Organized Land Transfer and Improvement in Agricultural Land Allocation Efficiency: Effects and Mechanisms

Abstract

Against the backdrop of pervasive land fragmentation and high transaction costs, organized land transfer has emerged as a growing trend in China’s agricultural land market, facilitating the transition toward moderate-scale farming. Based on survey data from 1472 households across 72 villages in Jiangsu Province, this study investigates the impact of organized land transfer on agricultural land allocation efficiency and explores the underlying mechanisms. The results show that organized land transfer significantly enhances agricultural land allocation efficiency. This finding proves to be robust across a series of robustness analyses. Specifically, organized land transfer enhances land allocation efficiency, primarily by enhancing transfer stability, expanding the transfer scale, and broadening the transfer scope. Moreover, our analysis of moderating factors reveals that the strength of the village collective economy positively moderates the relationship between organized land transfer and efficiency, whereas lineage networks exert a negative moderating influence. Addressing equity implications, this study also examines the model’s impact on farmers’ autonomy. The findings indicate that organized land transfer significantly suppresses transfer willingness, particularly in those with low incomes and the elderly. These results carry significant policy implications: when promoting organized land transfer, it is crucial to balance the strengthening of village collectives’ intermediary role with robust regulatory frameworks designed to safeguard farmers’ land rights and autonomy.

1. Introduction

As a core policy instrument for deepening rural land reforms, agricultural land transfer undertakes critical responsibilities in optimizing agricultural land allocation, facilitating rural labor transition to non-farm sectors, and enhancing rural household livelihoods (agricultural land transfer refers to the process by which farmers or economic organizations with contracted land management rights transfer these contracted land management rights to others through legal forms, without changing the nature of land ownership and the agricultural use of the land) [1,2]. Like other developing countries such as Vietnam and India, China also grapples with persistent challenges of land fragmentation and the low productivity of smallholder farming. Driven by the dual forces of national policy mandates and grassroots institutional innovations, China’s agricultural land transfer market has expanded substantially. Official data from the China Rural Policy and Reform Statistical Yearbook (2022) reveals that the total area of land transfer in China increased from 109 million mu in 2008 to 557 million mu by the end of 2021 (1 mu = 667 m² or 0.667 ha). The extant literature confirms that a well-functioning agricultural land transfer market has been shown to direct land resources to more productive households and agribusinesses [3,4,5].

However, despite the rapid development of China’s agricultural land transfer market, its operational mechanisms are constrained by persistent structural bottlenecks, including short-term transfer durations, inadequate standardization, and an over-reliance on relational transactions [6]. These issues collectively impede further improvements in agricultural land resource allocation efficiency. Data from the 2017 China Household Finance Survey (CHFS) corroborates this, indicating that 67.7% of agricultural land transfer transactions occurred within kinship or village networks, and 64.6% of rural households used informal contracts. This evidence suggests that China’s agricultural land transfer market is characterized by a narrow transaction scope and unstable transactions, which inevitably hinder the optimal allocation and utilization of agricultural land resources [7]. These empirical observations are echoed in the scholarly literature. For instance, Gai et al. [8] argue that only land inflows significantly enhance allocation efficiency, whereas land outflows exhibit no statistically significant effect. Similarly, Shi et al. [9] assert that land transfer has a limited corrective effect on agricultural land allocation efficiency, primarily due to imperfections in the agricultural land transfer market mechanism. In this context, excessive reliance on laissez-faire market mechanisms is unlikely to lead to a reduction in the prevalence of informal transactions. Consequently, the challenge is to devise strategies that effectively reduce land market transaction costs, unlocking the latent potential of agricultural land transfer markets and thereby augmenting agricultural land allocation efficiency.

In the context of the nationwide “Rural Revitalization” strategy and supportive national policies, village collective-led organized land transfer has emerged as a crucial institutional practice to address the underdevelopment of standardized agricultural land transfer markets [10]. Unlike other developing countries, China’s unique collective ownership system provides an institutional foundation for land transfer. Local governments and village collectives in China have been permitted and encouraged to facilitate and formalize agricultural land transfer. Village collectives operate under a dual mandate: they function as agents of grassroots governance and as autonomous representatives of rural households’ interests. This dual role endows them with distinct advantages in structuring agricultural land transfer markets [11]. On the one hand, village collectives can mobilize administrative resources from higher-level governments to formalize land transfer transactions through official registry systems and digital trading platforms. On the other hand, by leveraging their embedded knowledge of intra-village social networks, they can coordinate fragmented smallholders to participate in collective land pooling, thereby mitigating information asymmetry and reducing transaction costs inherent in decentralized land markets [12,13]. This context gives rise to a critical research question: can the organized land transfer led by village collectives, as a novel solution, standardize market behaviors, alleviate frictions in land allocation, and ultimately improve allocative efficiency?

The literature on agricultural organized land transfer can be broadly categorized into two streams. The first stream focuses on the implementation preconditions and associated risks of organized land transfer within the context of agricultural modernization, typically taking the intervention conditions as the analytical starting point [14]. The second stream explores the multifaceted impacts of organized land transfer models, including per-unit yield [15], agricultural production efficiency [16], rural households’ livelihood capital [17], formalization of land transfer markets [12], and households’ income [18], from the perspective of intervention modalities. Despite this progress, significant research gaps remain. First, although existing literature has examined the resource allocation effects of land transfer, they only conduct analysis from a single dimension of villages through a simplistic binary approach of “whether a transfer occurred or not” [8], which fails to uncover the distinct institutional characteristics and impact mechanisms of organized land transfer as a specific model. Second, the current literature has yet to systematically investigate the potential equity effects of organized land transfer, particularly its differential impacts on various farmer groups.

Drawing on this background, this study utilizes survey data from Jiangsu Province to empirically examine the impact of organized land transfer on the allocative efficiency of agricultural land resources. We further investigate the underlying mechanisms and explore the impact of organized land transfer on farmers’ willingness to engage in the land market. This study makes twofold marginal contributions to the extant literature: First, it employs micro-level empirical analysis to delineate the specific mechanisms through which organized land transfer enhances agricultural land allocation efficiency, thereby complementing the current understanding of organized land transfer mechanisms. Second, this study simultaneously analyzes the efficiency and equity effects of organized land transfer, providing a new perspective for balancing efficiency and equity. This study offers valuable policy implications for rural governance, agricultural-scale operations, and village differentiation, which can be applied to rural communities in other countries with similar socioeconomic differentiation.

The remainder of this study is arranged as follows: Section 2 analyzes the effect of organized land transfer on agricultural land allocation efficiency from the view of transaction costs and concludes the theoretical hypothesis. Section 3 presents the data, the variables, and the estimation strategy. The econometric results are presented in Section 4. Section 5 further examines the equity effects of organized land transfer. Section 6 is the discussion, presenting the main findings and the limitations of this study. Finally, Section 7 concludes this study.

2. Theoretical Basis and Research Hypothesis

According to transaction cost economics (TCE), pioneered by Coase [19], all economic transactions can be systematically deconstructed. This theory provides a foundation for analyzing transaction costs in agricultural land transfer. In the context of agricultural land transfer, transaction costs typically comprise three main components: first, search and information costs, which include efforts to identify potential transfer partners and acquire relevant market data; second, negotiation and contracting costs, which involve bargaining over key terms such as transfer modality, tenure, scale, and rental rates, as well as the formalization of agreements; third, monitoring and enforcement costs, which arise from ensuring contractual compliance and addressing potential disputes. Transaction costs, as a significant form of unproductive expenditure, not only directly constrain farmers’ land transfer decisions but also exclude participants from the transfer market by creating entry barriers, ultimately leading to the misallocation of agricultural land resources.

Under China’s fragmented farmland reality, spontaneous transfers among households are subject to multiple transaction cost constraints. On the one hand, decentralized transfer models require repeated bilateral negotiations, leading to high coordination costs. On the other hand, the high default rate associated with informal contracts further exacerbates resource misallocation. Village collectives can serve as crucial market intermediaries. Leveraging their unique organizational authority, information advantages, and governance capacity, they can effectively mitigate market transaction costs by consolidating fragmented supply–demand information, providing standardized contract guarantees, and promoting parcel consolidation. This organizational transformation originally scattered market transactions into systematic organizational coordination, thereby generating significant efficiency improvements. Based on this, we propose the following core hypothesis:

Hypothesis 1.

Compared with the spontaneous transfers among households, organized land transfer can significantly improve the allocation efficiency of agricultural land resources by reducing information search costs, negotiation and contracting costs, and monitoring and enforcement costs.

To unpack this hypothesis, we explore the internal mechanisms through which organized land transfer affects the allocation efficiency of agricultural land resources, focusing on three aspects: transfer stability, the transfer scale, and the transfer scope.

From the perspective of transfer stability, organized land transfer significantly promotes long-term and stable agricultural land transactions, thereby effectively enhancing agricultural land allocation efficiency by reducing transaction frictions. The stability-enhancing effect operates through two primary channels: contractual standardization and transaction continuity. First, standardized written contracts effectively mitigate opportunism by stabilizing transaction expectations and reducing hold-up risks, replacing informal verbal agreements. Village collectives formalize credible commitment mechanisms through formalized contracts that clarify property rights and obligations, thereby decreasing market uncertainty. This aligns with Williamson’s [20] transaction cost economics framework, where institutional safeguards substitute relational contracting to prevent ex post renegotiation. Simultaneously, as third-party enforcers [21], village collectives implement preventive risk mitigation mechanisms to maintain contractual integrity [22]. Second, to protect high transaction costs from repeated contracting, village collectives prioritize selecting tenants with long-term management commitments, thereby minimizing frequent recontracting costs in accordance with Coase’s [23] transaction cost minimization principle. By reducing both coordination and monitoring costs through these dual pathways, organized land transfer significantly improves transaction stability. Stable transfer relationships allow operators to confidently invest in long-term yield-increasing measures such as soil improvement, thus avoiding damage to land productivity caused by short-term operations [24]. This stability reduces transaction frictions, allowing land to flow more smoothly to efficient operators and lowering the risk of misallocation. Ultimately, the stability of land transfer promotes land market development and optimizes land resource allocation.

Hypothesis 2.

Organized land transfer enhances the stability of agricultural land transfers through standardized contract design and prioritizing long-term tenants, thereby promoting long-term investments by operators and improving resource allocation efficiency.

From the perspective of the transfer scale, organized land transfer is pivotal in expanding contiguous agricultural land, thereby enhancing allocative efficiency through economies of scale. The existing literature confirms that increasing the scale of agricultural operations improves both returns to scale and the efficiency of land use [25,26]. In the Chinese context, agricultural land remains dominated by smallholders, with approximately 91% of rural families managing less than 10.05 mu of land [27]. Such fragmentation significantly inflates the coordination and negotiation costs inherent in agricultural land transfer processes. Village collectives, as endogenous institutional actors embedded in rural social networks, possess superior information about local endowments and household preferences. By acting as intermediaries, village collectives provide symmetric information on agricultural land transfer to both supply and demand sides, thereby reducing information search and discrimination costs [28] while enhancing the probability of transaction completion. This principal-agent transfer model effectively capitalizes on village collectives’ comparative advantages in resource coordination. By consolidating fragmented plots from multiple households into unified parcels for tenants, the model achieves two key efficiency gains: significantly reducing tenants’ transaction costs in negotiating with dispersed lessors, and meeting the operational requirements for contiguous, large-scale agricultural production. Large-scale and contiguous operations enable the adoption of heavy agricultural machinery, which improves production efficiency and reduces unit production costs. For example, in large-scale contiguous plots, large equipment such as combine harvesters can operate more effectively, reducing harvesting time and costs [29]. Furthermore, the expansion of the transfer scale is conducive to attracting external capital investment, further promoting agricultural modernization, and achieving the efficient allocation of agricultural land resources [30].

Hypothesis 3.

Organized land transfer overcomes the constraints of land fragmentation via coordinated organizational interventions, enabling concentrated and contiguous land management and improving resource allocation efficiency.

From the perspective of the transfer scope, organized land transfer broadens the spatial scope of agricultural land markets, transcending the “parochial networks” of traditional peer-to-peer transactions to enhance allocative efficiency. This is supported by research demonstrating that reducing village-constrained transaction constraints and expanding the market allocation scope facilitates the integration of land transfer markets, thereby improving land allocation efficiency, which is critical for optimizing the allocation of grain production factors [31]. As endogenous governance bodies in rural grassroots systems, village collectives possess stronger organizational and resource integration capabilities, enabling them to overcome the pervasive village-level boundaries and information asymmetry in household-level transfers [12]. By facilitating cross-village land reallocations, land resources can be concentrated from low-efficiency smallholders to high-efficiency operators, enabling the realization of scale economies and specialized production networks. Such spatial expansion of land markets not only breaks through the geographical barriers but also promotes the rational flow of agricultural land resources across administrative boundaries, creating a more open and efficient market environment for agricultural production factors.

Hypothesis 4.

Organized land transfer can overcome the limitations of intra-village acquaintance networks, attract cross-village management entities, promote the concentration of resources to high-efficiency operators, and enhance land allocation efficiency through cross-village optimization of production factors.

Figure 1 presents an analytical framework of the organized land transfer for agricultural land allocation efficiency in China.

3. Model, Data, and Variable Measurement

3.1. Data Source

The data used in this study is derived from a special survey on agricultural production and management conducted by the research team in eight counties of Jiangsu Province in 2023. Given the significant socioeconomic heterogeneities among the Northern Jiangsu, Central Jiangsu, and Southern Jiangsu regions, a multi-stage random sampling strategy was employed to ensure the representativeness of the survey data. Counties were selected in a 4:2:2 ratio for Northern Jiangsu, Central Jiangsu, and Southern Jiangsu, respectively, with three townships sampled per county, three villages per township, and approximately 20 rural households per village. In total, the survey covered 1472 households across 72 villages in 24 townships of eight counties. The questionnaire collected information on households’ historical agricultural operations, family livelihood strategies, non-farm employment, social networks, and other dimensions. For the purposes of this study, our analysis centered on farmland transfer behavior. Within our sample of 1472 households, we identified 499 households that had transferred land in (inflow) and 1095 households that had transferred land out (outflow) during the reference period (some households are involved in both land inflow and outflow, so the total number exceeds the sample size). The final analytical dataset combines village-level data with detailed household and household head characteristics for these subsamples. To ensure data quality, we assessed the reliability of the survey instrument after data cleaning. Various methods are available for evaluating questionnaire reliability, among which Cronbach’s alpha coefficient is used to measure internal consistency. Values closer to 1 indicate higher reliability, while values below 0.6 suggest questionable reliability. In this study, the Cronbach’s alpha coefficients exceeded 0.7, demonstrating that the questionnaire possesses high reliability.

Figure 2 shows the specific surveyed counties, districts, and villages of this dataset.

3.2. Variables

The dependent variable in this study is agricultural land allocation efficiency. Following the method of Zheng et al. [32] and Gai et al. [8], we measured this using Olley–Pakes covariance (OP covariance). The theoretical premise is that in an efficient market, more productive economic agents should command a larger share of productive inputs. Consequently, a positive covariance between productivity and scale indicates that resources are flowing to those who can use them most effectively. A higher covariance value, therefore, signifies a higher degree of land allocation efficiency within a village. This covariance was calculated as follows:

$${\Omega }_{vi}={\displaystyle \sum _{i=1}^I\left(y_{vi}-\overline{y_{vi}}\right)}\left(s_{vi}-\overline{s_{vi}}\right)$$

(1)

where $y_{vi}$ represents the land productivity (output per mu) of household i in village v. $s_{vi}$ represents the proportion of the actual cultivated land area operated by household i, $\overline{y_{vi}}$ represents the arithmetic mean of the per-mu output of agricultural production across households in village v, and $\overline{s_{vi}}$ represents the arithmetic mean of the proportion of actual cultivated land area operated across households in village v.

The primary independent variable is the degree of organized land transfer, which we operationalized as the proportion of a village’s total transferred land area that is managed or facilitated by the village collective. We deliberately chose this continuous variable over a simple binary indicator (i.e., “whether organized land transfer occurs”). This is because the proportional measure more accurately captures the intensity and depth of the collective’s involvement in the local land market. Given the significant variation in the degree of collective participation across rural China, this nuanced indicator provides a more precise measure of the phenomenon in question.

Drawing upon our theoretical framework, we investigated three potential mechanisms through which organized land transfer may affect allocation efficiency: transfer stability, the transfer scale, and the transfer scope. Referring to Xu et al. [33], transfer stability is measured by two indicators: (1) formalization of transfer, which is specifically reflected in whether a written contract is signed for land transfer; (2) the transfer duration, which refers to the duration of the land transfer arrangement. The evaluation of the transfer scale combines the total operating scale of the land transferee and the land operational concentration (measured by the proportion of the area of the largest plot to the total operating area). The transfer scope is measured by a binary variable that indicates whether a transfer is a cross-village transaction, defined as a transfer to an operator residing outside the village.

To isolate the effect of organized land transfer, we controlled for a range of village-level characteristics that may confound the relationship, referencing the approach of Xu et al. [33]. The non-farm employment status of villages significantly impacts the pattern of agricultural land transfer, so two variables—non-farm employment and the gig market—are used to measure the characteristics of village-level non-farm employment. Geographical characteristics reflect the development level of villages to a certain extent, encompassing the accessibility of natural resources and access to public services. Villages in suburban areas with convenient transportation and developed infrastructure possess stronger capabilities. Consequently, control variables related to geography were introduced, operationalized through two indicators: (1) the distance to the nearest township, and (2) whether it is a suburban village (dummy variable). Village income significantly impacts the governance capacity, so village per capita income and collective economic income are further included as control variables. As both income variables exhibited a strong right-skewed distribution, we applied a natural logarithm transformation to mitigate the influence of outliers and normalize their distributions. Additionally, the strength of village lineage networks is also have a certain impact, which is also controlled in this study.

Table 1. Variable definitions and descriptive statistics.

Variables	Variable Definition	Mean	S.D.
The dependent variable
The allocation efficiency of agricultural land resources	OP covariance between the per-mu output and the operational area proportion of sampled households in the village	50.81	127.3
The independent variable
Organized land transfer	Degree of organized land transfer in the village (%)	56.87	39.34
Instrumental Variable (IV)
Village governance capacity	Degree of farmer participation in rural public affairs (%)	59.50	26.23
Mechanism variables
Formalization of transfer	1 if a written contract was signed, 0 otherwise	0.725	0.447
Transfer duration	Duration of transfer (years)	8.217	4.637
Land management area	Operational area post-land transfer for incoming renters (mu)	258.5	380.7
Land operational concentration	Proportion of the maximum plot area to total operational area (%)	0.505	0.290
Cross-village transfer	1 if the tenant is an external, 0 otherwise	0.163	0.370
Control variables
Non-agricultural employment	The proportion of employment outside the county within the village (%)	43.64	25.15
Gig market	Proportion of gig workers within the village (%)	24.73	22.62
Geographical location	Distance to the nearest township from the village (KM)	22.23	11.87
Village types	1 if the village is a suburban village, 0 otherwise	0.250	0.436
Fragmentation degree of contracted farmland	Average number of land parcels per household	3.943	4.036
Land consolidation	1 if the village has implemented land consolidation, 0 otherwise	0.569	0.499
Village governance structure	1 if the village party secretary and village committee director are the same person, 0 otherwise	0.958	0.201
Village collective economy	Village collective economy (CNY) (natural logarithm)	4.716	1.176
Village income per capita	Income per capita at the village level (CNY) (natural logarithm)	9.973	0.464
Village lineage networks	Proportion of households with the most common surname in the village (%)	24.24	16.23
Southern Jiangsu	Dummy variable for Southern Jiangsu (1 if located in Southern Jiangsu, 0 otherwise)	0.250	0.436
Northern Jiangsu	Dummy variable for Northern Jiangsu (1 if located in Northern Jiangsu, 0 otherwise)	0.500	0.504
Central Jiangsu	Dummy variable for Central Jiangsu (1 if located in Central Jiangsu, 0 otherwise)	0.250	0.436

summarizes the main variables used in this analysis.

3.3. Estimation Strategy

3.3.1. Baseline Model: The Impact of Organized Land Transfer on Allocation Efficiency

To estimate the overall impact of organized land transfer on village-level land allocation efficiency, we specified the following baseline regression model:

$${Cov}_v={\alpha }_0+{\alpha }_1{Transfer}_v+\gamma X_v+\epsilon$$

(2)

where ${Cov}_v$ represents the allocation efficiency of agricultural land resources in village v. This was measured using the OP covariance between the per-mu output and operational area proportion of sampled households in the village. ${Transfer}_v$ is the primary independent variable, representing the intensity of organized land transfer in village v. It was measured as the proportion of the village’s total transferred land area that is facilitated by the village collective. $X_v$ is a vector of village-level control variables, including geographic, economic, and social characteristics as specified previously. ${\alpha }_0$ is the constant term, ${\alpha }_1$ is the coefficient to be estimated, and $\epsilon$ is a residual error that is normally distributed.

3.3.2. Mechanism of Organized Land Transfer on Allocation Efficiency of Agricultural Land Resources

To investigate the mechanisms through which organized land transfer operates—namely, by enhancing transfer stability, scale, and scope—we conducted a series of household-level regressions. This approach allowed us to directly test the effect of the transfer mode on these intermediate outcomes. The model was specified as follows:

$$M_{vi}={\beta }_0+{\beta }_1{Transfer}_{vi}+\gamma X_{vi}+\epsilon$$

(3)

where $M_{vi}$ represents the mechanisms through which organized land transfer influences agricultural land allocation efficiency, including three pathways: transfer stability, the transfer scale, and the transfer scope. Transfer stability was measured by formalization of transfer and transfer duration. The transfer scale was measured by the land management area and the contiguity of agricultural land. The transfer scope was measured by whether the transfer was cross-village. ${Transfer}_{vi}$ is a binary variable indicating the mode of transfer for household i. It takes a value of 1 if the household’s transfer was organized by the village collective and 0 otherwise. $X_{vi}$ is a vector of household- and village-level control variables to account for other determinants of the mechanism outcomes. ${\beta }_0$ is the constant term, ${\beta }_1$ is the coefficient to be estimated, and $\epsilon$ is a residual error that is normally distributed.

4. Econometric Results

4.1. The Impact of Organized Land Transfer on the Allocation Efficiency of Agricultural Land Recourse

Table 2. Impact of organized land transfer on allocation efficiency of agricultural land resources.

	(1)	(2)	(3)
	COV	COV	COV
Organized land transfer	0.980 ***	0.812 **	0.910 **
	(0.369)	(0.379)	(0.419)
Non-agricultural employment		−0.614	−0.384
		(0.407)	(0.372)
Gig market		−0.160	0.068
		(0.524)	(0.537)
Geographical location		0.972	1.246 *
		(0.748)	(0.723)
Village types		39.845	46.283
		(39.009)	(41.792)
Village governance structure		−15.061	−22.227 *
		(18.770)	(12.878)
Land consolidation		−27.860	−43.757
		(43.114)	(52.351)
Fragmentation degree of contracted farmland		0.894	1.237
		(1.707)	(1.580)
Village income per capita		−28.612	−52.462
		(38.972)	(47.494)
Village collective economy		43.152	22.096
		(32.228)	(24.909)
Village lineage networks		−0.552	−0.424
		(0.652)	(0.525)
Region effects	NO	NO	YES
Constant	−4.914	125.804	406.876
	(25.434)	(298.457)	(391.302)
Observations	72	72	72
R2	0.092	0.279	0.325

Note: *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Robust standard errors are reported in parentheses.

presents the results of our baseline regression models that estimated the impact of organized land transfer on the allocative efficiency of agricultural land. Column (1) displays a bivariate regression model without control variables. The coefficient for organized land transfer is positive and statistically significant at the 1% level, providing preliminary evidence of a positive association. Column (2) adds village-level control variables to the model in Column (1). After controlling for heterogeneous factors at the village level, the transfer coefficient remains significantly positive at the 5% significance level. This suggests that while part of the initial association was driven by confounding village-level factors, a significant independent effect persists. Further, Column (3) incorporates regional dummy variables on the basis of Column (2) to control for unobservable environmental differences across regions. At this point, the coefficient of organized land transfer rebounds to 0.910 and remains significantly positive at the 5% significance level. This finding indicates that, even after controlling for a comprehensive set of village characteristics and regional fixed effects, a higher intensity of organized land transfer is robustly associated with improved land allocation efficiency, thus lending support to Hypothesis 1.

Regarding the control variables, several patterns are noteworthy. The coefficient for the geographical location becomes statistically significant at the 10% level after including regional fixed effects, demonstrating significant spatial heterogeneity in agricultural land resource allocation efficiency. This finding aligns with the developmental disparities observed between Southern, Central, and Northern Jiangsu. The coefficient for village governance structure changes from −15.061 (insignificant) to −22.227 (significant at 10%), indicating that its suppressive effect emerges after accounting for regional variations. This likely reflects that in areas with stronger administrative intervention, excessively institutionalized governance structures may conversely constrain the dynamism of market-driven land transfers.

4.2. Endogeneity Treatment and Robustness Checks

4.2.1. Endogeneity Treatment: IV

The baseline OLS estimates may be susceptible to endogeneity bias. A primary concern is omitted variable bias, where unobserved factors—such as local agroecological conditions or historical land use patterns—could simultaneously influence both the village collective’s decision to organize land transfers and the current state of land allocation efficiency. Such a correlation between the core independent variable and the error term would render the OLS estimates inconsistent. To address this issue, we employed an instrumental variable (IV) approach using a two-stage least squares (2SLS) estimator. We selected “village governance capacity” as the instrumental variable, which is specifically measured by the “proportion of villagers participating in public affairs”. Its validity is based on the following two aspects: First, the instrument must be strongly correlated with the endogenous variable (organized land transfer). The proportion of villagers participating in public affairs is highly correlated with the degree of organized land transfer: a higher participation rate indicates stronger organizational and coordination capabilities of the village collective [34], which can more effectively integrate fragmented plots, reduce transaction costs, and thus significantly increase the proportion of the organized land transfer area. The pre-test results show that this instrumental variable is significantly positively correlated with the core explanatory variable at the 1% level, and the Cragg–Donald Wald F statistic of the first-stage regression is 26.02. The test statistic exceeds the critical value of approximately 10, rejecting the null hypothesis of weak instruments. Second, the instrumental variable must satisfy the exogeneity condition. The proportion of villagers participating in public affairs, as a historical accumulation of village social capital, theoretically will not directly affect the current production efficiency of farmers. Specifically, (1) this indicator reflects villagers’ willingness to participate in collective affairs, belonging to village-level political and social characteristics, and has no direct connection with individual farmers’ land investment decisions or agricultural productivity; and (2) the types of public affairs involved (such as infrastructure maintenance) have no direct connection with agricultural production activities, satisfying the exclusion restriction. The regression results are shown in Columns 1 and 2 of

Table 3. The results of robustness checks.

	IV		Robustness Check I	Robustness Check II
	(1)	(2)	(3)	(4)
	Organized Land Transfer	COV	COV	Profit per Mu (PPM)
Organized land transfer		0.553 *	0.596 **	159.793 ***
		(0.330)	(0.283)	(55.253)
Village governance capacity	0.928 ***
	(0.419)
Control variables	YES	YES	YES	YES
Regional effects	YES	YES	YES	YES
Constant	−176.669	305.163	65.832	970.441
	(120.350)	(315.635)	(283.722)	(859.796)
F-value of 1st stage	26.02
Observations	72	72	72	499
R2		0.315	0.280	0.209

Note: *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Robust standard errors are reported in parentheses.

. The instrumental variable (IV) estimate shows a coefficient of 0.553, which remains statistically significant at the 10% level, continuing to support a positive effect. This suggests that our core finding of a positive relationship is robust to the potential for endogeneity bias.

4.2.2. Robustness Check I: An Alternative Specification of the Independent Variable

In the preceding analysis, the measurement of the independent variable relied on the proportion of organized land transfer at the village level, based directly on village-level data. This measure, often based on official village reports, may be subject to reporting bias. To mitigate this potential bias, we redefined the independent variable as the proportion of households within a village that participated in organized land transfer. This new variable was aggregated from our household-level survey data. The regression results using this alternative measure are presented in Table 3, Column (3). The coefficient on organized land transfer remains positive and statistically significant, reaffirming our baseline finding that a higher intensity of organized land transfer is associated with improved land allocation efficiency.

4.2.3. Robustness Check II: Evidence from Household-Level

A core premise of our study is that improved village-level allocation efficiency manifests as land flowing to more productive operators. To test this premise directly, we shifted our analysis to the household level. We replaced the village-level efficiency covariance measure with a direct, household-level indicator of operator productivity: profit per mu. The independent variable is the binary transfer mode (1 if the transfer was organized, 0 otherwise), consistent with our previous mechanism analysis.

As shown in Table 3, Column (4), the coefficient on organized land transfer is positive and significant at the 1% level. This indicates that land transferred through organized channels is indeed associated with operators who exhibit higher profitability. This household-level evidence provides strong, complementary support for our main Hypothesis 1, suggesting the village-level efficiency gains are driven by a genuine reallocation of resources to more productive agents.

4.3. Mechanism Tests

As previously elaborated in the theoretical framework, organized land transfer is hypothesized to reduce transaction costs and enhance agricultural land allocation efficiency through three mechanisms: enhancing transfer stability, expanding the transfer scale, and broadening the transfer scope. This section empirically tests these mechanistic hypotheses.

4.3.1. Mechanism I: Enhancing Transfer Stability

Following prior research [12], transfer stability is operationalized through two dimensions: the formalization of transfer and the transfer duration. As shown in Column (1) of

Table 4. Mechanism tests of organized land transfer promoting allocation efficiency of agricultural land resources.

	Transfer Stability		Transfer Scale		Transfer Scope
	(1)	(2)	(3)	(4)	(5)
	Formalization of Transfer	Transfer Duration	Land Management Area	Land Operational Concentration	Cross-Village Land Transfer
Organized land transfer	3.505 ***	1.477 ***	162.840 ***	0.064 *	1.565 ***
	(0.674)	(0.479)	(30.472)	(0.036)	(0.474)
Control variables	YES	YES	YES	YES	YES
Regional effects	YES	YES	YES	YES	YES
Constant	−9.672	2.924	0.674	−1049.151 *	−19.878 ***
	(7.328)	(6.469)	(0.626)	(570.997)	(7.654)
Observations	499	499	499	300	300
R2		0.151	0.292	0.062

Note: * and *** indicate statistical significance at the 10% and 1% levels, respectively. Robust standard errors are reported in parentheses.

, organized land transfer exhibits a significant positive effect on the signing of written transfer contracts, and the regression results are statistically significant at the 1% level. Column (2) reveals that organized land transfer significantly promotes long-term land transfers, also significant at the 1% level. These findings provide robust empirical support for Hypothesis 2.

4.3.2. Mechanism II: Expanding Transfer Scale

To investigate the mechanism of large-scale contiguous transfers, this study operationalizes the contiguous transfer scale through two indicators: the land management area and the land operational concentration. Column (3) of Table 4 presents the regression results for the impact of organized land transfer on the land management area, demonstrating a significant positive effect at the 1% statistical level. Column (4) reveals that organized land transfer significantly increases the contiguity of land, with results significant at the 10% level. We may cautiously conclude that land transfers organized by village collectives can significantly expand the operational area of transferees and, to a certain extent, enhance the land operational concentration of operators. This thereby validates Hypothesis 3.

4.3.3. Mechanism III: Broadening Transfer Scope

Beyond transfer stability and transfer scale, organized land transfer is also hypothesized to enhance allocation efficiency by broadening transfer scope. Column (5) of Table 4 presents regression results that show that organized land transfer promotes cross-village land transfers, with statistical significance achieved at the 1% level. The realization of cross-village land transfers signifies that land resources have transcended village boundary constraints, enabling flows to more efficient operators beyond local communities. This cross-regional optimization of production factors enhances allocative efficiency. These findings provide empirical support for Hypothesis 4.

4.4. Further Analysis

4.4.1. Organized Land Transfer, Collective Economy, and Allocation Efficiency of Agricultural Land Resources

The effectiveness of organized land transfer is not uniform; rather, it is moderated by the institutional capacity of the village collective. We hypothesize that the positive impact of organized land transfer on land allocation efficiency is contingent upon the strength of the village’s collective economy. In villages with robust collective economies, the leadership typically possesses superior organizational capacity, more established governance structures, and greater resource endowments. These attributes enable them to be more effective intermediaries who are better equipped to overcome transaction frictions and coordinate complex land reallocations. Consequently, the efficiency-enhancing role of organized land transfer should be significantly amplified in such environments.

To empirically test the aforementioned theoretical analysis, this study incorporates the village collective economy and an interaction term between organized land transfer and village collective economy into the baseline regression model. The results are presented in

Table 5. The results of heterogeneity analysis.

	(1)	(2)
	COV	COV
Organized land transfer	0.784 **	0.830 **
	(0.338)	(0.372)
Collective economic	17.623
	(22.423)
Organized land transfer * Collective economic	0.803 *
	(0.446)
Lineage networks		−0.316
		(0.450)
Organized land transfer * Lineage networks		−0.030 *
		(0.015)
Control variables	YES	YES
Region effects	YES	YES
Constant	531.649	323.369
	(456.160)	(339.858)
Observations	72	72
R2	0.398	0.314

Note: * and ** indicate statistical significance at the 10% and 5% levels, respectively. Robust standard errors are reported in parentheses.

, Column (1). While the direct effect of the collective economy itself is not statistically significant, the coefficient on the interaction term is positive and significant at the 10% level. This finding indicates that the positive effect of organized land transfer on the allocation efficiency of agricultural land becomes more pronounced as the village collective economy becomes stronger. This finding provides critical empirical evidence for understanding the heterogeneous impacts of organized land transfer and offers valuable policy insights for optimizing land transfer.

4.4.2. Organized Land Transfer, Lineage Networks, and Allocation Efficiency of Agricultural Land Resources

The effectiveness of organized land transfer is also shaped by a village’s informal institutional landscape, particularly its lineage networks. As a pivotal informal institution, village lineage networks exert significant influence on transaction costs and organizational efficiency. Tight kinship networks mitigate information costs, while established clan authority provides a governance foundation, and high intra-group trust reduces monitoring costs. However, the net positive effect of the impact is contingent upon the congruence between lineage networks and collective interests. In practice, clan relationships have a dual impact on organized land transfer: they may improve efficiency by reducing coordination costs, yet they may also amplify implementation difficulties due to conflicts between clan-specific interests and collective interests. This influence mechanism underscores the complexity of clan factors, in which the ultimate effect emerges from the dynamic equilibrium of multiple competing forces.

Based on this, this study constructs a village lineage network variable and introduces it as an interaction term with the key explanatory variable in the regression model. Column (2) of Table 5 reports that the estimated coefficient for the interaction term between the village lineage network and organized land transfer is negative and statistically significant at 10%. A plausible explanation for this result is that in villages dominated by strong lineage networks, land transfers are more likely to occur informally among kin. These “insider” transactions, while socially embedded, tend to remain fragmented and suboptimal from a village-wide efficiency perspective. This could partially counteract or “crowd out” the benefits of more formalized, collective-led transfer systems, leading to a muted or even slightly negative moderating effect.

5. Equity Effect: Organized Land Transfer and Willingness to Transfer

The trade-off between efficiency and equity has always been a core proposition in economic research. The existing literature suggests that voluntary land transfer transactions have both efficiency and equity advantages [2,35]. This study confirmed that the organized land transfer can significantly improve resource allocation efficiency. However, the existing literature [11,12] also points out that this model may restrict the autonomy of farmers and operators. Therefore, after clarifying the impact of organized land transfer on agricultural land allocation efficiency and its underlying mechanism, this study further explores the effect of organized land transfer on farmers’ willingness to transfer their land, aiming to clarify whether village collective-intervened organized land transfer contributes to improving household welfare.

As reported in Column (1) of

Table 6. Organized land transfer and willingness to transfer.

	(1)	(2)	(3)	(4)	(5)
	Willing	High Income	Low Income	Elderly	Young
		Willing		Willing
Organized land transfer	−0.224 ***	−0.110 ***	−0.352 ***	−0.261 ***	−0.175 ***
	(0.026)	(0.029)	(0.046)	(0.043)	(0.033)
Control variables	YES	YES	YES	YES	YES
Region effects	YES	YES	YES	YES	YES
Constant	2.649 ***	1.823 ***	3.230 ***	2.474 ***	1.111 *
	(0.257)	(0.552)	(0.436)	(0.442)	(0.566)
Observations	1095	599	496	469	626
R2	0.098	0.069	0.140	0.160	0.094
p-value of coefficient difference	-	0.002 ***		0.074 **

Notes: (1) *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively. Robust standard errors are reported in parentheses; (2) This analysis was conducted at the level of land-transferring households; (3) p-values for tests of inter-group coefficient differences in the heterogeneity analysis were calculated using Fisher’s combined test with 2000 resampling iterations.

, the coefficient of organized land transfer on farmers’ willingness to transfer is −0.224, significant at the 1% level. This result indicates that organized land transfer exerts a significant negative effect on farmers’ transfer willingness. The possible explanation for this is related to the policy context: since 2014, the central government has issued a series of documents like the Opinions on Guiding the Orderly Circulation of Rural Land Management Rights and Developing Moderate-Scale Agricultural Operations, repeatedly emphasizing the need to strengthen the role of governments and village collectives, which has further promoted the implementation of agricultural land circulation target assessment policies in various regions. However, in local implementation, this may have translated into top-down administrative targets, leading some village collectives to employ coercive measures or excessively intervene in transfer negotiations. Such practices can infringe upon farmers’ autonomous decision-making, diminish the value of their property rights, and consequently reduce their willingness to engage in the system [36].

Heterogeneity analysis further demonstrates that organized land transfer has an inhibitory effect on the willingness to transfer among farmers at different income levels, and the magnitude of the effect varies significantly. The inhibitory effect on low-income farmers’ transfer willingness (coefficient = −0.352) is significantly stronger than that on high-income farmers (coefficient = −0.110), with the inter-group coefficient difference significant at the 1% level. This is likely because low-income households rely more heavily on their land as a critical safety net and a source of subsistence. With a weaker bargaining position, they may perceive organized land transfer as a process where they risk losing this essential asset under unfavorable conditions. Additionally, regression results grouped by age indicate that the negative impact of organized land transfer on the willingness to transfer among elderly farmers (coefficient = −0.261) is significantly more pronounced than that among young farmers (coefficient = −0.175), with the inter-group coefficient difference also significant at the 5% level. Meanwhile, elderly farmers typically exhibit stronger emotional attachment to land and may harbor concerns about post-transfer social security, such as anxiety over losing stable rental income or employment opportunities after land transfer, thereby reducing their willingness to participate in transfers.

In summary, while organized land transfer can enhance resource allocation efficiency, its implementation may suppress farmers’ willingness to transfer land due to excessive administrative intervention, with particularly significant impacts on low-income and elderly farmers. This finding underscores the need for policymakers to balance efficiency and equity in promoting large-scale agricultural management, avoiding overreliance on administrative measures and establishing more inclusive transfer mechanisms for vulnerable groups—such as low-income households and elderly farmers—to protect their land rights and long-term welfare.

6. Discussion

6.1. Main Findings

This study centers on the core issue of enhancing land resource allocation efficiency in developing countries, examining the pivotal role of organized land transfer within this context. Traditional theories posit that improvements in land allocation efficiency hinge on market-oriented transaction mechanisms, whereas socially embedded transactions often impede the flow of land resources toward more efficient producers. Against such a backdrop, the emergence of organized land transfer models—predominantly led by village collectives in rural China—offers a novel perspective and empirical evidence for the necessity of investigating land resource allocation efficiency.

This study found that organized land transfer effectively enhances the efficiency of land resource allocation by improving transfer stability and expanding the transaction scale. This aligns with the work of Qiu et al. [12], who demonstrated that village collectives can significantly reduce organizational and supervisory costs in the transfer process, thereby enhancing the stability of land transfers and expanding their scale. Furthermore, this theoretical logic is further validated in the study by Xu et al. [33]. In addition, this study revealed that organized land transfer breaks down village boundaries and facilitates the transfer of land to external operators, effectively concentrating land resources in the hands of more productive farmers and thus improving the efficiency of land resource allocation. This finding not only corroborates the proposition put forward by Wang and Xin [31] that “reducing the localization of land transfers is conducive to integrating the land transfer market and enhancing land resource allocation efficiency” but also provides robust empirical support for this view.

In further analysis, this study identifies that the effectiveness of organized land transfer is contingent upon the local institutional and social environment of villages. In developed East Asian economies such as Japan and South Korea, formal organizations like agricultural cooperatives have largely supplanted traditional social networks in land transfer practices [37]. By contrast, China’s distinctive “collective-clan” dual governance structure exhibits transitional features characterized by the coexistence of formal organizations and traditional networks. In villages with stronger collective economic capacity, organizational and mobilization capabilities are enhanced [38], which can significantly boost the efficiency of organized land transfer. However, clan networks exert a negative moderating effect on organized land transfer, which further corroborates the research by Zhou et al. [39] that strong social ties among farmers may facilitate self-organized land transfer.

Notably, the equity implications of organized land transfer uncovered in this study carry broader significance. This study indicated that organized land transfer exerts a negative influence on farmers’ willingness to participate, with elderly farmers and low-income households being particularly affected. Their disadvantaged negotiating position in the transfer process may result in the erosion of their own interests. This provides empirical support for the theoretical insights of Shi et al. [11], who explored the potential risks of information monopoly and rent-seeking inherent in the intermediary role of village collectives—risks that may encroach upon farmers’ legitimate rights and interests.

This study systematically investigated the impact of organized land transfer on agricultural land allocation efficiency and its underlying mechanisms. It is demonstrated that organized land transfer significantly improves the efficiency of land resource allocation; however, in the process of implementation, this model objectively weakens the decision-making autonomy of individual farmers, thereby affecting the protection of farmers’ rights to a certain extent. These findings not only expand the research dimensions concerning the impact of organized land transfer on large-scale land management, but more importantly, they introduce a perspective of assessing equity effects, offering a more holistic framework for comprehensively understanding the overall effects of organized land transfer.

6.2. Limitations and Future Directions

This study is subject to two primary limitations: First, our analysis was constrained by data availability. The use of cross-sectional data precluded our ability to control for unobservable, time-invariant, village-level characteristics, which could introduce omitted-variable bias and thus affect the robustness of our conclusions. Second, the scope of our analysis regarding the model’s dual effects on efficiency and equity was circumscribed. While we confirmed that organized land transfer enhances allocative efficiency, this study did not fully investigate the concurrent issues of distributional injustice. Specifically, the adverse impacts on vulnerable farmer groups were not sufficiently detailed, leading to an incomplete assessment of the model’s net social and economic impact.

Building on these limitations, future research can focus on an in-depth exploration around the dual effects of organized land transfer: On the one hand, in terms of incentive mechanism design, it is necessary to deeply explore how to construct institutional arrangements with strong incentive effects to promote intermediary organizations to actively participate in farmland transfer, thereby effectively reducing transaction costs. On the other hand, in the construction of the supervision system, it is necessary to systematically explore how to form effective constraints on the behaviors of intermediaries to effectively protect the legitimate rights and interests of farmers in the transfer process.

7. Conclusions

In the context of scarce and highly fragmented land resources, enhancing allocation efficiency through land transfers is imperative. This study empirically examines whether organized land transfer, as a distinctive transfer model, can effectively enhance land allocation efficiency using survey data from Jiangsu Province. Our key findings are fourfold: (1) Organized land transfer significantly improves land allocation efficiency, and this conclusion remains robust across multiple robustness tests. (2) The efficiency improvement of organized land transfer is primarily achieved through three mechanisms: enhancing transfer stability, expanding transfer scale, and broadening transfer scope. (3) The positive effect of organized land transfer is amplified by stronger village collective economies but is attenuated by the presence of dense clan networks. (4) Critically, organized land transfer can adversely affect farmers’ willingness to participate, with this negative impact being particularly pronounced among low-income and elderly households.

Based on these findings, this study proposes the following policy recommendations:

(1)

Promoting and standardizing organized land transfer to enhance efficiency. Given the demonstrated efficacy, organized land transfer should be actively supported. Central and provincial governments should encourage local governments and village collectives to serve as intermediaries. Specifically, higher-level governments should invest in strengthening the institutional capacity of rural land transaction platforms, providing dedicated funding for their operation, maintenance, and technological upgrades. At the local level, village collectives should leverage these platforms to offer professional services, such as market information and price assessments, and use policy advocacy and demonstration projects to guide farmer participation. To incentivize these grassroots efforts, the central government should establish targeted subsidies for organizational costs and link successful transfer outcomes to eligibility for other development projects, creating a synergistic policy environment for standardized and efficient land markets.

(2)

Safeguarding farmers’ rights and ensuring procedural fairness. To mitigate the risk of coercion and protect farmers’ autonomy, a robust regulatory and supervisory framework is essential. Higher-level governments must issue clear policy guidelines that define the functional boundaries of village collectives, restricting their role to facilitative services like information provision. All forms of coercion, whether overt (e.g., forced transfers) or disguised (e.g., undue intervention), must be strictly prohibited. Particular vigilance is required to prevent rent-seeking behaviors arising from collusion between village officials and commercial capital. To enforce this, a multi-stakeholder oversight mechanism—incorporating farmer participation, transparent reporting of village affairs, and higher-level government supervision—should be established, complemented by accessible channels for farmers to report grievances and protect their rights.

(3)

Implementing targeted protections for vulnerable groups. The inequitable impacts of organized land transfer on low-income and elderly farmers demand differentiated policy responses. It is recommended that tailored protection measures be implemented. First, for households unwilling to participate, establish land-exchange schemes that allow them to swap their plots for land of equivalent quality and area in a more suitable location, with financial compensation where necessary. This respects their choice while still facilitating contiguous land consolidation. Second, for households exiting agriculture, focus on ensuring their sustainable livelihoods. This includes providing vocational training to facilitate their transition into non-agricultural employment and implementing social support programs, such as “work-for-relief” to bolster their income and reduce their economic dependency on land.