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions and countermeasures","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e5.1. Research Conclusion\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on basic regression analysis, regional heterogeneity analysis, spatial spillover effect analysis and intermediary mechanism analysis, this paper analyzes the action mechanism and regional heterogeneity of influencing factors of rural land transfer, as well as the intermediary effects of rural labor force, agricultural mechanization and agricultural infrastructure in the process of digital inclusive finance affecting rural land transfer in an all-round way. The main research conclusions are as follows:\u003c/p\u003e \u003cp\u003e(1) Digital inclusive finance is beneficial to rural land transfer. This positive effect is influenced by the regional economic level and agricultural modernization level, and the regional heterogeneity is stronger in the central region than in the western region and the western region than in the eastern region. Moreover, due to the existence of intangible barriers between regions in the development of digital inclusive finance in China, the spillover effect of digital inclusive finance on rural land transfer is weak. In this paper, it is only significant in the dynamic spatial Durbin model under the geographical weight matrix, indicating that digital inclusive finance can produce diffusion effect in the long run. The direct impact of digital inclusive finance on rural land transfer mainly depends on the enhancement of farmers' willingness to transfer to land by capital and technology. In addition,farmers' investment in fixed assets and rural old-age insurance consumes agricultural funds and hinders the process of rural land transfer. It can be inferred that rural old-age care still depends on the income from agricultural production and operation. The coverage of digital inclusive finance in rural production and life is insufficient.\u003c/p\u003e \u003cp\u003e(2) The causal relationship between intermediary variables and rural land circulation. The positive effect of rural labor force on rural land transfer is not restricted by region.At present, the increase in the number of rural labor force in China is mainly caused by the return of rural labor force. The author mainly analyzes the mechanism of its influence on rural land transfer from the perspective of the employment structure of rural labor force. On the other hand, the non-agricultural employment or entrepreneurial behavior of returning farmers can promote the development of rural industries, and at the same time, promote non-agricultural employment and concurrent employment in rural areas, and promote rural land transfer. The overall effect of agricultural mechanization on rural land transfer is promoting. However, due to the prevalence of agricultural machinery service and land trusteeship mode in eastern China, the higher the level of agricultural mechanization is, it is not conducive to farmers' willingness to transfer out of the land. The construction of agricultural infrastructure is conducive to enhancing the willingness of farmers to expand the scale of operation, and thus has a positive effect on rural land transfer.\u003c/p\u003e \u003cp\u003e(3) Digital inclusive finance -- intermediary variable -- the mechanism of rural land transfer. The intermediary mechanism of digital inclusive finance affecting rural land transfer is composed of agricultural infrastructure, rural labor force and agricultural mechanization, and its intermediary effect is decreasing. First, the implementation and construction of agricultural infrastructure developed rapidly with the financial support of digital inclusive finance, which enhanced the willingness of large agricultural households to expand the scale of agricultural production and operation; Second, the improvement of the rural non-agricultural employment environment by digital inclusive finance accelerates the return of rural labor force, and the employment structure of rural labor forces shifts to non-agricultural, forming a positive feedback effect on the development of rural industries. The trend of non-agricultural employment enhances the willingness of farmers to transfer land and promotes the transfer of rural land. Third, the development of agricultural mechanization depends on the financial support of digital inclusive finance for farmers and agricultural machinery market, and its role in improving agricultural production efficiency and substituting rural labor force enhances farmers' willingness to transfer to land.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e5.2. Countermeasure\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e(1) Expand the coverage of financial services for digital financial inclusion and remove regional barriers. Promote the breadth and depth of digital inclusive financial services,continue to guide financial institutions to use digital inclusive financial services to sink financial services, invest financial resources and services more comprehensively in rural production and life, and establish a sound digital credit evaluation system for the main links of agricultural production and important expenditures in rural life. To improve the coverage and availability of financial services for rural residents; Give full play to the digital technological advantages of digital inclusive finance, improve the mechanism for the formation of rural land transfer prices, establish a hierarchical coordination mechanism for financial institutions, and form a multi-level digital inclusive financial system. On the demand side of inclusive financial services, through the publicity of offline financial institutions and the popularization of digital financial platforms, improve the financial literacy of rural residents, promote the transformation of financial services into a \"buyer's market\", customize financial service products according to the needs of rural residents, such as credit, investment, wealth management, insurance and other aspects, and improve the depth of inclusive financial services. In addition, the geographical restrictions of digital financial inclusion should be weakened, its diffusion effect on surrounding areas should be enhanced, and the balanced development of digital financial inclusion should be promoted.\u003c/p\u003e \u003cp\u003e(2) Promote the development of rural industries and non-agricultural employment and entrepreneurship of returning farmers to form new quality productivity in rural areas.In areas with developed rural industries, we will strengthen rural industrial planning, focus on undertaking the transfer of non-agricultural industries, extend the agricultural industrial chain, and increase rural employment Carrying capacity can attract rural labor to return to their hometown for employment and entrepreneurship, further promote the development of rural industries,and form a virtuous circle of industrial agglomeration[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. In areas with underdeveloped rural industries, planning guidance and policy support should be strengthened, characteristic industries such as green agriculture, traditional handicraft industry and rural tourism should be developed according to local conditions, and financial resources and digital platforms of digital inclusive finance should be utilized to provide long-term and stable financial services for the initial stage of rural industrial development[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Finally, efforts should be made to enhance the income-increasing role of non-agricultural industries in rural areas, promote the appropriate scale operation of agricultural industries, strengthen the transformation of scientific and technological achievements and the introduction of talents in rural areas, improve the production level of rural industries, and form new quality productivity in rural areas.\u003c/p\u003e \u003cp\u003e(3) Raise the level of agricultural mechanization in the central and western regions and continue to strengthen agricultural infrastructure construction. Give full play to the role of digital universal benefit financial support for agricultural machinery and agricultural infrastructure, promote agricultural machinery and equipment suitable for the central and western regions,establish agricultural machinery operation service system, and enhance the radiation effect of agricultural production services on the surrounding areas; To promote the construction of high-standard farmland through rural infrastructure in irrigation, transportation and other aspects, is conducive to the popularization of agricultural mechanization and moderate scale management in the central and western regions. In addition, strengthening agricultural technology research and development and production mode innovation is an important way to improve agricultural production efficiency in the central and western regions. In terms of agricultural machinery technology, the coverage rate of agricultural machinery operation in the central and western regions can be improved from the aspects of agricultural machinery improvement and special crop machinery innovation, which is conducive to transforming agricultural production mode and speeding up the process of rural land transfer. To further promote the appropriate scale management of agriculture and the development of rural industries.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization, T.C.; methodology, software, investigation, and writing\u0026mdash;original draft preparation, T.C. and L.L.; writing\u0026mdash;review and editing, T.C. and L.L.; project administration, T.C.; funding acquisition, T.C. and L.L. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was funded by Research on 2023 Major Project of Philosophy and Social Science Research in Hubei Higher Education Institutions \u0026ldquo;Research on Digital Economy Empowering the Integration of Urban and Rural Development in Hubei Counties\u0026rdquo;(23ZD114)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The data generated in this study are described in Section 3; they are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The authors thank all research members who provided support and assistance in this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclaimer/Publisher\u0026rsquo;s Note:\u003c/strong\u003e The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChen S Analysis of Policy Performance and Influencing Factors of Land Transfer\u0026ndash;A Comparative Study Based on Three Places in East, Central and West China[J]. Social Sci ,2011,5,48\u0026ndash;56.[CrossRef]\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang Z, Wang P The role of digital inclusive finance in the development of digital agriculture[J]. 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[CrossRef]\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Digital financial inclusion, land transfer, dynamic spatial Durbin model, impact mechanisms","lastPublishedDoi":"10.21203/rs.3.rs-6736992/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6736992/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDigital inclusive finance provides financial capital and digital services for agricultural production, which has the necessary conditions to promote rural land transfer and improve the rural factor market. This paper constructs a theoretical analytical framework for the impact of digital financial inclusion on rural land transfer from both direct and indirect roles; adopts the dynamic spatial Durbin model to empirically test the hypothesized spillover effect and impact mechanism. The results indicate that: (1) digital inclusive finance facilitates rural land transfer and generates long-term spillover effects; (2)the mediating effects of agricultural infrastructure, rural labor force, and agricultural mechanization in the process of digital financial inclusion affecting rural land transfer are significant and decreasing in order; (3)the differences in the agricultural industrial base and geographic endowment in central and western China are the main factors that cause regional heterogeneity. Finally, we propose three suggestions to promote the moderate-scale operation of agriculture by expanding the coverage and service depth of digital inclusive finance, promoting the double aggregation of rural population and industry, and making up for the short boards of agricultural production in the western region.\u003c/p\u003e","manuscriptTitle":"The Impact of Digital Finance on Rural Land Transfer: Dynamic Spillover Effects and Mechanism Examination","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-19 10:13:36","doi":"10.21203/rs.3.rs-6736992/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"acde9814-2bd7-4f8e-bc8a-d16b7eb3628e","owner":[],"postedDate":"June 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-10T12:53:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-19 10:13:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6736992","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6736992","identity":"rs-6736992","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}