Impact of the Cultivated-Land-Management Scale on Fertilizer Reduction—Empirical Evidence from the Countryside of China
1
China Academy for Rural Development, Zhejiang University, Hangzhou 310058, China
2
School of Public Affairs, Zhejiang University, Hangzhou 310058, China
*
Author to whom correspondence should be addressed.
Land 2022, 11(8), 1184; https://doi.org/10.3390/land11081184
Submission received: 10 July 2022
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Revised: 22 July 2022
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Accepted: 27 July 2022
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Published: 28 July 2022
(This article belongs to the Section Land – Observation and Monitoring)
Abstract
:Reducing the application of chemical fertilizers can improve the quality and promote the sustainable use of cultivated land, which is part of the green and sustainable development of agriculture. Based on the 2019 China Rural Household Panel Survey data, this article evaluated the impact of cultivated-land-management scale on fertilizer reduction via the OLS regression method. The results showed that, after controlling for other factors, the scale of cultivated land management is a strong factor affecting the intensity of fertilizer application by Chinese farmers. According to the results of quantitative analysis, the amount of fertilizer applied per hectare decreased by 20.6% for every 1 ha increase in the average grain sown area per household. The study also found that employing workers in agricultural production and operation can help achieve the aim of fertilizer reduction, but the fact that the head of the household is male, the increase in total household income and the increase in the proportion of household agricultural labor are not conducive to fertilizer reduction. A mechanism-of-action test showed that the expansion of the scale of cultivated land management can drive the reduction of chemical-fertilizer use by urging farmers to adopt agricultural technology and mechanized fertilization. Extensive research found that the fragmentation of cultivated land increased the amount of fertilizer applied per hectare by farmers. Therefore, the fragmentation of cultivated fields is a barrier to decreasing fertilizer application.
1. Introduction
Cultivated land is the basic resource and condition for human survival. However, the extensive use of chemical fertilizers has seriously threatened the quality and safety of cultivated land in recent years. China is not only the world’s largest fertilizer producer and consumer but also ranks among the top in terms of fertilizer-use intensity around the world. According to the statistics of the Food and Agriculture Organization of the United Nations, in 2019, China’s agricultural chemical-fertilizer-application amount was 47.55 million tons, and the agricultural chemical-fertilizer application per unit area was 350.50 kg/ha, far exceeding the internationally recognized safe upper limit of 225 kg/ha for chemical fertilizer application [1]; it was the main source of agricultural non-point-source pollution. At the same time, the current effective utilization rates of nitrogen, phosphate and potash fertilizers in China were only 33%, 24% and 42%, respectively [2]. The long-term excessive input and inefficient use of chemical fertilizers will not only destroy the soil structure, lead to soil hardening and acidification, nutrient imbalance, the deterioration of biological characteristics, increase the cost of agricultural production and hinder the sustainable development of agriculture [3] but also pollute the air and water sources, reduce the yield and quality of crops and ultimately endanger human health [4,5]. Therefore, the Chinese government attached great importance to the problem of agricultural non-point-source pollution and actively promoted the reduction of chemical fertilizers and soil-pollution control. In 2015, the Ministry of Agriculture and Rural Affairs issued the “Action Plan for Zero Growth of Fertilizer Use by 2020”. In 2022, the State Council issued the “14th Five-Year Plan for Promoting Agricultural and Rural Modernization”, which clearly proposed to effectively curb agricultural non-point-source pollution and ensure a continuous reduction in the use of chemical fertilizers by 2025.
Farmers are the microsubjects of China’s agricultural production, and the amount of fertilization is the result of farmers’ individual rational decisions. The reduction of chemical fertilizer application and the realization of agricultural sustainable development goals depend on the transformation of farmers’ production behavior. Therefore, we first need to understand what factors influence the intensity of fertilizer application by smallholder farmers. The existing research on the influencing factors of farmers’ chemical-fertilizer-application behavior can be summarized into the following three aspects: first, farmers’ individual and family characteristics, such as age, gender, family size, education level, attitude perception, risk preference, non-agricultural employment, etc. [6,7,8]; second, the characteristics of production and operation, such as planting structure, the proportion of the family farming labor force, whether employees are employed in agricultural operations, whether information technology is used, the degree of commercialization of agricultural products, etc. [9,10,11,12]; third, the external environment, such as technical training, the stability of land-property rights, agricultural subsidy policy, etc. [13,14,15].
Land is the most important input factor in agricultural production. Land management characteristics such as the scale of land management, the degree of land fragmentation and land rent had an important impact on the fertilizer application behavior of farmers [16,17,18]. Among them, the logic of realizing fertilizer reduction by expanding the scale of cultivated land management has received widespread attention from the academic community. Existing studies have pointed out that farmers’ production investment decisions mainly consider cost and benefit, and the small scale of land management may lead to insufficient incentives for long-term investment income [19], and improving economies of scale through increasing land can effectively motivate farmers to make long-term production investment and adopt chemical-fertilizer-reduction technology [20]. Some scholars confirmed the effect of fertilizer reduction on the scale of cultivated land management at the empirical level. For example, Liang et al. [21] used the data on 1314 rice farmers in the main rice production area of Hubei Province, China, and found that the management scale of rice has a significant negative impact on the amount of fertilizer applied; Ju et al. [22] analyzed the relationship between land management scale and farmers’ fertilizer input using data from the National Bureau of Statistics of China and also found that, with the expansion of the scale of farmers’ management, the amount of fertilizer input decreased rapidly; Wu et al. [23] used the panel data of 74 countries from the 1960s to the early 2000s found that one standard deviation (SD) increase in farm size reduced fertilizer use by 102% of its SD. However, some studies also believed that with the expansion of the management scale, the problem of the excessive application of chemical fertilizers by farmers had not been effectively alleviated and had even aggravated the short-term chemical-fertilizer-application behavior of farmers [24]. It can be seen that the academic community has not yet reached a consensus on whether the large-scale management of cultivated land can promote the reduction of chemical fertilizers.
Can expanding the scale of cultivated land management reduce the intensity of fertilizer application by farmers? If it can, what is the specific mechanism of action? This article used the 2019 China Rural Household Panel Survey database of Zhejiang University to conduct research on the above problems, in order to provide ideas for solving the problem of excessive fertilizer input and promoting green agricultural production.
This research contributes to cultivated land management and fertilizer reduction in the following ways. Firstly, we empirically studied the impact of the scale of cultivated land management on fertilizer reduction based on the national representative farmer-household data. Although some studies have used the microdata of a specific region of China to study this problem, whether the research conclusion is suitable for China as a whole remains to be discussed. Our sample well covered the three regions of China’s east, middle and west, and the research conclusions obtained were more universal. Secondly, we introduced the dummy variables of crop type into the econometric model to control the differences in the amount of fertilizer per unit area of different crops, so that the obtained estimation results were more accurate. Many studies did not distinguish the types of crops in detail. Thirdly, we deeply discussed the impact mechanism of the expansion of the scale of cultivated land management on fertilizer reduction and used large-scale microdata to empirically test the impact path. In fact, the discussion of relevant mechanisms in the existing studies was limited to theoretical reasoning and lacked rigorous empirical analysis.
2. Theoretical Analysis and Research Hypothesis
2.1. Cultivated-Land-Management Scale, Agricultural Technology Adoption and Fertilizer Reduction
Researching and developing technologies and training farmers are the mainstream practices to achieve fertilizer reduction [25]. However, the scale of cultivated land has become an important factor limiting the widespread adoption of these new technologies and new knowledge. Agricultural production, like industry, has “economies of scale” [26]. A large part of the adoption of fertilizer-reduction technologies (e.g., straw-returning technology, water and fertilizer integration technology and soil testing and formula fertilization technology, etc.) in agricultural production are learning costs that do not change with the increase in the scale of operations. Therefore, the average cost per unit of cultivated land will decrease as the scale increases. When the scale of cultivated land management is small, it is uneconomical to increase the technology learning cost. It is a natural and rational behavior for individual farmers to reject new technologies, because learning new technologies may prevent them from going out to work to obtain higher non-agricultural income. With the expansion of the scale of cultivated land management, the learning cost per unit area decreases and the total income increases, and rational farmers will learn to adopt the fertilizer-reduction technology [27]. In China, farmers with a small scale of cultivated land management often take part-time jobs, take agriculture as a sideline, do not devote enough energy to agricultural production and mainly rely on extensive production methods [28]; when the scale of farmland is large, part-time farmers will turn into specialized agricultural operators, agricultural income becomes the main income of the family and the cost of chemical fertilizer application is a key factor affecting agricultural income. Therefore, it is a rational choice to adopt chemical-fertilizer-reduction technology to reduce the amount of chemical fertilizer application to reduce costs.
2.2. Cultivated-Land-Management Scale, Mechanized Fertilization and Fertilizer Reduction
The scale of cultivated land management will affect the mechanization adoption behavior of farmers [29]. Small-scale land management can hinder the application of agricultural machinery. Existing studies pointed out that the small scale of land limits the improvement of the total power of agricultural machinery, increases the material cost of using machinery, restricts farmers’ investment in agricultural machinery and equipment and hinders the resource input and utilization efficiency of agricultural mechanization [30]. In this case, farmers usually use artificial fertilization. In order to save labor costs, farmers will reduce the frequency of fertilization and increase the amount of fertilization each time, which often leads to the excessive application of chemical fertilizers. Conversely, the larger the scale of farmers’ land management, the more they can exert the scale effect of agricultural machinery, reduce unit operating costs and transaction costs and are more conducive to mechanized fertilization [31]. On the one hand, the mechanized fertilization method can avoid the uneven and non-standard problems of artificial fertilization, reduce losses through precise application, effectively improve the application efficiency of chemical fertilizers and promote the reduction of chemical fertilizers [32]; on the other hand, the use of intelligent agricultural machinery can also improve the traceability of chemical fertilizers consumption, significantly increase the credibility of the “green” propaganda of agricultural products, achieve high quality and good prices and, in turn, encourage farmers to reduce fertilizers.
Based on the above analysis, this article proposed the following research hypotheses:
Hypothesis 1.
The expansion of cultivated land management scale can promote fertilizer reduction.
Hypothesis 2.
The expansion of cultivated land management scale can promote the adoption of agricultural technologies by farmers, thereby reducing the amount of chemical fertilizers applied.
Hypothesis 3.
The expansion of the scale of cultivated land management can promote farmers to adopt mechanized fertilization, thereby reducing the amount of chemical fertilizer application.
3. Data Sources, Variables Definitions, Model Settings
3.1. Data Sources
The data used in this article was the 2019 China Rural Household Panel Survey (CRHPS). The survey adopted a stratified, three-stage and population-scale proportional (PPS) sampling method. In the first stage, counties in the country were divided into 10 tiers based on per capita GDP, and sample counties were randomly selected by stratification. In the second stage, sample villages were randomly selected from sample counties. In the third stage, sample farmers were drawn from the sample villages. The survey involved a rural sample of 21,815 households, with 69,256 people from 29 provinces (cities and districts) in China, with national and provincial representation [33]. The content of the questionnaire is comprehensive and informative, including the basic structure of the family, agricultural production and operation, land use and circulation, etc. Among them, agricultural production and operation items include information such as crop planting and fertilizer application, and land use and circulation include information such as the area and usage of cultivated land, which provided good data support for this article to study the influence of the scale of cultivated land management on fertilizer reduction. In order to achieve the research purpose of this article, we retained farmers who only cultivated the three main food crops (rice, wheat, and corn), and eliminated farmers whose key variables were missing. After data collation, 5031 valid farmer sample data were finally obtained, including 1538 households in the eastern region, 1951 households in the central region and 1542 households in the western region.
Appendix A presents the basic characteristics of the sample farmers (Table A1). Statistics showed that most of the household heads were over 50 years old, of which 33.19% of the respondents were 50–59 years old and 42.24% were 60 years old and above. This showed that the aging trend of China’s agricultural labor force is obvious. The heads of households are mainly male, accounting for 87.91%. A total of 9.62% of the respondents never attended school, and only about half of the household heads (52.00%) completed compulsory education in China. The sample reflected that the educational level of China’s agricultural labor force is relatively low. The scale of the cultivated land management of the sample farmers is less than 1 ha (83.32%), and the number of farmland plots is more than two (64.46%), indicating that a considerable number of farmers have relatively fragmented farmland. Most of the sample farmers have less than three family farming laborers (92.72%). The above statistical results are consistent with the development status of China’s rural areas.
3.2. Variables Description and Descriptive Statistics
3.2.1. Explained Variables
The intensity of fertilizer application is measured using the amount of fertilizer applied per hectare of cultivated land. It should be noted that, in this study, the fertilizer application intensity was logarithmized in the estimation process to alleviate the potential heteroscedasticity problem of the model. In order to better examine the impact of the scale of cultivated land management on fertilizer reduction, this study also used the amount of fertilizer expenditure per hectare of cultivated land as an explained variable to conduct robustness tests.
3.2.2. Explanatory Variables
The scale of cultivated land management is measured by the area of grain sown.
3.2.3. Mechanism Test Variables
In order to deeply analyze the influence path of the scale of cultivated land management on fertilizer reduction, this article selected two mechanism test variables, namely whether to adopt agricultural technology and whether to adopt mechanized fertilization. As for whether to adopt new agricultural technologies, the questionnaire did not directly ask but did ask “did your family obtain some agricultural technical guidance in the process of agricultural production?”. Considering that the prerequisite for farmers to adopt agricultural technology is to accept technical guidance, this study used this question to measure the level of the adoption of agricultural technology. Regarding whether to adopt mechanized fertilization, this is based on the question in the questionnaire “Which parts do you use machinery in planting crops?”, the options include “1. Cultivation/fertilization; 2. Sowing; 3. Harvesting; 4. Transportation; 5. Spraying pesticides; 6. Not using machinery”. Considering the wide application of technology for manuring and sowing simultaneously of seed and fertilizer of grain crops, those who choose cultivation/fertilization or sowing are considered to adopt mechanized fertilization, while others are considered to not adopt mechanized fertilization.
3.2.4. Control Variables
By reviewing existing studies, it can be seen that the individual characteristics of the household head, family characteristics, crop type and location also affected the fertilizer-reduction behavior of farmers. Therefore, this study selected four levels of control variables. Specifically, the individual characteristic variables of the household head include age, gender, education level and physical condition; the family characteristic variables include the total household income, the proportion of the household agricultural labor force, whether there are village cadres in the family, whether the family has agricultural machinery and whether to employ workers in agricultural operations. The dummy variables of crop types include the three main food crops, which are divided into seven categories, namely rice, corn, rice–wheat, rice–maize, wheat–maize and rice–wheat–maize, with planting wheat-only as a reference. Considering that there may be differences in the topographic and climatic conditions in different provinces, we also control the provincial dummy variables. The definitions and descriptive statistics of the main variables are shown in Appendix A (Table A2).
3.3. Model Settings
3.3.1. Benchmark Regression Model
The core question of this study is whether the expansion of the scale of cultivated land management can help reduce the amount of fertilizer applied by farmers. Since the explained variables are continuous variables, this article used a multiple linear regression model (OLS) for empirical testing. The specific model settings are as follows:
Fertilizer = β0 + β1Scale + β2Control + ε
In Formula (1), Fertilizer is the explained variables, which represents the amount of fertilizer applied per unit area of cultivated land. It is logarithmic in the regression. Scale represents the scale of cultivated land management, which is the core explanatory variables of this study; Control are control variables that affect the fertilizer application of farmers, including individual characteristics, family characteristics, crop-type dummy variables and regional dummy variables; ε is a random disturbance term that obeys a normal distribution. β0 is the intercept term, and β1 is the estimated coefficient of the scale of cultivated land management, which is the focus of this study.
3.3.2. Mechanism Test Model
In order to further investigate whether the expansion of the scale of cultivated land management promotes the adoption of agricultural technology and mechanized fertilization, thereby reducing the amount of chemical fertilizer applied per hectare, this study combined the previous theoretical analysis to test the mechanism between the scale of cultivated land management and fertilizer reduction. It is set as follows:
M = α0 + α1Scale + α2Control + ε
In Formula (2), M are mechanism test variables, including the adoption of agricultural technology and mechanized fertilization. α0 is the intercept term, and α1 is the estimated coefficient of the cultivated land management scale. The rest of the variables are consistent with Formula (1) and will not be repeated here.
4. Results
4.1. Benchmark Regression Results
In this study, the estimation of Formula (1) is carried out by stepwise regression to test the robustness of the estimation results. Table 1 reports the estimated results of the scale of cultivated land management on fertilizer-application intensity. Column (1) is the regression result by adding the scale of cultivated land management, dummy variables of crop type and regional dummy variables. Column (2) adds individual characteristic variables on the basis of (1), and column (3) adds further family-characteristics variables. Then we replace the regional dummy variables with the provincial dummy variables. The regression results after replacement are shown in column (4). The results showed that the scale of cultivated land management in columns (1) to (4) has a significant negative effect on fertilizer-application intensity. Taking the estimated results in column (4) as an example, it is not difficult to find that the fertilizer-application amount per hectare of cultivated land decreases by 20.6% for every 1 ha of the scale of cultivated land management. Thus, hypothesis 1 of this study is confirmed.
Among the control variables, gender, total household income, the proportion of agricultural labor and whether to employ workers in agricultural production and operation significantly affect farmers’ fertilizer-application behavior. From the results in column (4) of Table 1, it can be seen that gender has a significant positive impact on the amount of chemical fertilizer applied to farmland per unit of farmers, and its coefficient passed the 10% significance test. Therefore, males are more inclined to apply more chemical fertilizers. For every 1% increase in total household income, farmers’ fertilizer application per hectare of cultivated land will increase by 4.9%, which is significant at the level of 10%. Finally, the increase in the proportion of family farming labor will lead to an increase in the fertilizer-application amount per hectare, while employing workers in agricultural production and operation has a significant negative impact on the fertilizer-application amount per hectare.
4.2. Robustness Check
4.2.1. Replacing Explained Variables
In order to ensure the robustness of the regression results, this study used the fertilizer-expenditure amount per hectare of cultivated land instead of the application amount for robustness test. Table 2 reports the estimated results of the scale of cultivated land management on fertilizer expenditure. The results showed that farmers’ input decision-making and use decision-making were consistent, and the expansion of the scale of cultivated land management can not only reduce the amount of chemical-fertilizer application but also reduce the amount of chemical-fertilizer expenditure. Specifically, taking the estimated results in column (4) as an example, it is not difficult to find that the amount of fertilizer expenditure per hectare of cultivated land decreases by 20.5% for every 1 ha of the scale of cultivated land management. It showed that expanding the scale of operation can encourage farmers to reduce fertilizer input and effectively promote the ecological protection of cultivated land. Therefore, the conclusions of this study are robust.
4.2.2. Rescreening Samples
In order to ensure national grain security, the Chinese government assigned 13 provinces [Namely Shandong, Hebei, Jiangsu, Heilongjiang, Henan, Sichuan, Jilin, Anhui, Hunan, Hubei, Inner Mongolia, Jiangxi, Liaoning] as the main grain-producing area of the country. According to statistics, in 2022, the grain output of the 13 main producing areas account for more than 70% of the country’s total grain output. Therefore, in this study, the research sample was reduced to the sample of farmers from the 13 main grain-producing areas, and Equation (1) was re-estimated to investigate the effect of the scale of cultivated land management on the amount of fertilizer application. The estimated results are shown in Table 3. It can be found that, for farmers in the main grain-producing areas, the scale of cultivated land management has a significant negative impact on the amount of chemical fertilizer applied per hectare. Therefore, the expansion of the scale of cultivated land management can still significantly reduce the amount of chemical fertilizers and their damage to soil health and loss, which further showed that the conclusions of this study are robust.
4.3. Mechanism Test Results
Theoretically, the expansion of the scale of cultivated land management mainly strengthens farmers’ chemical-fertilizer-reduction behaviors from the adoption of agricultural technology and mechanized fertilization. The above estimation results showed that the expansion of the scale of cultivated land management is conducive to reducing the fertilizer input of farmers. However, it is still necessary to further test whether the expansion of the scale of cultivated land management really promotes the adoption of agricultural technology and mechanized fertilization.
According to the previous theoretical analysis and data availability, this article has taken “whether to adopt agricultural technology” and “whether to adopt mechanized fertilization” as the explained variables and used the OLS model to regress Formula (2). The regression results are shown in Table 4, in which columns (1)~(2) show the influence of the scale of cultivated land management on whether to adopt agricultural technology, and columns (3)~(4) report the impact of the scale of cultivated land management on whether to adopt mechanized fertilization. It can be seen that the expansion of the scale of cultivated land management can significantly encourage farmers to adopt agricultural technology and mechanized fertilization. The results showed that the scale of cultivated land management can help farmers to adopt agricultural technology and mechanized fertilization, so as to reduce the amount of chemical fertilizer. Hypothesis 2 and Hypothesis 3 of this study are validated.
4.4. Extended Research
The resource endowment of more people and less land, the equal demand for cultivated land of different quality under the household responsibility contract system and a market environment where the cultivated-land transfer market was not fully developed caused serious land fragmentation problems in China, and land fragmentation increased the amount of labor input of farmers [34]. Conversely, concentrated and contiguous land can reduce the amount of chemical fertilizer applied by farmers by improving agricultural production conditions and improving the horizontal and vertical division of labor in agriculture [35]. Therefore, in this part, this study discussed the impact of the degree of cultivated land fragmentation on the application of fertilizers. Drawing on the research method of Liu and Xie [36], we used the number of household-cultivated-land plots to measure the degree of cultivated land fragmentation, and the regression results are shown in Table 5. It can be seen that the more plots of cultivated land, the more fertilizer is applied by farmers per hactare. On average, the amount of fertilizer applied per hectare increased by 1.4% for each additional plot of cultivated land. Therefore, cultivated land fragmentation is not conducive to fertilizer reduction.
5. Discussion
In this study, the large-scale survey data of 5031 farmers were selected to study the effect of the scale of cultivated land management on fertilizer reduction from the perspective of cultivated-land-management characteristics. This study not only studied the effect of the scale of cultivated land management on farmers’ chemical-fertilizer-application behavior but also empirically examined the impact mechanism of the expansion of the scale of cultivated land management on fertilizer reduction, which is comprehensive and practical. In addition, this study also discussed the impact of farmland fragmentation on fertilizer reduction. As the largest developing country in the world, the research results of China’s rural areas have strong practical significance. This article can provide reference for other developing countries to promote chemical fertilizer reduction and realize the sustainable use of cultivated land.
Through empirical research, we found that the larger the scale of cultivated land management, the lower the application of chemical fertilizer per hectare. This finding corresponds to studies done by Foster and Rosenzweig [37] and Akpan et al. [38]. Foster and Rosenzweig [37] argued that the application of fertilizer decreased with the expansion of the scale of land in India. Based on the data of 150 farmers in southern Nigeria, Akpan et al. [38] found that a unit increase in the farm size will reduce the possibility of adopting fertilizers by 13.23%. The main reason for these results is that small farmers are less organized, the adoption of new technologies has high learning costs and the lack of effective channels to transfer knowledge to farmers [23], resulting in low agricultural production efficiency, the unreasonable input of factors and the excessive input of chemical fertilizers [22]. However, the findings of this study are different from those of Bambio and Agha [24]. They believed that scale operation is not conducive to reducing the use of chemical fertilizers. The purpose of large-scale operation is to maximize profits, which increases the motivation for chemical-fertilizer investment. For the transferred land, the overall non-point-source pollution level is higher due to the changes in planting methods and planting objects. In addition, the fragmentation of cultivated land is not conducive to fertilizer reduction, which is consistent with the research of Gao et al. [39], who believed that the high degree of fragmentation is an important reason that the fertilizer-application rate of Chinese farmers is higher than the world average.
In terms of other factors, men used more chemical fertilizers than women. It is generally believed that, in the process of chemical fertilizer application, the differences in the psychological characteristics of men and women make women pay more attention to their own safety and health, so women tend to use less chemical fertilizers, which is consistent with the findings of Yuan et al. [40]. Thus, an increase in total household income will hinder the reduction of fertilizer, and the possible explanation is that households with higher income are more willing to increase agricultural productivity by increasing fertilizer input [41]. Additionally, the higher the proportion of family farming labor, the greater the intensity of fertilizer application by farmers. This is because agricultural operation income is the main source of income for such families, and the goal of agricultural production is to maximize profits and minimize risks. In order to ensure grain production, more fertilizers are used [42]. Finally, farmers who employ workers tend to reduce the amount of fertilizer used. A possible reason is that farmers who do not employ workers have to use more chemical fertilizers to make up for the lack of labor and ensure a certain amount of grain output [43], while farmers employing workers is equivalent to increasing labor input to replace fertilizers.
There are also some shortcomings in this study, which can be made up in future research. Specifically: (1) We selected the cross-sectional data of CRHPS in 2019 as the research sample of this study. However, the impact of the expansion of cultivated land management on fertilizer reduction is dynamic. Therefore, future studies can use panel data to further extend and verify the relationship between the two. (2) Based on a representative sample of rural households in China, this article studied the relationship between the scale of cultivated land management and fertilizer reduction. Whether this relationship is applicable to other developing countries remains to be explored.
6. Conclusions
This article first theoretically analyzed the effect of the scale of cultivated land management on farmers’ fertilizer-application amount and its mechanism and then used the nationally representative rural household survey data from 2019 to empirically test the influence and mechanism of the scale of land management on farmers’ fertilizer-application intensity by applying the OLS model. The main conclusions are: (1) The expansion of the land management scale promoted a reduction in the use of chemical fertilizers. Specifically, for every 1 ha increase in the average grain sown area per household, the amount of fertilizer applied per hectare decreased by 20.6%. (2) The individual household head and the characteristics of the family also significantly affected the fertilizer-application intensity of farmers. Among them, gender, total household income and the proportion of agricultural labor led to an increase in fertilizer application by farmers, while employing workers in agricultural production and operation had a significant negative impact on farmers’ fertilizer use. (3) The expansion of the scale of cultivated land management can reduce the amount of chemical fertilizers by encouraging farmers to adopt agricultural technology and mechanized fertilization. (4) The degree of cultivated land fragmentation increased the amount of fertilizer applied per hectare.
Based on the above research conclusions, the policy implications are as follows: (1) The government should guide farmers to develop appropriate-scale operations based on factors such as farmers’ management capabilities and regional resource endowments. At the same time, on the basis of the expansion of the scale of land management, localities should promote the concentration of land plots through various measures, so as to provide favorable conditions for farmers to reduce their input of chemical fertilizers. (2) Actively publicizing and promoting green agricultural technologies such as fertilizer reduction is important, as is giving play to the important role of socialized service organizations in agricultural technology promotion and farmer education. For training services with large positive externalities, relevant government departments should give certain financial subsidies. (3) Guiding the specialized development of regional planting structure, encouraging farmers to carry out a horizontal division of labor and contiguous planting, creating conditions for paying attention to the advantages of an at-scale economy of agricultural mechanization and releasing their potential for fertilizer reduction would all be helpful policies. (4) Additional benefits could come from improving the scale of the cultivated land management for farmers through land transfer, especially by encouraging contiguous transfer and land-replacement integration to reduce the degree of land fragmentation.
Author Contributions
Conceptualization, W.S. and C.Y.; methodology and formal analysis, W.S. and C.Y.; writing—original draft preparation, W.S.; writing—review and editing, C.Y. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the General Program of the National Natural Science Foundation of China (grant no. 71773113).
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Restrictions apply to the availability of these data. This research used data from Chinese Family Database (CFD) of Zhejiang University, and China Household Finance Survey (CHFS) conducted by the Survey and Research Center for China Household Finance at the Southwestern University of Finance and Economics (SWUFE), China.
Acknowledgments
The authors would like to thank the anonymous reviewers for their critical comments and constructive suggestions. Additionally, all authors are very grateful to Zhejiang University and the Survey and Research Center for China Household Finance at the Southwestern University of Finance and Economics, who provided the data.
Conflicts of Interest
The authors declare no conflict of interest.
Appendix A
Table A1.
Basic characteristics of sample farmers.
| Feature | Category | Frequency | Proportion (%) |
|---|---|---|---|
| Age of household head | under 40 | 290 | 5.76 |
| 40~49 years old | 946 | 18.80 | |
| 50~59 years old | 1670 | 33.19 | |
| Age 60 and older | 2125 | 42.24 | |
| Gender of household head | male | 4423 | 87.91 |
| female | 608 | 12.09 | |
| Education level of household head | No schooling | 484 | 9.62 |
| Primary | 1931 | 38.38 | |
| Junior High School | 2018 | 40.11 | |
| High school and above | 598 | 11.89 | |
| Cultivated-land-management scale | ≤0.33 ha | 2304 | 45.79 |
| 0.33~0.67 ha | 1402 | 27.87 | |
| 0.67~1 ha | 486 | 9.66 | |
| >1 ha | 839 | 16.68 | |
| Quantity of cultivated land | ≤2 pieces | 1788 | 35.54 |
| 3~6 pieces | 2198 | 43.69 | |
| 7~10 pieces | 588 | 11.69 | |
| >10 pieces | 457 | 9.08 | |
| Number of family farming people | ≤2 people | 4665 | 92.72 |
| 3~4 people | 348 | 6.92 | |
| >4 people | 18 | 0.36 |
Table A2.
Variables definitions and descriptive statistics.
| Variables Type | Variables Name | Variables Symbol | Variables Meaning and Assignment | Average | Standard Deviation |
|---|---|---|---|---|---|
| Explained variables | Fertilizer application intensity | Fertilizer | Fertilizer-application amount per hectare of cultivated land (kg/ha) | 986.86 | 755.93 |
| Explanatory variables | Cultivated-land-management scale | Scale | Grain sown area (ha) | 0.59 | 0.63 |
| Mechanism test variables | Adoption of agricultural technology | Technology | Whether agricultural technology guidance was obtained in the process of agricultural production: yes = 1, no = 0 | 0.155 | 0.362 |
| Mechanized fertilization | Mechanization | Whether machinery is used in cultivation/fertilization/sowing: yes = 1, no = 0 | 0.716 | 0.451 | |
| Individual characteristic variables | Age of household head | Age | Actual age of household head in 2019 | 57.03 | 10.79 |
| Gender of household head | Gender | Male = 1, Female = 0 | 0.88 | 0.33 | |
| Education level of household head | Education | No schooling = 1, primary school = 2, junior high school = 3, high school = 4, technical secondary school or vocational high school = 5, college = 6, undergraduate = 7, master student = 8, doctoral student = 9 | 2.58 | 0.92 | |
| The health of household head | Health | very good = 1, good = 2, average = 3, bad = 4, very bad = 5 | 2.92 | 1.03 | |
| Household characteristic variables | Total household income | Income | Logarithm of total household income in 2018 (yuan) | 9.90 | 1.22 |
| Proportion of agricultural labor force | Labor | Proportion of household agricultural labor force to total household population (%) | 0.54 | 0.35 | |
| Is there a village cadre? | Cadre | Is there a member of the cadre family serving as a village cadre? yes = 1, no = 0 | 0.07 | 0.26 | |
| Own agricultural machinery or not | Machinery | Whether the household owns agricultural machinery: yes = 1, no = 0 | 0.45 | 0.50 | |
| Employ workers or not | Worker | employ workers in agricultural production and operation: yes = 1, no = 0 | 0.11 | 0.32 | |
| Dummy variables of crop type | Rice | Rice | Whether rice is grown only: yes = 1, no = 0 | 0.25 | 0.43 |
| Corn | Corn | Whether corn is grown only: yes = 1, no = 0 | 0.29 | 0.46 | |
| Rice–Wheat | Rice–Wheat | Whether only rice and wheat are grown: yes = 1, no = 0 | 0.03 | 0.16 | |
| Rice–Corn | Rice–Corn | Whether only rice and corn are grown: yes = 1, no = 0 | 0.13 | 0.34 | |
| Wheat–Corn | Wheat–Corn | Whether only wheat and corn are grown: yes = 1, no = 0 | 0.25 | 0.43 | |
| Rice–Wheat–Corn | R–W–C | Are all three food crops grown: yes = 1, no = 0 | 0.01 | 0.11 |
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Table 1.
The effect of the scale of cultivated land management on the amount of fertilizer applied per hectare.
Table 1.
The effect of the scale of cultivated land management on the amount of fertilizer applied per hectare.
| Variables | (1) | (2) | (3) | (4) |
|---|---|---|---|---|
| Scale | −0.158 *** | −0.161 *** | −0.170 *** | −0.206 *** |
| (−3.62) | (−3.64) | (−3.55) | (−3.79) | |
| Age | 0.006 ** | 0.001 | 0.003 | |
| (2.00) | (0.38) | (1.09) | ||
| Gender | 0.180 * | 0.166 * | 0.182 * | |
| (1.89) | (1.75) | (1.94) | ||
| Education | 0.030 | 0.033 | 0.045 | |
| (0.89) | (0.96) | (1.32) | ||
| Health | −0.026 | −0.023 | −0.024 | |
| (−0.95) | (−0.83) | (−0.87) | ||
| Income | 0.050 * | 0.049 * | ||
| (1.78) | (1.75) | |||
| Labor | 0.487 *** | 0.394 *** | ||
| (5.32) | (4.26) | |||
| Cadre | 0.003 | 0.016 | ||
| (0.03) | (0.16) | |||
| Machinery | −0.027 | −0.085 | ||
| (−0.47) | (−1.42) | |||
| Worker | −0.444 *** | −0.437 *** | ||
| (−4.18) | (−4.06) | |||
| Rice | 0.250 | 0.258 | 0.271 * | 0.014 |
| (1.59) | (1.64) | (1.75) | (0.06) | |
| Corn | 0.285 * | 0.307 * | 0.283 * | −0.006 |
| (1.83) | (1.96) | (1.84) | (−0.03) | |
| Rice–Wheat | 0.341 | 0.320 | 0.393 * | −0.141 |
| (1.46) | (1.36) | (1.69) | (−0.46) | |
| Rice–Corn | 0.339 ** | 0.346 ** | 0.324 ** | −0.032 |
| (2.11) | (2.14) | (2.04) | (−0.15) | |
| Wheat–Corn | 0.383 ** | 0.385 ** | 0.375 ** | 0.203 |
| (2.45) | (2.46) | (2.43) | (1.21) | |
| R–W–C | 0.351 | 0.344 | 0.363 | −0.055 |
| (1.24) | (1.21) | (1.28) | (−0.18) | |
| East | −0.478 *** | −0.499 *** | −0.516 *** | |
| (−6.08) | (−6.31) | (−6.54) | ||
| Middle | −0.045 | −0.058 | −0.089 | |
| (−0.67) | (−0.86) | (−1.31) | ||
| cons | 6.183 *** | 5.704 *** | 5.288 *** | 2.170 *** |
| (41.29) | (21.32) | (12.76) | (2.89) | |
| i.province | No | No | No | Yes |
| R2 | 0.0135 | 0.0157 | 0.0268 | 0.0619 |
| Sample size | 5031 | 5031 | 5031 | 5031 |
*, ** and *** represent significance levels of 10%, 5% and 1%, respectively, and the values in parentheses are t values calculated with robust standard errors. Unless otherwise specified, the following tables are the same.
Table 2.
The impact of the scale of cultivated land management on the amount of fertilizer expenditure per hectare.
Table 2.
The impact of the scale of cultivated land management on the amount of fertilizer expenditure per hectare.
| Variables | (1) | (2) | (3) | (4) |
|---|---|---|---|---|
| Scale | −0.114 *** | −0.157 *** | −0.262 *** | −0.205 *** |
| (−2.87) | (−3.88) | (−5.77) | (−4.07) | |
| Individual-characteristic variables | No | Yes | Yes | Yes |
| Household-characteristic variables | No | No | Yes | Yes |
| Crop-type dummy variables | Yes | Yes | Yes | Yes |
| Regional dummy variables | Yes | Yes | Yes | No |
| i.province | No | No | No | Yes |
| R2 | 0.0043 | 0.0098 | 0.0218 | 0.0616 |
| Sample size | 5031 | 5031 | 5031 | 5031 |
*** represent significance levels of 1%, and the values in parentheses are t values calculated with robust standard errors.
Table 3.
Influence of the scale of cultivated land management on fertilizer-application amount per hectare (main grain-producing areas).
Table 3.
Influence of the scale of cultivated land management on fertilizer-application amount per hectare (main grain-producing areas).
| Variables | (1) | (2) | (3) | (4) |
|---|---|---|---|---|
| Scale | −0.105 ** | −0.118 ** | −0.113 ** | −0.137 ** |
| (−2.05) | (−2.28) | (−2.07) | (−2.13) | |
| Individual-characteristic variables | No | Yes | Yes | Yes |
| Household-characteristic variables | No | No | Yes | Yes |
| Crop-type dummy variables | Yes | Yes | Yes | Yes |
| Regional dummy variables | Yes | Yes | Yes | No |
| i.province | No | No | No | Yes |
| R2 | 0.0064 | 0.0095 | 0.0266 | 0.0438 |
| Sample size | 3031 | 3031 | 3031 | 3031 |
** represent significance levels of 5%, and the values in parentheses are t values calculated with robust standard errors.
Table 4.
The results of the mechanism test.
| Variables | Technology | Mechanization | ||
|---|---|---|---|---|
| (1) | (2) | (3) | (4) | |
| Scale | 0.022 ** | 0.024 ** | 0.108 *** | 0.038 *** |
| (2.18) | (2.06) | (11.33) | (3.51) | |
| Individual-characteristic variables | Yes | Yes | Yes | Yes |
| Household-characteristics variables | Yes | Yes | Yes | Yes |
| Crop-type dummy variables | Yes | Yes | Yes | Yes |
| Regional dummy variables | Yes | No | Yes | No |
| i.province | No | Yes | No | Yes |
| R2 | 0.0478 | 0.0627 | 0.1421 | 0.2089 |
| Sample size | 5031 | 5031 | 5031 | 5031 |
** and *** represent significance levels of 5% and 1%, respectively, and the values in parentheses are t values calculated with robust standard errors.
Table 5.
Effects of the degree of cultivated land fragmentation on fertilizer-application amount per hectare.
Table 5.
Effects of the degree of cultivated land fragmentation on fertilizer-application amount per hectare.
| Variables | (1) | (2) | (3) | (4) |
|---|---|---|---|---|
| Number of plots | 0.016 *** | 0.015 *** | 0.016 *** | 0.014 *** |
| (4.00) | (3.91) | (3.93) | (3.46) | |
| Individual-characteristic variables | No | Yes | Yes | Yes |
| Household-characteristic variables | No | No | Yes | Yes |
| Crop-type dummy variables | Yes | Yes | Yes | Yes |
| Regional dummy variables | Yes | Yes | Yes | No |
| i.province | No | No | No | Yes |
| R2 | 0.0133 | 0.0154 | 0.0267 | 0.0611 |
| Sample size | 5031 | 5031 | 5031 | 5031 |
*** represent significance levels of 1%, and the values in parentheses are t values calculated with robust standard errors.
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Song, W.; Ye, C. Impact of the Cultivated-Land-Management Scale on Fertilizer Reduction—Empirical Evidence from the Countryside of China. Land 2022, 11, 1184. https://doi.org/10.3390/land11081184
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Song W, Ye C. Impact of the Cultivated-Land-Management Scale on Fertilizer Reduction—Empirical Evidence from the Countryside of China. Land. 2022; 11(8):1184. https://doi.org/10.3390/land11081184
Chicago/Turabian StyleSong, Wenhao, and Chunhui Ye. 2022. "Impact of the Cultivated-Land-Management Scale on Fertilizer Reduction—Empirical Evidence from the Countryside of China" Land 11, no. 8: 1184. https://doi.org/10.3390/land11081184
APA StyleSong, W., & Ye, C. (2022). Impact of the Cultivated-Land-Management Scale on Fertilizer Reduction—Empirical Evidence from the Countryside of China. Land, 11(8), 1184. https://doi.org/10.3390/land11081184
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