The Role of Non-economic Factors in Customary Farmland Reallocation in Shandong Province, China: An Analysis of Distrust to Village Cadres

Abstract

This study aims to determine whether non-economic factors impact villagers’ attitudes toward Customary Farmland Reallocation (CFR). Based on data collected from Village X in Shandong Province, based on the binary logistic regression analysis, this study concludes that: 1) household size is correlated to villagers’ attitudes towards CFR. 2) the distrust of village cadres is correlated to villagers’ attitudes towards CFR. This study suggests that non-economic factors like the distrust of village cadres need to be considered, as well as economic factors when considering CFR.

1.  Introduction

In the examination of agricultural modernization, farmland customs have consistently garnered attention due to their impact on formal farmland institutions. Unlike government-driven legal farmland institutions, these farmland customs primarily rely on support from the private sector for sustenance. China serves as an exemplary nation influenced by farmland customs.

After the 1980s, accompanied by the Reform and Opening-Up policies, the Household Responsibility System emerged as a formal farmland institution. Within this framework, the village enjoys farmland ownership collectively, while individual villagers possess farmland’s contractual management rights (i.e., the use rights). The ambiguity of collective ownership and the rapid population growth has led to frequent reallocation of contractual management rights, i.e., farmland is constantly being taken back and reallocated to new farmers. This phenomenon is known as Customary Farmland Reallocation (CFR). CFR threatens villagers’ farmland tenure security (Deininger et al., 2014; Che et al., 2019a). Consequently, a series of inhibitive policies implemented by the Chinese government since the early days of the Reform and Opening-Up endeavors aim to mitigate the impact of CFR on farmland (Zhao, 2020).

CFR was explicitly prohibited in 2002 by enacting the Rural Land Contracting Law and a series of inhibitive policies. Nevertheless, empirical evidence from studies and tracking surveys indicates that CFR still has some supporters in rural China, even though the authorities declared it illegal. Much research has been invested in explaining these proponents from an economic perspective. For example, Deininger et al. (2014) discuss that enhancing the security of property rights in agricultural land can promote economic growth. At the same time, exploring non-economic factors is still limited, especially the discussion of social pressure within the village or trust in village cadres.

The primary objective of this study is to investigate the potential relation between villagers’ attitudes towards CFR and non-economic factors. Does distrust toward the village’s cadres predispose villagers to hold unfavorable views toward CFR? This study advocates for considering non-economic factors levels when attempting to mitigate the impact of CFR.

2.  Literature review

A prevalent custom is inherently embedded in its societal fabric, conferring advantages upon its supporters. These benefits may encompass economic, social, or a combination of both.

Exploring farmers’ attitudes toward CFR is a crucial aspect of the study of CFR. In a survey of 119 Chinese villages, Tao et al. (2009) discovered that 60% of respondents expressed negative attitudes toward the prohibition of CFR and still desired to participate in CFR, citing population changes as a critical consideration. Feng et al. (2013) reported that 43% of respondents endorsed the prohibition of CFR, while 28% opposed it. Additionally, their research introduces equity contributing to villagers’ attitudes toward CFR. Based on a survey of 443 farmers across five provinces in China, Zheng and Gao (2017) found that 39.3% of farmers opposed the prohibition of CFR. Notably, their study considers the impact of village elites’ perspectives on equality or rent-seeking behavior on villagers’ attitudes toward CFR by incorporating the respondent’s role as a village cadre (village secretary of the village branch of Communist Party of China) in the investigation.

Several studies have delved into the economic rationales behind villagers’ support for CFR. Huang and Tan (2018) contend that villages are inclined to reallocate land to secure their basic livelihood expenses, notably when lacking or having insufficient social security coverage. Xiao et al. (2023) posits that household members in need of care (0–4 years old) significantly increase the likelihood of farmers retaining their land. Kung et al. (2011) observes that elevated transaction costs arising from topographical factors prompt villages to reduce the size and scope of CFR. Similarly, Che et al. (2019b) confirm that an increase in the number of plots mitigates the transaction costs of CFR for villages, bringing a higher proportion of CFR.

In contrast, fewer studies have addressed non-economic factors, with discussions primarily focusing on farmers’ subjective perceptions of altruism or equality. For instance, Yiwen and Kant (2022) suggest that CFR is associated with farmers’ prosocial preferences (altruism), although the impact of such preferences may vary.

Villagers’ attitude towards CFR encompasses not only their intrinsic values but also their interactions within their village community, including interactions with other villagers and the elite stratum of the village, i.e., village cadres. By this thinking, factors represent social pressure, and trustiness should be involved when addressing CFR. Given the necessity for villagers to sustain themselves within the village, where agricultural activities often require mutual assistance, the following question arises: Do villagers consent to CFR in the village due to apprehensions about the social pressure of rejecting CFR? Moreover, as a farmland custom, CFR is primarily dictated by the local village, particularly the elites of the village. Regardless of whether the elites genuinely benefit from this custom, does the uncertainty-driven distrust of village cadres correlated with villagers’ attitudes toward CFR?

This study aims to explore farmers’ attitudes toward CFR initially. Subsequently, this study explores the relationship between villagers’ attitudes toward CFR and non-economic factors by distrust of village cadres.

3.  Background and data

(1)  Customary farmland reallocation

Although CFR is diverse regarding membership, reallocation methods, and periodicity, a constant common element can be found throughout previous research: a practice of reallocating farmland within a village or among villagers under the Household Responsibility System. As the farmland collective ownership indicates that all villagers enjoy a share of ownership of the farmland of their village, CFR typically responds to changes in population dynamics such as marriage, birth, adoption, death, or migration (Zhu, 2002; Kung et al., 2011; Wang et al., 2011).

In more detail, these three perspectives have been widely mentioned in previous studies. Firstly, regarding content, CFR involves negotiations within the village, often instigated by village leaders or elites. These negotiations encompass eligibility criteria for members, calculation of population changes, average land area per person, and strategies for balancing variations in topography or farmland quality (Kung et al., 2011). Usually, farmland will be divided into several small plots corresponding to the per capita farmland area. Then, farmers, on a household basis, will draw lots to determine their new farmland for the next cycle. Secondly, regarding periodicity, CFR usually follows a predetermined cycle, determined through village negotiations and often initiated by village leaders or elites. Previous studies have revealed diverse cycles, with common patterns occurring every 5 or 10 years (Zhu, 2002). Finally, regarding legality, the authority initially tried to restrict and limit the scope and manner of CFR, eventually banning CFR in the 2002 Rural Land Contract Law. Because collective ownership means that all villagers enjoy a share of ownership, allocating farmland to the new population is a natural result and the consensus of the villagers. However, CFR was banned after implementing the Rural Land Contract Law in 2002. Despite villagers still collectively owning farmland, their collective exercise is narrowed down to the contractual management right, as proposed in the Household Responsibility System.

In summary, although CFR is affected by its unique characteristics, efforts to understand these common characteristics and the factors underlying these common characteristics are necessary to explain why CFR has not disappeared in the past 20 years even after the Rural Land Contract Law banned it.

(2)  Study site

The research location will be Village X in southwest Shandong Province. The reasons are as follows: First, farmers have a strong demand for farmland in Village X. Village X is located in China’s major grain-producing and densely populated area. On the one hand, Heze Prefecture, where X village was located in 2021, is the top crop-sown area in Shandong Province. On the other hand, the scarcity of farmland is also extreme. With 411.8 hectares of farmland supporting more than 2400 residents, the per capita farmland of Village X is 0.16 ha. This data is relatively larger than the 0.08 ha of cultivated land per capita in Shandong province in 2014 (the province’s cultivated land per capita includes the non-farming population in its statistics). Following the characteristics of “too many people, too little land,” farmers urgently want farmland. In addition, Village X is located in the North China Plain, which has less particular topography than South China, making its CFR less affected by unique characteristics and more valuable to observe.

Second, Village X is both an administrative village and a natural village. Natural villages represent the appropriate population size and social relations within X village. In contrast, administrative villages represent X village with clear village boundaries. Y natural village and Z natural village around X village are counted as one administrative village because of their smaller size. As a custom, CFR relies on mature population size and solid social relationships; in this regard, Village X is an appropriate choice for research.

Finally, Village X also has non-farm income channels that can be utilized. There are two towns within 10 km and two towns within 20 km of Village X. (The administrative definition of a town is a resident population of more than 2000 with more than 50% non-farm population). The distance to the nearest high-speed railway station is about 20 km. In addition, nearby villages have a spinning mill and a plate-making factory. Migrant labor is a common choice.

Figure 1 shows the sample of farmland in Village X. It is planted with winter wheat, the vacant farmland is reserved for intercropping a cash crop (peppers), and there are slightly raised ridges (rectangles areas) between the plots to separate the land from each other. These ridges are not constant; they can be easily leveled and rebuilt to accommodate CFR.

Fig. 1

The sample of farmland in Village X

Source: Author

(3)  Data

This study employed a quantitative approach, obtaining micro-level data through a questionnaire survey conducted in Village X, Shandong Province, China, between January and February 2023. Since most information about Village X is unavailable, the authors had to opt for snowball sampling. But to minimize bias, firstly, the author chose the Chinese New Year as the period of the survey because family reunions are a custom of the Chinese New Year, thus increasing the overall size and diversity of the sample. Secondly, the author and two helpers strolled along the roads in the village on an uncertain route over the survey period, using the villagers they met on the way as survey respondents. Eventually, 154 valid responses to the questionnaire were recorded. Table 1 briefly shows the mean of farmland area and population of farmers.

Table 1. 

Statistics of Farmland and Population of Farmers

Variables	Mean	Standard deviation
Household Farmland area	0.42	3.02
Household Farmland plots	2.34	0.91
Household size	4.42	1.53
Number of non-labor force	2.34	1.61

Source: Author

1) N=154.

2) The unit of household farmland area is hectare per household. The unit of household farmland plots is the plot per household. The unit of household size is the number of people per household. The unit of non-labor force size is the number of people per household.

4.  Results and discussions

(1)  Respondents’ characteristics

In this section, the study elucidates the characteristics of the respondents. Initially, 154 participants participated in the questionnaire survey, with males constituting 62% and females 38% of the sample. Considering that males are usually involved in agriculture and CFR, the slightly elevated representation of male respondents is by anticipated respondent characteristics. Secondly, about age groups, most respondents belong to the 20 to 59 age brackets, comprising 68% of the total. This age group commonly constitutes the primary labor force in agriculture, suggesting that respondents are more likely to have experience pertinent to CFR. Concerning education levels, more than 75% of respondents have received only primary or secondary education.

Family type indicates that 62% of respondents belong to the nuclear family type, encompassing either a couple or a couple with underage children. Moreover, 33% of respondents are classified under the quasi-extended family type, wherein a couple, underage children, and grandparents cohabit. Furthermore, the average land area per household is 0.42 ha, typically comprising 2.3 land plots. With an average household size of 4.42, it can be inferred that in Village X, most families consist of couples with two children or couples with one child and one older adult, enjoying approximately 0.42 ha of farmland spread over 2–3 plots.

The farmland situation above poses challenges in maintaining a livelihood. Consequently, beyond villagers engaged as full-time farmers, there are alternative options—becoming part-time farmers, commonly known as migrant workers (nongmingong). Another choice is to exit the agricultural sector while still registered as a farmer in the household registration (hukou). Results indicate that 3% of respondents in Village X chose to withdraw from the agricultural sector. They typically retain their farmer hukou to preserve their contractual management rights, subcontract their farmland to others, and work and reside in cities or towns. Among the remaining 97% engaged in farming, 64% are full-time farmers. Moreover, 36% are part-time farmers, indicating their inclination to explore opportunities in urban areas during the agricultural slack season to increase their income. It is vital to note that this full-time/part-time catalog is flexible. Farmers can either become part-time farmers by chance or quickly return to being full-time farmers due to economic downturn.

(2)  CFR in X Village

This study uses a seven-point Likert scale. A rating of 1 indicates strong disagreement with a given statement, while a rating of 7 indicates strong agreement with a given statement.

Regarding interviews with CFR, respondents were asked to describe their attitudes toward the following statement, “What are your attitudes toward the CFR? (AtCFR)” Table 2 shows the frequency of respondents on each attitude. Respondents’ average score of 4.6 indicates a relatively favorable overall attitude toward CFR. However, the standard deviation of 2.02 suggests a notable dispersion of attitudes among participants, indicating an apparent diversity in their opinions. Results show that 45% of respondents expressed approval of CFR, 30% expressed opposition, and 25% expressed neutrality. Those results clearly show that opinions within the village are distinct, and CFR does not enjoy universal popularity among all villagers.

Table 2. 

Likert scale frequency of AtCFR, DVC, SP

	AtCFR	DVC	SP
Strongly disagree	16	34	12
Disagree	10	42	10
Relatively disagree	20	16	10
Neutral	38	10	10
Relatively agree	6	12	12
Agree	22	12	42
Strongly agree	42	28	58

Source: Author

1) N=154.

2) This table shows the frequency of respondents on each attitude.

3) Likert is in des-cending order, strongly agree is equal to 7, neutral is equal to 4, and strongly disagree is equal to 1.

Distrust of village cadres (DVC) asked interviewees to evaluate their attitudes toward the following statement, “Do village cadres benefit suspiciously more from the CFR process?” The results reveal a slight trust towards village cadres, with a 3.47 mean value indicating that respondents subjectively believe that village cadres could not gain more suspicious benefits from CFR. Similarly, the standard deviation of 2.23 implies a diversity of opinions within the respondents. 33.8% of the respondents believe that village officials may have been suspicious, and 18.2% firmly hold this view.

Concerning social pressure (SP), respondents were asked to weigh their attitudes toward the following statement, “Refusing to participate in the CFR will harm my social relationships in the village.” With a mean value of 5.32, the result indicates that villagers are concerned that the CFR may harm their interpersonal interactions within the village, even though the strength and form of this harm are not explicitly clarified. Since 72.8% of the respondents agreed with this concern, fearing this potential risk may relate to individuals to express outward approval of CFR, regardless of their genuine perceptions.

(3)  CFR, social pressure, and distrust

In this section, this study addresses the relationship of three primary variables: attitudes toward CFR(AtCFR), social pressure (SP), and distrust of village cadres (DVC). Specifically, this study has two primary concerns. Do villagers within their community consent to CFR relate to concerns about being exposed to social pressure if they reject CFR? Does distrust toward the village’s cadres relate to villagers’ unfavorable views toward CFR?

This study has made some processing to answer the questions above. First, this study created dummy variables of AtCFR, SP, and DVC, where AtCFR=1 is for agreeing with CFR, includes strongly agree, agree and relatively agree, SP=1 is for being influenced by social pressure, includes strongly agree, agree and relatively agree, and DVC=1 is for distrusting village cadres, includes strongly agree, agree and relatively agree. Secondly, this study created dummy variables for gender (1=female), age (1=greater than 70 years old), and agricultural engagement (1=part-time farmer) to smooth the analysis.

In Table 3, two separate models were created with AtCFR as the dependent variable. The primary concern of this study was examined in Model 1, which were used to observe the relationship of DVC and SP on AtCFR. Also, in order to consider the performance of SP and DVC under the influence of other variables in an integrated manner and to reduce unobservable variable bias, in model 2, DVC, SP, gender, age, agricultural engagement, farmland area, farmland plots, household size, and non-labor force population were substituted.

Table 3. 

Binary logistic regression model with AtCFR as the dependent variable

Model	Variables	Coefficient	SE	OR (Odds ratio)
1	Constant	−0.839	0.640	0.432
	SP	0.339	0.553	1.403
	DVC	1.568**	0.526	4.798
2	Constant	−3.067	1.428	0.047
	SP	−0.238	0.708	0.788
	DVC	1.419*	0.595	4.132
	Agricultural engagement	0.819	0.656	2.267
	Gender	−0.07	0.656	0.933
	Age	0.742	0.760	2.1
	Farmland area	−0.114	0.131	0.892
	Farmland plots	0.123	0.339	1.131
	Household size	0.789**	0.300	2.201
	Non-labor force	−0.411	0.280	0.663

Source: Author

1) N=154.

2) **p<0.01, *p<0.05.

3) Multicollinearity was not found.

In Model 1, the chi-square for the Hosmer and Lemeshow Test was 2.64 (p=0.267), and the total observed percentage was 70.5. The OR for DVC was 4.798 (p=0.003), indicating that DVC is positively correlated to AtCFR, implying that the respondents who have favorable attitudes are related to those respondents who do not trust village cadres. The OR for SP is 1.403, but p=0.540, suggesting that SP is positively correlated to AtCFR, but not statistically supported.

Model 2 had a chi-square of 7.2 (p=0.408) for the Hosmer and Lemeshow. The OR for DVC was 4.132 (p=0.017), suggesting that DVC is positively correlated to AtCFR. The OR for household size is 2.201 (p=0.009), indicating that household size is also positively correlated to AtCFR.

First, household size’s significant correlation on CFR is reconfirmed, consistent with many previous studies. Larger household size means that relatively more farmlands will be available in the next round of CFR, and thus, larger household size is correlated with farmers’ positive attitude towards CFR. Second, this study finds that DVC is positively correlated to AtCFR. This assertion is eye-opening. It implies that villagers are more likely to support CFR while they harbor distrust of village cadres. One possible explanation is that first of all, the CFR is implemented by drawing lots, which represents that even though village cadres may be able to play tricks with the farmland grading or membership of CFR, drawing lots to reallocate farmland is relatively more complex to play tricks. Thus, the CFR is still acceptable to the villagers. Moreover, DVC represents the villagers’ subjective perception that village cadres may have suspiciously benefited more. This subjective perception may come from the experiences of CFR and other farmland options such as the Household Responsibility System. So, under the presupposition that the village cadres are suspicious, a choice between a CFR that is relatively familiar and an HRS (formal land system) in which the village cadres have more interpretive space, the farmer’s more familiar CFR will be the favored one. As results, DVC is statistically correlated to AtCFR.

However, it is essential to note that due to the scarcity of village statistics, the sampling in this study was based on snowball sampling, and the sample size was small. There is still a need to be vigilant about the impact of sample bias on the statistical results. The finding that the correlation of DVC and AtCFR is only a preliminary finding, and more robust assertions must be made with larger samples. The interpretations provided in this study must also be further validated in upcoming fieldwork.

In this study, the multicollinearity among variables was assessed, and the results indicate that multicollinearity is not a significant issue. Specifically, the VIF values for the Gender and DVC variables are 1.216 and 1.102, respectively. The VIF values for Agricultural Engagement and SP variables are 1.527 and 1.358, respectively. The VIF values for Age and Farmland Area variables are 1.97 and 1.94, respectively. Notably, the VIF value for Household Size is 2.698, which is higher but still within acceptable limits.

5.  Conclusion

In conclusion, this study explored villagers’ attitudes toward CFRs in Village X and analyzed whether distrust of village cadres related to such attitudes. The SP is not significantly correlated to attitudes toward CFR. The study found that respondents slightly preferred CFRs in general and distrust of village cadres is correlated to villagers’ preference for CFRs. The author suggests that subjective cognitive distrust of village cadres may related to both CFR and experience with other farmland options. Thus, the CFR with a lottery system is favored over an unfamiliar farmland option. The analysis of the binary linear regression shows that the non-economic factors, that is, the distrust of village cadres, remain correlated effective when the effect of economic factors is considered. This result suggests that non-economic factors, like economic factors, should also be considered when discussing the CFR issue.

This study does not clarify causal relationships and must be limited to saying that there is a statistically significant correlation between the DVC and AtCFR. It is necessary to clarify the causal relationship between these variables and to solve the problem of endogeneity and to go into causal relationships in the future studies.

Acknowledgments

This research was granted by Ritsumeikan University’s AY2023 Research Grant for Doctoral Students.

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