How Do Farmers Make Money Renting Out Farmland

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Research Article

How practise farmland rental markets impact farmers' income? Show from a matched renting-in and renting-out household survey in Northeast China

• Zhifeng Gao,
• Chuchu Dominicus,
• Mengyao Wang

How do farmland rental markets affect farmers' income? Evidence from a matched renting-in and renting-out household survey in Northeast Cathay

• Ning Geng,
• Zhifeng Gao,
• Chuchu Sun,
• Mengyao Wang

ten

• Published: September 30, 2021
• https://doi.org/10.1371/journal.pone.0256590

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Abstract

Promoting farmland transfer through the farmland rental market is an essential musical instrument to attain the scale economy of agronomical production in Red china. However, past literature on the land reform in Cathay pays more than attention to the renting-in household or the renting-out household, respectively, less to both types of households together. Using a big-scale survey of farm households in Mainland china, we examine the determinants of participation in the farmland rental market and quantify the impact of the rental market on farmers' income. Findings show household off-farm income, family members' office-time employment, agricultural subsidies, and participation in agricultural cooperatives significantly impact farmers' participation in the farmland rental marketplace. Participation in the farmland rental market significantly increases the income of renting-in households, while information technology decreases the income of renting-out households, which might result from the temporary lag result of the country system reform.

Commendation: Geng N, Gao Z, Sun C, Wang M (2021) How do farmland rental markets impact farmers' income? Evidence from a matched renting-in and renting-out household survey in Northeast China. PLoS 1 sixteen(ix): e0256590. https://doi.org/10.1371/journal.pone.0256590

Editor: Tahirou Abdoulaye, International Plant of Tropical Agronomics, NIGERIA

Received: December 7, 2020; Accustomed: August 10, 2021; Published: September xxx, 2021

Copyright: © 2021 Geng et al. This is an open access article distributed nether the terms of the Creative Eatables Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting information files. The data underlying the results presented in the study are all bachelor.

Funding: This enquiry was funded by the ministry of education and social scientific discipline youth program, grant number 17YJC79004 (host: NG) , the national natural science foundation of China program, grant number 71803104 (host: NG), and Qingchuang Scientific discipline and Technology Support Plan for Colleges and Universities in Shandong Province grant number 2019RWE009 (principal member: NG).

Competing interests: The authors have declared that no competing interests exist.

i. Introduction

Land reforms implemented since the beginning of the 1980s have profoundly stimulated China's rural land rental marketplace. Since land is not privately endemic in many countries, liberalizing rural state use rights has long been advocated equally a good policy for agricultural economic growth and peasants' well-being improvement in some developing countries. Starting 2002, there was an increased incidence of land rental activities in Mainland china (Deininger & Jin, 2005; Shuyi Feng et al., 2010) [1,2]. In the meanwhile, more and more rural young labors are pouring into China's big cities to have up not-farm employment, accelerating the process of urbanization. Therefore, the development of the rural state market place is gaining momentum (Huang et al., 2012) [three]. The contribution to the economical growth of a well-performance land rental marketplace has well been recognized in China. Recently, the Chinese government farther promoted rural state markets through "subcontracting, leasing, exchanging, or swapping" state-use rights (Huang et al., 2012) [4]. The state policy motivates some farmers to rent more country to increase farm size and reduce rural land fragmentation.

Development economics postulate that institutions play an essential role in facilitating economical growth (Due north, 1990) [five]. Securing property rights are expected to be a necessary factor of an institutional environment contributing to development (de Soto, 2000) [half dozen]. So the arguments over holding rights take long been the root cause of country reform, more than often considering the vast majority of the rural population rely on the land to generate livelihoods (Deininger Chiliad, 2005; Feng S., 2008; Becerri J., 2010) [1,seven,eight]. In particular, the reform of rural land resources' property rights is at the center of rural development and urbanization in contemporary Red china. Equally land is an essential factor of agronomical production, securing property rights is expected to not only improve productivity (Carol et al., 2015) [nine] but also motivate investment in farm production (Jerzy Michalek et al., 2014) [10].

Land tenure security is an important precondition to developing a well-functioning rural land rental market place (Besley, 1995) [eleven]. When rural state is rare, the certification of land use rights is expected to be a crucial way to impart greater security (Wang H., 2015) [4]. The land-employ rights certification can identify the content of country employ rights also as confirm and secure long-term state tenure. Some studies show that enhanced tenure and land use right certification promote participation in the country rental market (Jinming Y.,2021) [12]. Findings in Cathay show that tenure-enhanced land reforms increased the land market place activities by 5.five% from the renting-in households (Deininger et al., 2015) [13]. Studies besides show that country certification can positively bear on renting-out households just leave renting-in households unaffected (Deininger et al., 2011) [fourteen]. Land certification induces greater appointment in Bharat's land rental marketplace (Bardhan et al., 2014; Holden et al., 2011) [15,16] and appears to have stimulated more land rental market place activities in the SNNP region in Ethiopia (Holden et al., 2016) [17]. Therefore improving tenure security and country certification is critical to the development of the land rental marketplace.

As rural land rental market activity has increased in recent decades, then have the number of studies estimating its furnishings on farmers. Regarding the impacts of the rural land rental market, attention is mainly focused on efficiency, equity, and welfare. It is well known that the land rental market could have enhanced the allocative efficiency and agricultural productivity in rural China (Carter and Yao, 2002; Jin and Deininger 2009; Kimura et al., 2011) [xviii–20]. Research finds that land transfers from less efficient to more efficient farmers through land markets volition help reallocate land. Empirical evidence from southeastern China and Ethiopia suggested that the rural land rental marketplace could significantly boost economical growth and productivity because renting-in households accept a higher marginal product of rural country than renting-out households (Shuyi Feng, 2010; Klaus Deininger, 2013) [2,21]. Regarding the effect on equity, several contempo studies ended that rural country rental markets could promote disinterestedness in some developing countries past transferring country from country-rich farmers to state-poor farmers and from labor-poor households to labor-rich household (Jacob Ricker-Gilbert, 2019; Chamberlin & Ricker-Gilbert, 2016; Yamano et al., 2009) [22–24]. Min Shi (2017) suggests that China'southward land rental market is a more effective method of rural land reallocation than authoritative distribution without necessarily jeopardizing equity [25]. As well, the welfare effect is primarily concerned with increasing income of renting-in or renting-out land and reducing poverty. The country rental market can facilitate greater access to land for small farms as a primary productive asset (Songqing Jin & T.Southward. Jayne 2013) [26]. The empirical evidence from dynamic panel income models shows that the small farms' total income gains from renting-in state were very remarkable (Klaus Deininger et al., 2013; Holden, Otsuka, and Place 2009) [21,27]. Renting-in land can increase the income of households and reduce the incidence of family poverty (Chen & Zhai, 2015) [28] The findings from Republic of kenya bear witness that renting-in state would reduce poverty status by increasing per capita total income by 6.6% (Kimura S., 2011) [20]. As well, off-farm employment too enables renting-out households to increase their earnings from the land rental and non-agricultural incomes (Feng & Heerink, 2008) [29].

Despite the general finding of positive effects from the rural land market, questions still remain well-nigh how the rental market place meliorate income in the smallholder farming system for both renting-in and renting-out household. One of the major gaps in the literature is that most researchers focus on the land rental market place's income result either for renting-in households or for renting-out households. Few have examined the consequence of the land rental market on both renting-in and renting-out households at the same time. An exception is a study by Chen & Zhai (2015), which found that the cyberspace income consequence for renting-in household mainly originates in the calibration expansion of farmland and improvement of technology efficiency, while the income issue of renting-out household is mainly from off-farm income increment and partly from rent revenue [28].

In this study, nosotros focus on the rental land marketplace in the Shandong province that lies on the coast of northeast China and uses recently nerveless data on renting-in household and their matched renting-out household to estimate the income effect from land renting. Shandong is a noteworthy case in several aspects. First, Shandong is a province with better economic evolution where rapid changes in land transformation have taken place in the context of industrialization and urbanization. Specially, the province's superior geographical location provides many opportunities for farmers to appoint in off-farm employment. 2nd, the province is a region of low flat state and an important grain production base of operations. Thus, a well-functioning rental state marketplace is crucial to ensure the nation'south grain supply. 3rd, Shandong province is representative with a loftier incidence of state transactions. Considering of the to a higher place reasons, it will be interesting to estimate the income effect and the determinants of rural state rental market place participation in Shandong province.

Our research is motivated past the two questions: (i) would the improving welfare attributed to state rental markets in the previous studies hold if renting-in and renting-out households are observed every bit in the same dataset? (2) What are the determinants of farmers' participation in the country rental marketplace?.

Nosotros contribute to the current literature mainly from 3 aspects. Starting time, we overcome the trouble of estimating the income effect of renting-in and renting-out households separately. By compiling a dataset with renting-in households and their corresponding renting-out households, nosotros consider both the need and supply sides of the land rental market. Estimating the economic benefit to renting-in and renting-out households from land renting simultaneously, we can draw some conclusions that help make accurate land rental policies. 2nd, we use the propensity score method (PSM) to separate the effect of land renting from other factors that may affect the farm income. Thus the calculated results are relatively more convincing. Third, nosotros investigate the determinants that pb to farmers' decisions on renting in or out rural land. Specifically, we determine whether the factors that impact households' decision to rent in or out are dissimilar and how the same factor may affect the land rental market participation in different ways.

The remainder of this commodity is organized equally follows. In Department 2, nosotros develop a conceptual framework to describe the determinants of participation in the country rental market. Section 3 mainly introduces the written report site, the procedure of information drove, and descriptive statistics. Section four describes the empirical model to analyze the possibility that farmers will rent in or rent out country and the PSM method to measure the income effect of land rental market. In department 5, we discuss the estimation results of the models. Section 6 shows the summary and conclusions of our study.

2. Conceptual framework

Following an agronomical household model of product and rural land market place participation (Deininger and Jin, 2005; Jin and Deininger, 2009) [1,xix], with the premise of "rational economic man", nosotros develop a conceptual model to decide the factors affecting a peasant'south participation in the rural land rental market.

Assume the household i choose the rural land to farm (Ai), the allocation of household labors engaged in the farming (50 _ia ), the amount of labors for off-farm employment (L _io ). We tin use the post-obit equation to model a household's income maximization beliefs: (2.1) (2.ii)

In this equation, and are the fixed number of rural labor and land endowments, respectively, of the i household, while a _i is a prepare of household characteristics; f(a _i , L _ia , A _i ) is an agricultural production function; p stands for the cost of agronomical products; west denotes the wage charge per unit of off-farm employment for L _io ; and r is a competitive rent in the rental land market. and are indicators standing for the renting-in ( for renting-in land or 0 otherwise) and the renting-out ( for renting-out land or 0 otherwise), respectively, of land. and are the respective transaction costs for renting land in the land rental market.

Solve the income maximization problem; the post-obit 2 equations define the conditions of the renting-in and renting-out of country: (ii.3) (ii.4)

Suppose r is dissimilar for the local households due to the different plots of land. and are consistent for all farmers because they may face the risk of land loss, and the 2 indicators are related to the land tenure security (or certification of state renting contract), thus we can contain r, , A _i , and into the vector Mi which denotes rental market transaction variables. The labor variables ( and a _i can be represented by a vector of household characteristics (Howdy), and Di is causeless to be family unit off-farm employment. As well, w can be included in the external surroundings (Wi). Hence nosotros can derive the two reduced-form function associated with the Eqs two.iii and ii.4 as follows: (2.5) (ii.half-dozen)

The Eqs (2.5) and (2.6) show that the determinants of renting-in or renting-out lands are determined by family off-farm employment (D), household characteristics (H), rental market transaction characteristics (M), likewise equally the external environs (W).

3. Survey and data

3.1 Report site

Shandong is an of import agricultural province that lies on China's east declension and across the sea from Japan and Republic of korea (Fig 1), with a location suitable for an consign-oriented economy. Shandong is also 1 of the about densely populated provinces of Prc, with small farms and high levels of land fragmentation comprehend approximately 157,100 km2. Equally the major grain-producing region, Shandong's grain production in 2017 was 53.two million tons (Fig 2), accounting for 8 percent of the national total. Shandong led the country in total grain output value in 2017 (Fig iii), reaching $60.635 billion. In sum, Shandong is a typical region that characterizes the manifestly surface area of northeast China and also a production base for ensuring food security.

Besides, Shandong has about 24.2 million rural laborers working off-farm by 2017. An efficient rural state market would not only help meliorate country productivity but too increases rural income. The Chinese government has promoted the reform of rural land holding rights since 2015. The innovation of the land reform lies in liberalizing the land usage (or direction) rightⁱ (In People's republic of china, rural land ownership belong to the rural commonage organization, farmers only have contracted management and use rights.) and activating the land rental marketplace according to supply and demand of farmland (Wang H, 2015) [thirty], which tin realize the scale economy of farmland and improve peasants' income (Vandeplas et al, 2013) [31].

However, due to the influence of traditional Chinese thinking, in Shandong, many modest-calibration landholders are not willing to rent out their farmland, although these smallholders operate their country very inefficiently. In the meanwhile, productive farmers may not have the experience to manage large-scale farmlands when they make a decision on renting in more land. Therefore, it is essential to determine the factors influencing farmers' participation in the land rental market and whether participation in the country rental market can amend rural income.

three.2 Data collection

The information used in this article were collected from a socio-economic survey of landholders from December 2017 to November 2018 during the non-farming season in Shandong. The survey collected detailed information on family members' socioeconomic characteristics, such as household income, on-farm and off-subcontract activities, the amount of renting state, land-use history, and country certification status.

To ensure that the sample includes typical renting-in and renting-off households, sample choice was carried out as follows. First, the survey was conducted in two cities of Shandong province, Dezhou and Qingdao. Both regions are manifestly areas with large plots and take an active country rental marketplace in Shandong. More than chiefly, they are agricultural demonstration zones in Shandong, and more than 40% of farmland is traded in the land market. Specifically, the proportion of traded land in Qingdao is approximate 50%, while information technology is 42% in Dezhou. Second, considering we wanted to interview both the land renting-in (renting-out) households and their corresponding renting-out (renting-in) households, the sample areas selected were relatively large villages with many rural state transactions. Thus, iv administrative townships were randomly selected from Dezhou city, including iii administrative villages in each sample township. While in Qingdao, two administrative townships were selected, and in each sample township, five administrative villages were selected.

Finally, to increase the response charge per unit and obtain respondents' truthful opinions, nosotros collected the data using a face-to-face up survey. During the survey, ane enumerator took 1–ii hours to complete one questionnaire, and each survey enumerator completed 3–5 questionnaires per twenty-four hour period. To ensure the actuality of the survey, nosotros randomly selected respondents in the sample villages. Because our piece of work focused on the income effect of the land rental market on land renting-in households and their corresponding renting-out households, when nosotros interviewed the renting-out households, nosotros tried to place their matching renting-in households past the country charter contract. To estimate the land rental market'south income effect, we likewise interviewed farmers who were not participating in the land rental market in the sample villages, which was used every bit a control grouping.

With the data covering 810 rural households across 22 villages from Shandong province, our study can exist considered a representative sample of the rural state rental market place participants. At that place are 407 participating households, including 240 renting-out households and 167 renting-in households. Moreover, most of the land lease agreement was between 8–xx years. Because the current study mainly focuses on the welfare outcome of participation in the land market, we did not examine the impact of lease agreement length on the land rental market place participants' income. Future research tin investigate the effect of land rent-in/rent-out contract length on household welfare.

3.three Definition and descriptive statistics

In this section, nosotros ascertain and describe the critical variable in the model that may bear upon farmers' participation in the country rental marketplace and their household income.

As discussed in Section 2, land hire in and hire out behaviors are influenced by four sets of variables such as household characteristics (H _i ), family off-subcontract employment (Di), rental market transaction characteristics (M _i ), as well as the external environment (West _i ) (Eqs two.iii and 2.iv). The 4 dimensions and their relevant indicators (Table 1) are discussed below.

H _i denotes a vector of household characteristics including age ("age") and education ("edu") of the householder. Generally, the average age of the renting-in group is significantly lower than that of the renting-out group considering young households are more willing to hire in farmland for scale farming (Min et al, 2015) [32]. In addition, the renting-out farmers have a significantly higher education level considering well-educated farmers have more opportunities to find off-subcontract jobs.

D _i is a vector of variables representing the number of farms and off-subcontract labors. In our written report, we use the share of household off-farm income ("share") and the ratio of family members`off-subcontract employment to farm employment ("parttime") every bit proxy variables of Di. As the rapid evolution of urbanization, the non-agricultural activities of ordinary farmers are gradually transferred to the service industries in the surrounding areas or urban areas. Therefore, the higher the proportion of non-agronomical income or the ratio of family unit members' off-farm employment, the more inclined farmers are to hire out more farmland. In today'south Mainland china, renting a lot of state requires hiring labor, and hiring labor can supervene upon family members.

M _i includes the rental market transaction variables, such as state operating surface area (area), a long-term certificate for land tenure (cont), the price of renting land (price), and the subsidies for production (subsidy). The land operating area is an important factor affecting rural country transfer every bit farmers with more than land are more probable to rent land out (Huang and Ji, 2012) [3]. Additionally, the land price (e.g., state rent) is a key element in the land rental market (Wang et al., 2011b) [33]. A high price of renting land may motivate more farmers to rent the land out. Besides, a long-term land tenure document is helpful to the development of the land renting market. Information technology has been promulgated to peasants for ensuring state use correct with a stable contract menstruum since the "Rural Land Contract Law" was issued in China in 2002 (Huang and Ji, 2012; Deininger et al., 2014) [three,34]. At last, the subsidies for product (subsidy) will induce more need for renting-in land considering they can reduce the production price when farm operation is expanded to a large product scale (Chen.F,2015) [28].

W _i is the 4th dimension cogent the external environment that may affect the country transfer. The variables included are the distance from the village to the urban area ("distance"), which tin exist used to correspond the off-subcontract opportunity information of household members. Furthermore, participation in agronomical cooperatives could promote scale economies or reduce transaction costs to some extent (Tafesse West. et al., 2019) [35]. And so the control variable "cooper" could take a meaning bear upon on the renting-out and renting-in land. At present, in China, agricultural production has shifted from labor-intensive to technology-intensive product, so whether family members accept received special technical training represents farmers' technical level. The "tech" variable indicates farmers' knowledge of agricultural technologies. More than knowledgeable farmers are more likely to rent in the land to develop efficient agriculture.

The statistical descriptions of all variables used in the regression are summarized in Tabular array two. The statistics in Table 2 prove that the renting-in group's income level was significantly higher than that of those not participating at 1% significance level. The income level of the renting-out group was the lowest of the 3 groups. However, the statistical deviation of the to a higher place indicators may not exist the inevitable result of land renting, but caused by other factors. Therefore, we demand to institute other econometric models to examination the impact of land renting on household income.

4. Empirical model

Following the in a higher place conceptual models, in this section, we will establish econometric models to estimate the determinants of farmers' renting-in and renting-out land and use the propensity score matching (PSM) method to measure the income effect of the state rental market place.

4.1 Model specification: The Logistic model

The determinants of farmers' renting-in or renting-out conclusion on rural country tin be modeled with the Stochastic Utility Decision Model (Ali, A., and Abdulai, A., 2010) [36]. We postulate U1 and U0 representing the utility of farmers' participation in the state rental market place and non-participants, respectively. If Five* = U1- U0>0, the farmers will choose to participate in the rental land market, otherwise not. Although nosotros can't observe V, it can be represented as a part of observable variables. We specify the following function models: (4.one)

In office (4.i), V is a two-value variable. If one household participates in the land rental market (renting in or renting out), V is equal to 1, otherwise, V is equal to 0. Ten is the vector of exogenous explanatory variables affecting farmers' participation in the land rental market. The detailed definitions and statistical descriptions X are summarized in Tables i and 2. μ is a random disturbance term.

Nosotros can estimate the determinants of farmers' renting-in and renting-out land decisions past Logistic model. Specifically, the probability that a farmer hire in or rent out her/his land is (4.ii)

Suppose , and , nosotros tin get the post-obit equation, (iv.iii)

Taking the log of both sides of Eq 4.iii, we get another equation as follows, (4.4)

Thus, the sign of an contained variable'south coefficient indicates whether changes in the independent variable would increment or decrease the probability that a farmer rents in or rents out the land.

4.ii Estimation approach: Welfare upshot of state rental market

Previous studies accept shown that whether to participate in the land rental market, farmers are "self-selecting", and some unobservable factors (such as production preference, management skills or family wealth, etc.) may affect the decision-making and lead to biased estimation results. For this purpose, Rubin (1974) put forward "a counterfactual framework", which was referred to as "Rubin Causal Model (RCM)" [37]. The dichotomous Di = {0, 1} indicates whether the household ith participates in the land rental market. Correspondingly, the counterfactual outcomes are y _1i and y _0i , respectively, participation and non-participation in the land rental marketplace.

(iv.five)

The handling effect for i is thereby (y _1i - y _0i ), which is what we want to guess. y _1i and y _0i tin can not be observed at the aforementioned time. So nosotros can model the household i's observed result every bit follows: (four.6)

In Eq (4.5), y _i is impacted by the household i'southward traits set X _i , the exogenous explanatory variables set 10 _j , and the random unobservables μ _i . For the aforementioned household i, μ _i represents the unobserved determinants of outcomes following a articulation normal distribution, such every bit the household's product preferences, managerial skills, or household wealth. On this basis, the influence equation of participating in farmland capitalization on farmers' welfare tin can be ready as follows: (4.7)

Moreover, the household ith participation in the land rental market does non affect other individuals, which is deemed to "stable unit of measurement handling value assumption" (SUTVA). This assumption excludes inter-individual social interactions or general equilibrium. Because the treatment effect (y _1i - y _0i ) is a random variable, nosotros just need to pay attending to the expected value East.

To solve "self-selection" of inquiry objects and the influence of unobservable factors (such as product preference, direction skills or family wealth, etc.), this commodity adopted the propensity score matching (PSM) method. We selected farmers who did not participate in the state rental market as the control group for the matching analysis. Rosenbaum & Rubin(1985) constructed a counterfactual analysis framework dissimilar from Eq (4.7) to effectively eliminate the biased estimation of non-random distribution of samples [38]. We need to detect a control group like to the treatment group to reduce the bias of sample pick. For those having participated in the land marketplace, we estimate the average treatment-on-the-treated effect (ATT) past: (4.8)

Eq (four.8) shows that East(y _1i | Ten _i , X _j , D _i = one) is appreciable, while Due east(y _0i | 10 _i , X _j , D _i = one) is unobservable, which is chosen a counterfactual result. Therefore, an alternative indicator E(y _0i | X _i , X _j , D _i = ane) tin can exist constructed using the propensity score matching method (PSM). On the premise that the covariates (Ten _i , X _j ) of the ii groups are as similar or identical as possible, the propensity score of each sample to enter the handling group is calculated. This method can accurately evaluate the income outcome of the land rental marketplace and compare the source of the income effect of two groups of matched samples.

5. Estimation results and discussion

5.ane Determinants of farmers' participation in the land rental market

Before the regression estimation, we outset clarify the correlation of the covariates variables X in the model and test the possible multicollinearity problems. Table 3 shows that the average variance inflation cistron (VIF) for the country hire-out and rent-in groups are 1.24 and ane.45, respectively. The largest VIF of the command variables for both groups is ii.58. Therefore, it can exist concluded that the multicollinearity problem in the models is not serious.

To further measure the income upshot of the land rental market on unlike households, and to provide conditional probabilistic fitting values for computing the household income effects (ATT), a flexible logistic model was used for regression interpretation. We commencement estimate ii functions as Eqs (ii.5) and (2.vi). The regression results are reported in Table iv. The following conclusions can be drawn from the coefficient estimates of the key variables in the ii models.

First, in the model for renting-in land, the coefficients of "historic period", "share", "parttime", "toll", "subsidy", and "tech", are pregnant at the levels of 1% (Table 4). The results imply that relatively young households are more willing to rent in farmland for scale farming. The negative coefficient of "share" implies that the lower the proportion of non-agricultural income, the more than likely is a household willing to rent in the country. And the "parttime" denotes the number of household members who have off-farm employment. Due to the depression comparative returns of agriculture, ordinary farmers' not-agricultural activities are gradually transferred to the chief service industries in the surrounding areas and urban areas. Therefore, the households with more family members having off-farm jobs are more inclined to rent in farmland. These farmers tin can earn higher income from off-farm employment to hire laborers for farming (Deininger and Jin, 2005; Chen & Zhai, 2015; Jacob Ricker-Gilbert, 2019) [1,23,28]. Table four also shows that the other explanatory variables, e.m., the price of renting land, the agricultural cooperative, and agricultural technical grooming, significantly touch farmers' participation in the land rental market. In line with our theoretical assay, land toll is a primal element of the land rental market (Jerzy Michalek et al., 2014) [10]. The higher the land hire is, the less likely a household is to hire in the land (Carol et al., 2015) [9]. The "tech" variable clearly indicates that the households receiving technical training are more than likely to rent in the country. At nowadays, agricultural output has shifted from labor-intensive to technology-intensive production, and then farmers' technical skills related to efficient agricultural product technologies should significantly affect their land renting behavior (Carter and Yao, 2002; Jin and Deininger 2009; Kimura et al., 2011; Jerzy Michalek et al., 2014) [10,18–20]. The command variable "cooper" also indicates that households who are members of the agricultural cooperatives are more likely to rent in farmland. Joining cooperatives may reduce transaction costs, thus increase households' likelihood to rent in the land.

Second, in the model for renting-out land, the positive coefficient of "edu" indicates that a college level of landholders' education will increase their likelihood of renting out the land considering these people have higher chances to find off-farm jobs (Yamano et al., 2009; Shuyi Feng, 2010; Klaus Deininger, 2013) [ii,21,24]. Moreover, the variables "share", "parttime", "subsidy", and "cooper" take the same impact on renting out land equally in the model for renting-in country. This indicates that the above factors influence the participation of farmers in the land rental market place (Feng & Heerink, 2008; Songqing Jin & T.S. Jayne 2013) [26,29]. Furthermore, the land area (area) is positively correlated with households' land renting-out behavior. Households with more than country are more probable to rent out the land. This might be because land-rich households have more chances to earn money instead of specializing in farming (Klaus Deininger et al., 2013) [21]. Finally, the distance from the village to the urban surface area is significantly negatively associated with the probability that a household rents out the country. The distance to the urban area tin can be used as an indicator of the cost for farmers to go out for work. The further information technology is to the urban area, the fewer off-farm employment opportunities, and farmers are less willing to hire out their land (Macmillam, 2000; Dijk, 2003) [39,40].

5.2 Measurement and analysis on income result of the land rental marketplace

The most important purpose of propensity score interpretation is to residue the distribution of variables between experimental and treatment groups rather than to obtain authentic probabilistic predictions. Figs 4 and 5 indicate the region of mutual back up of transfer households (renting-out households and renting-in households) and non-participants. Compared with the total sample size, the sample loss ratio is modest, and the condition of the common support domain is satisfactory.

Moreover, to minimize the inter-group differences in the probability distribution of sample households of different groups and ensure loftier-quality matching results, we carried out a balance test on explanatory variables and command variables of the experimental and handling groups. Table 5 shows the departure before and after the match. The bias (in %) of explanatory and about command variables later the matching have shrunk to less than 10%, and most of the T-test result is significant after the match. Peculiarly important, matching can not simply reduce the full bias but too tin can effectively reduce the differences between groups of unlike samples. The standardized divergence of private control variables is more than x% afterward matching just still within the adequate range. The above test results show that the matching of explanatory variables and control variables between unlike samples is desirable. It has certain persuasive power to explain the change of farmers' welfare level.

Afterwards obtaining constructive matching samples, we calculated the income effect of the land rental market (ATT) as in Eq (iv.8). Stata12.0 software was used for the actual matching. To reduce the loss of effective samples, the matching was carried out with a replacement, and different matching methods were used considering the selected sample individuals (control grouping) in this report were limited. The results in Table six show that, from a quantitative perspective, although the values of the 4 matching results are unlike, the numerical directions are consequent, and near of them accept passed the significance exam. Based on the comparative assay of the two primary welfare furnishings, the welfare effect of renting-out farmland is negative while renting-in farmland has a significant increase in income. In other words, the average per capita net income of a renting-out household will decrease by 567.29 yuan. In comparison, the average per capita net income of a renting-in household will increase by 26386.53 yuan.

Considering the limitations of PSM, the implicit bias caused by unmeasurable factors should exist considered. That is, the influence of the implicit bias on the matching results should be tested. We used the "Rosenbaum Bounds" dominion to test the sensitivity of the matching results (Rosenbaum,1985) [38]. Examination results testify that when Γ = 1.5, the respective P-value is still meaning at v% or ten% levels. This indicates that the effect of unobserved confounding on the ATT estimates is relatively pocket-size, and our conclusion on the welfare result of the land renting marketplace is reliable.

Based on the to a higher place regression results (Tabular array 4) and the calculated results of the income effect of farmers (Table 6), the following conclusions tin exist made. Firstly, the land rental market can significantly increase the income level of the renting-in household. This may mainly relate to the government's financial subsidies for production. However, the income level of renting-out households is declining.

Secondly, for the renting-out household, "didactics", "the share of household non-farm income (share)", "the ratio of family unit members`part-fourth dimension employment (parttime)", "household contracted farmland area (area)", "whether to join agronomical cooperatives (copper)", and "the distance from the hamlet to the city (altitude)" are the key elements for the renting-out households. Theoretically speaking, farmers are willing to voluntarily hire out their state only when the total income from the land rent and non-agricultural income is higher than the net income of agricultural production. Nevertheless, the income level of renting-out households has not been improved significantly, which may arise due to the lag effect of the land organisation reform (Besley and Burgess 2000) [41].

Thirdly, for the renting-in households, The results bear witness that reducing production cost ("subsidy") and improving applied science level ("tech") are the cardinal influencing factors of current land scale management households. The variables of "historic period" betoken the ability of farmers to operate and manage the land. Meanwhile, farmers' scientific and technological levels and the agricultural subsidies determine the output boundary of the farmland and the profit space of scale operations.

6. Conclusion

This study evaluates the income effect of farmers participating in the land rental market place and analyzes farmers' beliefs relevant to participation in the land rental market. Taking account of four dimensions of livelihoods decision-making of farmers, we find that the state rental marketplace increased the level of income for farmers who rented in farmland while reducing the level of income for farmers who rented out their land. Two reasons may contribute to the outcome. Firstly, given the long-term goal of gaining economies of scale in agronomics, upwards-to-bottom country reform past the regime brings more back up (eastward.chiliad., agronomical) for the renting-in rural households to realize scale-operation of farmlands. The focus is on enhanced agricultural productivity (Carter and Yao, 2002; Jin and Deininger 2009; Kimura et al., 2011) [eighteen–20]. On the other hand, since our data only covers the initial 3rd year of the land reform, the lag outcome of the land system reform may decline the income for land renting-out rural households.

To encourage more participation in the country market, policymakers tin provide more training to young farmers to cultivate the "professional farmers" who can empathize technology. Improved understanding of agricultural technologies will heighten the land managers' ability to operate and manage large land areas and too as reduce the potential loss caused by blind investment in land. The cultivation of more "professional farmers" can boost the land transaction activities in land markets and improve the productivity of state because skilled farmers are more likely to rent in the country. Other than providing technical training to farmers, policymakers can also use subsidies and provide more than off-farm chore opportunities to encourage more rural farmers to rent in and rent out the land. More land transaction activities in the rural area would, in the long run, assist increment the productivity of farmland considering skilled farmers are more likely to hire in land for scale farming. Meanwhile, unskilled farmers are more likely to rent out the country for other income opportunities.

Nosotros should interpret some results of this study with caution. Our results show that the income level of renting-out households is lower than those who do non participate in the land rental market. However, it does not mean that China'southward land reform is not successful. The income of renting-out households may, in the kickoff identify, be lower than those who do non rent out their land. Country reform potentially frees farmers from agriculture to discover off-subcontract jobs that can earn them college income. During the early years of the state reform, increased transaction costs may exist the short-term frictional institutional price. However, the transaction cost would be reduced or eliminated when well-nigh country in the market has been hire in or rent out. The limitation of the current study is that our information are just from the land reform demonstration zones. Subsequent studies tin can aggrandize the sample areas with different levels of economical development and carry out research based on larger sample information. With more data nerveless, the analyses tin be conducted for farmers with different country sizes, which can provide a deep insight into the effect of farmland rental markets on the income of households with various farm sizes.

Supporting information

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Source: https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0256590

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