1. Introduction
Agricultural machinery commonly acts as a substitute for the labor force, due to rapidly increasing non-farming wages in the context of industrialization and urbanization. Recently, such a process has been experienced in many developed countries [
1,
2,
3,
4,
5].
China is the fastest growing economy in the world, with many rural laborers joining the non-agricultural sector in the past decades and with labor migration significantly improving the income of rural households [
6,
7]. However, the agricultural labor shortages that result from real wage increases have seriously challenged China’s grain production. Therefore, it is crucial to enhance mechanization operations to improve grain productivity [
8,
9,
10].
Rice, wheat, and maize are China’s staple grains, accounting for 85% of the total sown area of grain crops [
11]. Grain farms are typically characterized by small-sized and family-based operations, most of the farms are unlikely to purchase professional machinery, such as a combine harvester, due to their expensive price and low usage rate; instead, farm operators tend to buy machinery services from mechanization services provider [
12]. Since a widespread regional difference occurs in the farming schedule in China, service providers are able to operate several months through migration, and this model of service supply significantly improves a farm’s access to mechanization services [
13]. This mechanization service mode was initially derived from cross-regional mechanized grain harvesting in the Jiangsu province [
14]. Now, cross-regional mechanization services have been popularized in most of China’s rural areas, and services have been extended to most Sections of crop farming, including land preparation, sowing, and harvesting. According to the 13th Five-Year Plan for the Agricultural Mechanization Development of China, the comprehensive level of mechanization for wheat production, rice production, and maize production are 93.7%, 78.1%, and 81.2%, respectively [
15].
Under the Household Responsibility System (HRS), initiated in the 1980s, a rural household was allocated multiple plots that are small and spatially dispersed, based on a principle of egalitarianism [
16], and these small plots seriously hinder the application of large-scale machinery. Hence, agricultural machinery is still dominated by medium and small-scale machinery in most of China, and with the increase of non-agricultural wages, machinery service providers also call for a larger farm size to improve the efficiency of mechanization and thus increase income.
Increasing the labor productivity of the grain industry is critical for sustainable food production and supply [
17], given the extremely low per capita land resource endowment in China [
18]. For this purpose, an important strategy is to enlarge farm size to improve mechanization efficiency. However, until now, few studies have estimated a moderate farm scale from the perspective of machinery utilization, even though many scholars have highlighted that a considerable increase in farm size is the key to efficient mechanization [
19,
20]. Indeed, an appropriate operation scale exists for achieving the optimal efficiency of machinery utilization when this machinery is only for private use [
21,
22].
Obviously, this situation is not applicable in the case of Chinese farmers because most of the family farms realize mechanization through the prevailing machinery services. As a result, the scale economies on machinery are mainly coming from savings on machinery service expenditures. Several studies have found an increasing cost advantage of large farms in mechanized farming. For example, an increase in farm size and reduction in land fragmentation contributes to reduced production cost and improved technical efficiency [
23,
24]. Moreover, a negative relation between plot size and average cost also has been found more recently, indicating the presence of a scale economy within a plot [
25]. In general, these studies mainly examine the cost advantage of large farms derived from scale-dependent mechanization. Specific to machinery services cost, Gu et al. [
26] assumed a linear relation between the machinery services cost and farm size and estimated this relation with a linear model. Indeed, because of the presence of diminishing marginal utility, the potential nonlinear relation between the farm size and per area machinery services expenditures (PAMSE) was largely neglected in the previous study.
How large a grain farm is appropriate in China? This issue has aroused hot debates in the academic community. The literature provides diverse results based on different evaluation standards. A representative consideration is that the agricultural income of professional farmers should be roughly equal to the social average income in the urban non-agricultural sector, and a correspondingly appropriate farm size is generated following this principle. According to this principle, Songjiang, a suburban area of Shanghai, was estimated to be a moderate size of 100 mu in 2014 [
27]. Further, because of remarkable regional differences, the literature suggested that a moderate-scale operation should be different according to land resource endowment and local economic development levels [
28]. In addition, other studies contributed to this issue from multiple analysis perspectives and objectives, including the maximization of land productivity [
29], per area profit maximization [
30], and optimum technical efficiency [
31,
32], in accordance with different standards, various results can be obtained.
To summarize, although previous studies have found a negative relation between the farm scale and machinery costs owing to the presence of scale economies, the nonlinear relation between them has been largely neglected. More importantly, few studies have paid attention to an estimation of moderate farm scale from the perspective of mechanization supply cost, particularly in Chinese grain production, which has a socialized service system in mechanization supply. Therefore, this study contributes to the literature in two ways. First, using the database from the 2015 China Rural Household Panel Survey (CRHPS), we tested the nonlinear impact of the farm size on the PAMSE based on the threshold model, and second, we further focused on the potential moderate operational scale when the marginal effect of the farm size expansion on the PAMSE is fairly small. The result can enhance our understanding of the influence of farm size on mechanization efficiency and offer policymakers a new method to formulate land policy to promote moderate-scale operation and improve grain production efficiency, which can provide new insights into food security and agricultural sustainability.
The rest of this paper is structured as follows. The next section introduces the theoretical hypothesis and model specification;
Section 3 presents data resources and statistical description; the fourth section reports the empirical results; the following section discusses the results, and in the last section, the conclusions and policy implications are illustrated.
3. Data and Statistical Description
3.1. Data and Samples
Data used in this research were obtained from the CRHPS conducted by Zhejiang University in 2015; this source is a nationally representative survey comprising all provinces on mainland China, except for Xinjiang and Tibet. In the sampling process, a three-stage (county or district, village, and household) sampling design was implemented to ensure a representative database. In the first stage, the whole counties were split into ten groups based on the per capita gross domestic product, which was specified as a stratified index, and then 363 counties or districts were randomly selected from 29 provinces (
Figure 2). Furthermore, 22,535 households from 1439 villages or residential committees were randomly extracted as respondents in the above counties or districts. In this survey, household information on demographic features, agricultural production, family assets, family incomes, and expenditures were collected.
Since our objective was to investigate the relationship between the farm size and PAMSE, we imposed a series of restrictions on the full sample to generate a more accurate household database. First, given the backward mechanization of the cash crop industry, we included only grain farms, on which rice, wheat, or maize are grown; second, the samples with a zero farm size (measured by sowing area) or machinery services expenditures were excluded, and then we excluded the bottom and top 2.5% machinery services expenditures, which may result from low-level mechanization or statistical problems; third, we further removed some observations with missing values in other important variables. After the above-described data cleaning procedures were complete, the samples used in this study consisted of 2133 grain farm observations.
3.2. Statistical Description
The sample was divided into 27 groups according to the farm size and sample size, and the PAMSE was examined in every size group; the results are presented in
Table 1. Note that for 72% of the sample the farm size was less than 10 mu, and approximately 90% of the households operated a grain farm of less than 20 mu in our sample; moreover, the farm size averaged 11.36 mu. The data showed remarkable differences in the PAMSE among the different groups of farm sizes. For example, the PAMSE averaged 370.30 Yuan/mu when the farm size is less than 1 mu, whereas the cost was reduced to 37.45 Yuan/mu when the farm scale is larger than 100 mu. In general, these data show a decreasing tendency of the PAMSE with an expansion in the farm scale; specifically, the cost reduction occurred at a higher rate when the farm scale was small, and this rate declined as the farm size increased. That is, the cost reductions in machinery services become progressively smaller with the continuous expansion of farm scale. However, this phenomenon calls for a strictly causal identification test.
Table 2 present the definitions and descriptive statistics of the controlled variables analyzed in this research. In terms of farm characteristics, the data shows that 77% of the households operated more than one parcel of cropland, indicating widespread land fragmentation in rural China. Regarding the attributes of the largest household parcels, 76% of the respondents reported that their largest parcel was supportive for large-scale mechanization; 71% of the households reported that their largest land was adjacent to the tractor road, and the quality of the largest parcel ranged between fair to good on average. In addition, the data revealed that 17%, 5%, and 28% of the households only grew rice, wheat or maize, respectively, and 50% of the farmers in the sample planted a mixture of these crops. For the head of the household, the average age was approximately 53, and the average education level ranged from primary education to secondary education, with 79% of the head of household believing themselves to be healthy. In terms of family characteristics, on average, approximately two adult labors were engaged in agricultural production in a household, and the total values of agricultural machinery and equipment in a household averaged 2711.86 Yuan.
In terms of regional characteristics, 52% of the households are located in a county on the plains, where the proportion of mountainous area is less than 30%; moreover, according to the combination of geographic location and economic development, our sample can be subdivided into 4 province groups: east China (Beijing, Tianjin, Hebei, Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, Hainan), central China (Shanxi, Henan, Hubei, Hunan, Jiangxi, Anhui), west China (Sichuan, Guangxi, Guizhou, Yunnan, Chongqing, Shaanxi, Gansu, Inner Mongolia, Ningxia, Qinghai), and northeast China (Liaoning, Jilin, Heilongjiang). Thus, the proportions of our sample from east China, central China, west China, and northeast China were 29%, 35%, 23%, and 13%, respectively.
6. Conclusions and Policy Implications
Using the database from the 2015 CRHPS conducted by Zhejiang University, this study investigates the impact of the farm size on the household’s PAMSE. In contrast to previous studies, the contributions made here are that the structural change point of farm size is estimated endogenously instead of by an empirical judgment, and a nonlinear relation between the farm size and PAMSE is examined using a threshold model. Furthermore, we tried to determine the moderate operation scale in China’s grain production from the perspective of mechanization cost. This study lends important insights to recent reforms for farmland systems aimed to promote moderate-scale operations and improve food production efficiency in China.
Our findings suggest that significant multiple threshold effects of farm size exist in the PAMSE, with the farm size being negatively associated with the PAMSE in all cases. Along with farm size expansion, the effect of the farm size is reduced, which follows the law of diminishing marginal utility. In particular, if the farm size exceeds the threshold of 50 mu, a 1 mu increase in the farm size can only lead to a 0.3% decrease in the PAMSE; thus, a farm scale of 50 mu can be viewed as an instructive value to develop family farms with a moderate scale under the current comprehensive mechanization level and farmland system in China. During further analysis regarding land parcels, we found that grain farms are experiencing land consolidation in the process of farm size expansion. Operators of larger farms (i.e., >50 mu), especially, are presenting strong demands to enlarge parcel areas, and this finding provides important evidence that parcel area expansion is a key source of scale economies in machinery utilization.
The results of the study provide important implications for policymaking. First, because of the ubiquitous scale economies of farm size expansion, persistent efforts should be devoted to improving farmland circulation efficiency and developing scale farms. More importantly, governmental supporting policies, such as agricultural subsidies, need to attach more importance to large-scale farms (i.e., >50 mu), because large farm operation is more rationally economic, and results in a strong inclination for land consolidation and efficient operation. Second, since the parcel area directly affects the working efficiency of machinery, full rights should be granted to farmers for the contracted farmland, to enable them to obtain higher returns from land assets. Correspondingly, this also provides lessee households more full rights to implement land consolidation and reduce land fragmentation in the process of farm size expansion.
This study only provides a preliminary discussion regarding the moderate operation scale of grain production from a national perspective. For a lack of detailed data, the moderate operation scale for regions with different terrains and for different crops are not included in this study. Moreover, because the detailed data for each kind of mechanized operation is not available in the database, the PAMSE is calculated by the unit cost for services, including all mechanized operations, which introduced uncertainties. In further research, we will carry out a more detailed survey to enhance our data sources to explore this issue more explicitly. An analysis of moderate operation scale according to local conditions will be strengthened in order to gain more tailored results. In addition, the scarcity of land resources and land fragmentation are more serious in mountainous area in China; therefore, the size of farms in mountainous areas is generally smaller than that in plain areas, and most large farms are located in plain area. The samples used in this study are in line with this regional distribution of farm size. Thus, the samples can be considered as national representatives of the characteristics of farm households, and the issue of sample bias can be ignored.