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Journal of Geographical Sciences >

2018 , Vol. 28 >Issue 1: 93 - 108

DOI: https://doi.org/10.1007/s11442-018-1461-5

Research Articles

Analysis of the coupled relationship between grain
yields and agricultural labor changes in China

  • GE Dazhuan , 1, 2, 3 ,
  • LONG Hualou , 1, 3, 4, * ,
  • ZHANG Yingnan 1, 2, 3 ,
  • TU Shuangshuang 1, 5
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  • 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 2. University of Chinese Academy of Sciences, Beijing 100049, China
  • 3. Center for Assessment and Research on Targeted Poverty Alleviation, CAS, Beijing 100101, China
  • 4. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
  • 5. Key Laboratory of Environment Change and Resources Use in Beibu Gulf, the Ministry of Education, Guangxi Teachers Education University, Nanning 530001, China

Author: Ge Dazhuan (1987-), PhD Candidate, specialized in agricultural transition. E-mail:

Received date: 2017-03-28

  Accepted date: 2017-04-25

  Online published: 2018-01-10

Supported by

Key Program of National Natural Science Foundation of China, No.41731286

The National Key Technology R&D Program of China, No.2014BAL01B05

Copyright

Journal of Geographical Sciences, All Rights Reserved
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Abstract

In this paper we establish a model that expresses the coupled relationship between grain yield and agricultural labor changes in China, and present a preliminary discussion of the coupled processes involved in changes in these factors at the county level. Thus, we develop two coefficients on the basis of county-level statistical data for grain yield and agricultural labor for the years 1991, 2000, and 2010, namely, the grain-labor elasticity coefficient (GLEC) and the agricultural labor-transfer effect coefficient (ALTEC). The results of this study show that during the transformation process of agricultural development in China, different kinds of coupled relationships between grain yield and agricultural labor changes co-existed at the same time. For example, between 1991 and 2010, counties characterized by three different coupled modes (i.e., increasing grain yield and decreasing agricultural labor, increasing grain yield and agricultural labor, and decreasing grain yield and agricultural labor) account for 48.85%, 29.11%, and 19.74% of the total across the study area, respectively. Interestingly, a coupled relationship between increasing grain yield and decreasing agricultural labor is mainly concentrated in the traditional farming areas of China, while a coupled relationship between increasing grain yield and agricultural labor is primarily concentrated in pastoral areas and agro-pastoral ecotones in underdeveloped western China. At the same time, a coupled relationship between decreasing grain yield and agricultural labor is concentrated in areas that have experienced a rapid development transition in agriculture, especially the developed southeastern coast of China. The results of this study also show that between 1991 and 2010, 1961 counties experienced a decline in the proportion of agricultural labor; of these, 1452 are also characterized by increasing grain yield, 72.38% of the total. This coupled relationship between grain yield and changes in the proportion of agricultural labor shows a stepped fluctuation and has continually strengthened over time. Data show that mean values for the GLEC and ALTEC increased from -0.25 and -2.93 between 1991 and 2000 to -0.16 and -1.78 between 2000 and 2010, respectively. These changes in GLEC and ALTEC illustrate that the influence of agricultural labor changes on increasing grain yields has gradually diminished. Finally, the results of this study reveal that the ‘Hu Huanyong Line’ is a significant boundary sub-dividing this coupled relationship between grain yield and changes in agricultural labor.

Key words： grain yield; agricultural labor; agricultural transition; labor migration; ‘Hu Huanyong Line’; coupled relationship

Cite this article

GE Dazhuan , LONG Hualou , ZHANG Yingnan , TU Shuangshuang . Analysis of the coupled relationship between grain
yields and agricultural labor changes in China[J]. Journal of Geographical Sciences, 2018 , 28(1) : 93 -108 . DOI: 10.1007/s11442-018-1461-5

1 Introduction

The agricultural labor force is indispensable and important for grain yields (Qi, 2007; Long et al., 2016; Wu, 2010). However, since the 1990s, both grain yields and the agricultural labor force within China have varied rapidly (Zou et al., 2009). Grain yields, for example, increased from 435 million tons in 1991 to 546 million tons in 2010, while the agricultural labor force decreased from 0.35 billion people to 0.27 billion people over the same period. Furthermore, the proportion of non-agricultural employment and income from agricultural labor has increased (Li et al., 2013), while the methods in which the labor force participates in agricultural production has changed markedly (Zhang et al., 2011). Against this background of changes in agricultural labor, understanding the pattern and security of grain yields, as well as their coupled relationship with labor, are key research topics (Song et al., 2001; Chen et al., 2013; Wang et al., 2016).
Although research on the dynamic relationship between grain yields and agricultural labor has continued progress, a number of main points-of-view remain controversial (Chan, 2010; Taylor et al., 2010). For example, studies have argued that the transformation of agricultural labor has had a range of varied effects on grain production. Changes in grain yield are closely related to the supply of agricultural labor, manifested in several different ways. The first of these arguments states that when the supply of agricultural labor is sufficient, any transfer will not weaken grain-producing capacity, but will enhance the environment for agricultural production and increase grain yields (Chan et al., 1969; Lin, 2010). In contrast, a second argument states that limiting the supply of agricultural labor will lead to a rise in opportunity costs and a concomitant decrease in grain yields (Lipton, 1980; Clay et al., 1998). Thirdly, given free movement of the labor market, grain production will rely on supplementary inputs from other agricultural production factors following the complete transformation of agricultural surplus labor (Oseni et al., 2009; Gu, 2013).
The relationship between grain yields and the agricultural labor force in China has been researched in detail and has encompassed several different perspectives, including the factors that influence changes in grain yields (Zhang et al., 2011), the characteristics of agricultural labor transfer (Song et al., 2001), and the impacts of agricultural labor transfer on grain yields (Yan et al., 2011). Important recent progress has been made in the areas of food security given the background of urbanization (Christiansen, 2011), transformation of agricultural production modes under labor migration (Yan et al., 2016), the relationship between structural evolution of agricultural labor and grain production (Lu et al., 2008), and the impacts of rural depopulation on grain production (Long et al., 2012; Long, 2014).
In the context of a comprehensive analysis of grain yields and agricultural labor changes, it is clear that the bulk of previous research has investigated the unilateral rather than bilateral coupling between grain yields and changes in the agricultural labor force. While a large number of small-scale case studies have been carried out, few studies have addressed regional modes and the different factors involved in changes in grain yield and the supply of agricultural labor in China. Thus, the aim of this paper is to first determine the coupled relationship between grain yields and changes in agricultural labor based on existing research. Secondly, using the data for 1991, 2000, and 2010 at the county level, we present an analysis of patterns and the coupled relationship between grain yield and agricultural labor changes in different regions of China. Third, we test for the presence of theoretical coupling models using empirical evidence in order to provide suggestions for guiding adjustments in grain production policy.

2 Materials and methods

This paper mainly focuses on the coupled relationship between grain yields and agricultural labor changes across mainland China at the county level. We reveal the coupled relationship between these factors using theoretical models and empirical tests.

2.1 The relationship between grain yields and agricultural labor

2.1.1 The coupled relationship between grain yields and agricultural labor changes
Agricultural labor is indispensable for grain production. Under classical dual economic theory, Lewis (Lewis, 1989) and Ranis-Fei models (Ranis et al., 1969) have been used to map the process of labor transformation from traditional agricultural to modern production and have revealed the necessary conditions and effects of agricultural labor transfer on grain production. Thus, existing research demonstrates that the relationship between grain yields and changes in agricultural labor is affected by supply of the latter (Lipton, 1980; Oseni et al., 2009). Therefore, changes in agricultural labor can be used to characterize supply and reveal the coupled relationship between changes in grain yields and labor. In China, since the reform and opening-up policies were enacted in 1978, a number of characteristics defined changes in agricultural labor including regional increases and decreases. Building on previous analyses, three coupled models are developed in this paper between grain yields and changes in agricultural labor.
The coupled relationship between grain yield and changes in agricultural labor conforms to a Lewis-Fei-Ranis model given the context of an agricultural labor increasing zone (Ranis et al., 1969). Thus, the coupled relationship between grain yields and agricultural labor changes basically conforms with the reverse of dual economic structure transformation (Figure 1a). In other words, increasing agricultural labor over the period between T1 and T2 has enhanced mankind’s ability to develop nature. Grain yields have therefore constantly increased as the scale of regional agricultural production has expanded as the result of increasing labor. However, at the same time, the marginal diminishing effect of grain production has also become increasingly obvious. On the basis of this model, agricultural labor productivity reaches a maximum and the effects of natural resource constraints become prominent at the point T2. Subsequent to T2, even if the volume of the available agricultural labor continues to increase, grain yields will stall and the relationship between food supply and demand will lead to severe social crises, necessitating urgent reforms of existing production relationships. As a result of this process, the coupled relationship between grain yields and agricultural labor changes enter a transitional period.
There are two coupled modes-of-relationship that concern grain yield and decreases in agricultural labor, one of which dominates in traditional agricultural zones (TAZs), while the other is prevalent in rapid agricultural transformation zones (RATZs). Different models of coupled relationships involve different processes, as illustrated in Figure 1b which highlights the coupled relationship between grain yields and decreases in agricultural labor in a TAZ. During the early stage of this process (T1), agricultural labor includes a high degree of surplus but at a low level of productivity, directly limiting grain yields. At this time, per capita grain occupancy remains low and is integrally linked to poverty in rural areas (De et al., 2005); the relationship between grain yields and agricultural labor is considered to be in an ‘antagonism’ stage at this point. In contrast, during the period between T1' and T2', urban areas come to the forefront of development and a ‘Lewis’ urban-rural dual structure is apparent. Affected by the costs of opportunity and comparative benefits, agricultural labor begins to transfer and non-agricultural employment is seen coupled with increasing non-farm incomes. This transition leads to structured employment and a gradual improvement in quality of life. Coupled with these developments, people also being able to obtain advanced technology as well as more funds which results in improvements in agricultural labor productivity and further increases in grain yields. All this has the effect of alleviating the so called ‘man-land’ and ‘man-grain’ interrelations characteristic of TAZs (Rozelle et al., 1999). Over the course of the period between T'2 and T'3, grain yields reach their highest point, G'3, as agricultural labor decreases and productivity increases. Due to rapid urbanization and industrialization, labor productivity, agricultural production technology, and management systems are all continuously innovated, while the scale and specialization of agricultural production is continuously promoted (Wang et al., 2016). At the same time, marginal declines in the effects of agricultural production also come to the forefront; after point T'3, for example, grain yields will decline because of the problem of rural ‘hollowing’ as the income gap widens between the urban and rural population. This process is accompanied by the widespread marginalization of agricultural land (Chen et al., 2009; Tian et al., 2010), which leads directly to widespread land abandonment (Chan, 2010).
The coupled relationship between grain yields and decreases in agricultural labor in RATZs (Figure 1c) conform to a dual economic structure model with respect to the relationship between the labor transfer and variations in agricultural output (Rains et al., 1969). However, both the economic basis and locations of RATZs are an improvement compared to those of TAZs, ensuring agricultural transformation. In other words, the more non-agricultural employment opportunities there are, the lower the opportunity cost to abandon grain production, which reduces the social security function of grain. In cases where declines in agricultural labor do not lead to decreases in grain yield between T1'' and T2'', inputs of other production factors compensate for the impact of decreases in agricultural labor. During the process of regional economic transformation in China, agricultural production was lower in efficiency than other kinds of production; this was then gradually replaced by other industries, and regional grain self-protection capacity declined.
Figure 1 Conceptual models illustrating the coupled relationship between grain yields and changes in agricultural labor. Coupled models in agricultural labor increasing zones (a), traditional agricultural zones (b), rapid agricultural transformation zones (c).
The three coupled relationships that exist between grain yields and changes in agricultural labor can occur simultaneously in different areas because of differences in levels of regional development and location conditions. It is also noteworthy that these three coupled models can also appear continuously in the same region over different time periods; for example, agricultural labor first increased and then decreased as the result of regional agricultural transformation, before eventually being transferred. Thus, one of the aims of this paper is to reconstruct the couplings between grain yield and agricultural labor changes which characterize differences within the same and different time periods.
2.1.2 The grain-labor elasticity coefficient (GLEC)
The GLEC can be defined as the ratio between the rate of grain yield change divided by the rate of agricultural labor change over a given time period (Zou et al., 2009; Liu et al., 2010), The GLEC is calculated as follows:
\[GLE{{C}_{i}}=\frac{GY{{R}_{i}}}{ALN{{R}_{i}}}=\frac{(G{{Y}_{it2}}-G{{Y}_{it1}})/G{{Y}_{it1}}}{(AL{{N}_{it2}}-AL{{N}_{it1}})/AL{{N}_{it1}}} \ \ (1)\]
In this expression, i denotes the county number, while GYRi and ALNRi refer to the rate of grain yield and the rate of agricultural labor number change respectively in a county, i. Thus, GYit2 and GYit1 refer to the grain yields of county i during the time periods t2 and t1, while ALNit2 and ALNit1 denote agricultural labor in county i during t2 and t1, respectively. Similarly, GLEC denotes the elasticity coefficient between grain yield and agricultural labor, which indicates a coupling relationship between grain yield changes and agricultural labor changes over the period between t1 and t2.
Thus, by analyzing changes in GLEC, the coupled relationship between grain yields and agricultural labor is revealed. In other words, if ALNR is greater than zero and GLEC is less than zero, an increase in agricultural labor and a decrease in grain yields is implied; increases in the former will have a reverse effect on the latter. Conversely, if ALNR and GLEC are both greater than zero, agricultural labor and grain yields vary in the same direction, and can explain the positive effect of increases in the former on the latter. In a case where both indexes are less than zero, agricultural labor decreases while grain output increases and the former has a positive effect on the latter. While if ALNR is less than zero and GLEC is greater than zero, decreases in agricultural labor will exert an inverse effect on increasing grain yield.

2.2 The relationship between grain yields and the proportion of agricultural labor

2.2.1 The coupled relationship between grain yields and changes in the proportions of agricultural labor
The coupled curve that expresses the relationship between grain yields and changes in agricultural labor proportion exhibits stepped fluctuations such that discrete trends are continually strengthened. In this context, agricultural labor refers to the number of people engaged in production within this sector, while proportion refers to rural employees, reflecting regional employment structure and labor transfer trends. The model shows that between T1 and T4, trends in agricultural labor passed through four ‘initial-middle-late-immoderate’ transfer stages, respectively, which determine the different coupling curves between grain yields and changes in agricultural labor proportions (Figure 2). Similarly, the coupled process between grain yields and agricultural labor proportion comprises three stages of ‘agglomeration-discretization-reaggregation’. Previous work has shown that during the early stage of agricultural transformation, the labor proportion was generally high (Lin, 1992) and the coupled grain-labor curve conformed to a ‘negative skew’. However, during the process of agricultural transformation and development, average grain yields obviously improved in concert with decreasing agricultural labor proportion and the coupled grain-labor curve continuously advanced alongside a low proportion of agricultural labor with increasing discrete trend.
Between T1 and T3, the model shows that transfer of agricultural labor had a positive effect on grain yields (Li et al., 2013) which increased across China. Similarly, between T3 and T4, excessive transfer of agricultural labor led to the accumulation of grain production into more dominant regions, while the centralization and specialization trend in grain yields increased (Wang et al., 2016). The proportion of agricultural labor in RATZs declined rapidly at this time, and originally dominant grain-producing areas were partially withdrawn from grain production. Nevertheless, underdeveloped regions with a higher proportion of agricultural labor retained some fractional grain-producing capacity because of the social security function of food (Tian et al., 2010). Results show that between T3 and T4, the declining agricultural labor proportion exerted an inhibitory influence on grain production (Heerink et al., 2007). The ongoing transfer of agricultural labor continues to threaten the safety of grain production, while the coupled relationship between grain yields and the labor proportion means that we are entering a new phase of adjustment.
Figure 2 Conceptual model illustrating the coupled relationship between grain yields and changes in the proportion of agricultural labor at the county level
2.2.2 The agricultural labor-transfer effect coefficient (ALTEC)
The transfer effects of agricultural labor include shifts from agricultural production to non-agricultural production as well as regional transboundary shifts. Thus, one of the aims of this paper is to determine the ALTEC and utilize it to describe the influence of the transfer of agricultural labor on regional grain yields. ALTEC is calculated as follows:
\[ALTE{{C}_{i}}=\frac{GY{{R}_{i}}}{ALP{{R}_{i}}}=\frac{(G{{Y}_{it2}}-G{{Y}_{it1}})/G{{Y}_{it1}}}{\left( \frac{AL{{N}_{it2}}}{RE{{N}_{it2}}}-\frac{AL{{N}_{it1}}}{RE{{N}_{it1}}} \right)} \ \ (2)\]
In this expression, i denotes county number, while GYRi and ALPRi represent rates of change in grain yield and the proportion of agricultural labor, respectively. Similarly, GYit2 and GYit1 refer to the grain yield of a county i during time periods t2 and t1, respectively, while ALNit2 and ALNit1 denote the agricultural labor number, and RENit2 and RENit1 denote the rural employees of county i during the period between t2 and t1, respectively. Values of ALTEC therefore explains the coupled relationship between grain yields and changes in the proportion of agricultural labor.
Thus, if ALTEC is greater than zero then changes in grain yields will exhibit the same trend as the agricultural labor proportion, but if grain yield increases and ALPR is greater than zero then the increasing agricultural labor proportion will have a positive effect on grain yield. In contrast, if ALPR is less than zero and grain yields are also reduced then declines in the proportion of agricultural labor will act to inhibit grain production. Similarly, if ALTEC is less than zero and ALPR is greater than zero when grain yields decrease, this could indicate that increases in the agricultural labor proportion will exert an obstructive effect on grain production. Finally, if ALPR is less than zero and the grain yield increases, decreases in the proportion of agricultural labor will exert a positive effect on grain production.

2.3 Data

The data used in this paper include agricultural labor statistics, the number of rural employees, and total grain yields for the years 1991, 2000, and 2010. Data for 1991 were provided by the China Natural Resources Data Center (http://www.data.ac.cn), while those for 2000 and 2010 come from the China County (City) Social and Economic Statistical Yearbook. Thus, with the exception of counties where statistical data is absent, this paper includes a total of 2,006 effective statistical units. The basic geographical data we used are derived from the Resource and Environment Science Data Center of the Chinese Academy of Sciences (http://www.resdc.cn/). Because administrative divisions at the county level across China were continuously adjusted between 1991 and 2010, those used in this study are adjusted against standard divisions of 2010.

3 Results

3.1 Coupling between grain yields and changes in agricultural labor

3.1.1 Coupling between grain yields and changes in agricultural labor at the county level
Characteristics of spatial coupling between grain yields and agricultural labor in China are obvious; in places where there is more agricultural labor, grain yields are higher. In addition, the ‘Hu Huanyong Line’ (the ‘Hu Line’) determines the nature of this spatial pattern (Figure 3). To the southeast of the ‘Hu Line’, agricultural labor and grain yields are higher than to the northwest, especially within river alluvial plains, while in contrast, to the northwest of this line, the proportion of agricultural labor is generally low and grain yields are very limited. These characteristic spatial couplings between grain yield and agricultural labor across China are inseparable from physical factors, including water, soil, air temperature, and heat, as well as the spatial distribution pattern of population (Figure 3).
Figure 3 Maps showing the spatio-temporal pattern in the coupled relationship between grain yields and agricultural labor at the county level over the period between 1991 and 2010
3.1.2 Spatio-temporal coupling between grain yields and changes in agricultural labor at the county level
(1) GLEC spatial characteristics between 1991 and 2000
Between 1991 and 2000, agricultural labor decreased in 1078 counties mainly located to the southeast of the ‘Hu Line’ (Figure 4a). Of these, 363 were characterized by decreasing grain yields (i.e., ALNR less than zero and GLEC greater than, or equal to, zero) and are mainly distributed in Zhejiang Province and on the eastern Shandong Peninsula. A total of 715 counties were characterized by increasing grain yields (i.e., ALNR and GLEC less than zero), mostly concentrated in areas including the Huang-Huai-Hai Plain and Sichuan Basin. At the same time, 712 counties exhibited increases in both agricultural labor and grain yields (i.e., ALNR greater than zero and GLEC greater than, or equal to, zero), mostly located in the central and western parts of Xinjiang Uygur Autonomous Region (Xinjiang), on the Yunnan-Guizhou Plateau, in the Henan-Shandong-Anhui junction area, and in the west of Sichuan Province (Figure 4d). A further 228 counties are characterized by increasing agricultural labor and decreasing grain yields (i.e., ALNR greater than zero and GLEC less than zero), mainly scattered in northern Qinghai and western Liaoning provinces. Indeed, over the time period of this survey, counties characterized by ‘increasing grain yields and agricultural labor’, ‘decreasing grain yields and agricultural labor’, ‘increasing grain yields and decreasing agricultural labor’, and ‘decreasing grain yields and increasing agricultural labor’ comprise 35.54%, 18.09%, 35.64%, and 10.72%, respectively, of the total number.
Figure 4 Maps showing spatio-temporal patterns of GLEC at the county level between 1991 and 2010
(2) GLEC spatial characteristics between 2000 and 2010
Between 2000 and 2010, results show that 1385 counties experienced a decrease in agricultural labor, mainly in eastern China (Figure 4b). Of these, 482 saw a decrease in grain yield (i.e., ALNR less than zero and GLEC greater than, or equal to, zero) and are mainly scattered in the southeastern coastal provinces and Guangxi Province, while 903 counties accounting for 45% of the total experienced an increase in grain yields (i.e., ALNR and GLEC less than zero), principally located on the Huang-Huai-Hai Plain, in the Hetao area, and on the northeastern plain. At the same time, 432 counties chiefly concentrated in Xinjiang and eastern Inner Mongolia experienced an increase in both agricultural labor and grain yields (i.e., ALNR greater than zero and GLEC greater than, or equal to, zero) (Figure 4d); of these, just 189 counties mostly distributed in eastern Tibet and in Hainan Province experienced an increase in both agricultural labor as well as a decrease in grain yields (i.e., ALNR greater than zero and GLEC less than zero). Counties at this time that are characterized by ‘increasing grain yield and agricultural labor’, ‘decreasing grain yield and agricultural labor’, ‘increasing grain yield and decreasing agricultural labor’, and ‘decreasing grain yield and increasing agricultural labor’ accounted for 21.54%, 24.03%, 45.01%, and 9.42% of the totals, respectively.
3.1.3 The evolution and classification of the coupled relationship between grain yields and changes in agricultural labor
Changes in GLEC show that the effects of agricultural labor changes on grain yields both decline and exhibit significant regional differences. Results show that between 1991 and 2010, the average GLEC value rose from 3.81 to 3.99 in counties characterized by increasing agricultural labor. This result indicates that the effect of increasing agricultural labor on grain yields is still present in less developed areas; however, between 2000 and 2010, this county type decreased to just 307 with grain yields accounting for 41.22% of the total in 2000, before falling further to 25.81% in 2010. Over the same period, the average GLEC values of counties characterized by decreasing agricultural labor increased from -2.56 to -1.76, which shows that the effect of decreases in this factor on enhancing grain production also declined. Grain yields in this county type accounted for 58.78% of total yields in 2000, increasing to 74.19% in 2010, becoming the major coupling between these two factors. Against the background of an overall decline in the availability of agricultural labor, average GLEC across China rose from -0.25 between 1991 and 2000 to -0.16 between 2000 and 2010. This increase is indicative of the positive effect of agricultural labor decreases on declines in grain production. As a result, the role of agricultural labor in promoting grain production has gradually declined in China while the role of non-labor-related factors continues to strengthen (Gao et al., 2012; Chen et al., 2013; Shao et al., 2014). Spatial patterns within the coupled relationship between grain yields and agricultural labor also reveal a number of obvious regional differences, with the ‘Hu Line’ acting as a large-scale GLEC boundary. Counties that exhibit a coupled relationship in the opposite direction are located mainly to the southeast of the ‘Hu Line’ (exception of developed areas in the southeastern coastal region of China), where agricultural labor is decreasing and grain yields are simultaneously increasing. Similarly, counties that exhibit a coupled relationship in the same trend direction are mostly concentrated to the northwest of the ‘Hu Line’, characterized by increases in both grain yields and agricultural labor (Heerink et al., 2007).
Because of agricultural transformation and development, different coupled relationships co-exist simultaneously between grain yields and changes in agricultural labor in different regions. This phenomenon is one distinguishing feature of Chinese agricultural transformation and development that is different to other countries. Indeed, coupled relationships between increasing agricultural labor and grain yields are mainly seen in under-developed pastoral regions and in the agro-pastoral ecotones of western China, while coupled relationships between increasing grain yields and decreasing agricultural labor are mainly concentrated in traditional farming areas which account for the highest total grain yields countrywide. Coupled relationships between decreasing grain yields and agricultural labor are seen in areas that have experienced rapid transitions in agricultural development, especially in developed southeastern coastal China, a region characterized by much more employment in non-agricultural sectors as well as a gradual withdrawal from grain production. Because these coupled relationships also reveal regional differences in agricultural transformation and development processes, it is necessary to formulate differentiated policies to address regional grain production security.

3.2 Coupling between grain yields and changes in agricultural labor proportions

3.2.1 Coupling between grain yields and agricultural labor proportions at the county level
Spatial coupling patterns between grain yields and agricultural labor proportions are shown in Figure 5. These data show that in 1991, the proportion of agricultural labor in China was generally high (mean: 84.12%) and that counties with high grain yields were mainly distributed in the middle and lower reaches of the Yangtze Plain, on the Huang-Huai-Hai Plain, and in the Sichuan Basin. Indeed, with the exception of the Yangtze and Pearl River deltas, major grain producing areas were also characterized by a higher proportion of agricultural labor. However, by 2000, the proportion of agricultural labor in China had fallen to 74.28%, and the coupled relationship between grain yields and proportions of agricultural labor showed obvious differences both sides of the ‘Hu Line’. Results show, for example, that the proportion of agricultural labor decreased while grain yields did not fall significantly to the southeast of this line. At the same time, the proportion of agricultural labor was maintained at a high level and grain yields were stable northwest of the ‘Hu Line’ (Figure 5). By 2010, the proportion of agricultural labor in the middle and lower reaches of the Yangtze Plain as well as in southeastern coastal provinces declined rapidly, especially in the Yangtze and Pearl River deltas, concomitant with rapid decreases in grain yields in these areas.
Figure 5 Maps showing spatio-temporal patterns in the coupled relationship between grain yields and agricultural labor proportions at the county level between 1991 and 2010
The curve illustrating the coupled relationship between grain yields and changes in agricultural labor proportions reveals stepped fluctuations (Figure 6). Taking the range in agricultural labor proportion as the abscissa, we calculated the proportion of counties and grain yields with a different range of agricultural labor compared to the total counties and grain yields, and referred to these values as ‘county proportion’ and ‘grain yield proportion’, respectively. The data presented in Figure 6 reflect dynamic changes in county and grain yield proportions for each section and show peaks within the same range as well as a trend towards downstream sections with declining peak values. Over the period between 1991 and 2000, agricultural labor force proportions greater than 80% and between 60% and 90% characterize 71.79% and 76.72% of total counties and generated 65.95% and 69.53% of total grain yields. At the same time, a synchronous peak in county and grain yield proportions appeared within the range between 80% and 90% and between 70% and 80% of the agricultural labor proportion, respectively. In 2010, the proportion of agricultural labor that fell between 40% and 60% reflects peaks in county and grain yield proportions. While the average proportions of agricultural labor in China decreased and coefficients of variation were 13.20%, 18.36%, and 29.08% in 1991, 2000, and 2010, respectively. Average grain yield proportions and standard deviations also increased over this period; all-in-all, a discrete trend that reflects a coupled relationship between grain yields and the proportion of agricultural labor was continually strengthened throughout the survey period.
Figure 6 Number of counties and grain yield proportions given differences in agricultural labor at the county level across China
3.2.2 Spatio-temporal characteristics in the coupled relationship between grain yields and changes in the proportion of agricultural labor at the county level
The coupled relationship between grain yields and changes in the proportion of agricultural labor reveals a number of distinct regional differences. Data presented in Table 1 illustrates the proportion of counties that show different coupling relationships between grain yields and changes in the proportion of agricultural labor during different periods. These data show that county-level proportions of agricultural labor decreased while grain yields increased (i.e., ALPR and ALTEC values less than zero) in more than 62% of the different periods (Figures 7a and 7b). This coupled relationship is dominant and suggests that, in most counties, transfer of agricultural labor had a positive effect on promoting grain yields. Counties of this type are mainly distributed on the Huang-Huai-Hai Plain, and also include three provinces in northeastern China and Inner Mongolia. At the same time, however, the proportion of counties characterized by both a decrease in the proportion of agricultural labor and grain yields (i.e., ALPR less than zero and ALTEC greater than, or equal to, zero) make up nearly 25% of the total and are mainly located in the Yangtze and Pearl River deltas as well as in southeastern coastal areas. These regions have been at the forefront of Chinese socio-economic development and the transfer of agricultural labor has had an obviously reverse effect on grain production (Chen et al., 2007). In addition, a small number of counties are also characterized by increases in the proportion of agricultural labor (Figures 7c and 7d), although regions where this coupling occurs do not cluster together.
Table 1 Classification statistics illustrating the ALTEC at the county level between 1991 and 2010
ALTEC 1991 to 2000 (%) 2000 to 2010 (%)
ALPR < 0 ALTEC ≥ 0 25.98 (521) 31.16 (625)
ALTEC < 0 65.2 (1,308) 62.87 (1,261)
ALPR > 0 ALTEC ≥ 0 5.88 (118) 3.54 (75)
ALTEC < 0 2.94 (59) 2.24 (45)

Note: Numbers in parentheses indicate the number of counties that belong to each coupled type

Figure 7 Maps showing spatio-temporal patterns in the ALTEC at the county level between 1991 and 2010
Results show that between 1991 and 2010, the coupled relationship between grain yields and changes in the proportion of agricultural labor exerted a positive influence on grain production, although differences in spatial patterns were also evident. Subsequent to the 1990s, more than 90% of counties experienced a decline in the proportion of agricultural labor. Data show that the mean ALTEC value rose from -2.93 between 1991 and 2000 to -1.78 between 2000 and 2010, indicating a gradual reduction in the effect of transferred agricultural labor. At the same time, a ‘non-grain’ trend also characterizes southeastern coastal regions while river delta regions have transitioned into urbanized regions from originally grain-producing areas. Because these phenomena have tended to partially weaken Chinese grain-producing capacity, if reasonable policy and measures are not enacted to guide this process then the positive effects of agricultural labor transfer on grain yields may be weakened. It is therefore necessary to protect Chinese food security from the negative impacts of excessive agricultural labor transfers (Zhang et al., 2011).

4 Discussion and conclusions

Data show that between 1991 and 2010, counties characterized by three different coupled models (i.e., increasing grain yields and decreasing agricultural labor, increasing grain yields and agricultural labor, and decreasing grain yields and agricultural labor) account for 48.85%, 29.11%, and 19.74% of the total Chinese counties, respectively. Results also show that the average GLEC for all counties increased from -0.25 between 1991 and 2000 to -0.16 between 2000 and 2010. At the same time, while average GLEC rose from 3.81 to 3.99 in counties where agricultural labor increased, grain yields also accounted for 41.22% and 25.81% of totals in 2000 and 2010, respectively. The average GLEC of counties characterized by decreases in agricultural labor rose from -2.56 to -1.76 over this period, while their grain yields accounted for 58.78% of the total in 2000 and 74.19% of the total in 2010.
We show that this coupled relationship between grain yields and changes in agricultural labor exhibits synchronous diversification. Thus, based on theoretical analyses and empirical research, the results of this paper highlight three coupled relationships between grain yields and agricultural labor in the pastoral and agro-pastoral ecotone, in traditional agricultural areas, and in the rapid agricultural transition zone. These three relationships have co-existed with one another over a long time period, while the ‘Hu Line’ represents a significant boundary delineating the coupled relationship between grain yields and changes in agricultural labor. Traditional agricultural areas characterized by this coupled relationship are mainly located to the southeast of the ‘Hu Line’ where agricultural labor decreases and grain yields increase. However, decreases in both grain yields and agricultural labor mainly characterize the rapid agricultural transition zone of southeastern coastal China, while a coupled relationship within pastoral and agro-pastoral ecotones is also seen to the northwest of the ‘Hu Line’ where both grain yields and agricultural labor increase.
The coupled curve between grain yields and changes in the proportion of agricultural labor exhibits stepped fluctuations but has been continually strengthened over time. Indeed, this coupled relationship between grain yields and changes in the proportion of agricultural labor has mainly been positive over time, indicating that the transformation of agricultural labor has had a positive effect on promoting grain yields albeit with different spatial patterns. Mean ALTEC values rose from -2.93 between 1991 and 2000 to -1.78 between 2000 and 2010, which implies that the transfer effect of agricultural labor has declined.
Compared with other countries, the agricultural labor market, land ownership, and man-land interrelations in China exhibit specific characteristics as regional socio-economic development levels as well as the social security function of grain differ markedly. The coupled relationship between grain yields and agricultural labor also exhibits significant regional differences. Thus, based on theoretical analyses and empirical research, this paper summarizes three coupled relationships between grain yields and agricultural labor changes as well as their main areas of distribution. Data show that there is a strong need to take significant geographical differences into account across China; even if regions are characterized by the same coupled relationships, staggered phenomena occur within different couplings.
Chinese food security and the transfer of agricultural labor are important current research topics. Based on the GLEC and ATLEC values, this paper describes the coupled relationship between grain yields and changes and proportions in agricultural labor. Analyses show that the overall effect of agricultural labor transfer is declining. At the same time, grain production organization mode, new types of agricultural management bodies, land resource managerial systems, and other new factors of grain production (Long et al., 2015) as well as their impacts on grain production are increasing. Given a market economic background, the factors influencing changes in grain production are also increasing, but because they interact with one another, it is difficult to quantitatively measure their degree of influence on agricultural labor. Thus, based on detailed natural environment and socio-economic data, quantitative description of the impacts of agricultural labor on grain yield changes will be a future research focus.
The coupled relationship between grain yields and changes in agricultural labor not only reflects processes of regional agricultural transformation, but also tracks the path and nature of regional spatial transformation and development. At present, nearly half of the Chinese population still lives in rural areas, and thus their survival and development remain closely associated with grain production. The social security function of grain determines the relationships between fair, efficient, current, and long-term social security and ecological protection as part of the processes of rural transformation and development. A sustainable rural development system (Long et al., 2016), which guarantees food security and promotes benign rural advancement, is thus an important factor in formulating future agricultural and rural policies in China.

The authors have declared that no competing interests exist.

References

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Chen Y, Li X, 2013. Spatial-temporal characteristics and influencing factors of grain yield change in China.Transactions of the Chinese Society of Agricultural Engineering, 29(20): 1-10. (in Chinese)Despite high attention to the stability and increase of grain production and market supply by Chinese government, grain yield in China has been undergoing a great fluctuation during the past decades, which could be a big challenge to national food security. This paper thus analyzes the spatial-temporal characteristics and influence factors of grain yield change in China since 1990 from the aspect of evolution stages and main types.Statistical indicators and spatial econometric models for panel data are introduced, which are supported by Geodata, ArcGIS, and Matlab software. It shows that the growing process of Chinese grain yield has three stages,namely stage 1990-1998, 1998-2003, and 2003-2011 respectively. Meanwhile, provinces in China can be categorized into three sets according to different supply-demand relationships, which are provinces with surplus grain(PGSG), provinces with balanced grain supply and demand(PBGSD), and provinces with insufficient grain supply(PIGS). The three separate types vary every year, with different provinces included each other. Roughly speaking, the grain production status of eastern provinces, central provinces, western provinces, and northeastern provinces is decreased, weakened, enhanced and strengthened respectively. In 2011, the PGSG, the PBGSD, and the PIGS distribute mainly at North, Middle, and South China respectively. Among all the factors that influence grain yield, the land factor has a significant positive impact, changing from strong to weak. It indicates grain production in China is increasingly dependent upon factors that contribute to per unit yield, such as technical progress, capital investment, etc. The labor factor brings an effect from positive significant to insignificant then negative significant, reflecting the change of agricultural surplus labor, rural labor structure, etc. The impact of different types of capital input varies as follows. Definitely, agricultural infrastructure investment, represented by irrigation facilities, has a strong positive effect. As a kind of labor saving capital investment, the total power of agricultural machinery brings about -ositive to negative and positive again' effect; the chemical fertilizer input,as a representative of agricultural materials, follows the law of diminishing returns to scale. Besides agricultural production factors, agricultural structure adjustment, non-agricultural industry development, and random error factors of neighboring provinces also influence the actual yield. As to the three separate types, the driving mechanism of grain yield change differs significantly, including the impact of agricultural production factors and that of macro environment. It is the mutual result of both internal law such as diminishing marginal returns and scale effect and external factors such as government regulation. Taking into account the above different driving mechanism, it will be meaningful to promote the regional division of grain production among the PGSG, the PBGSD, and the PIGS, to protect a large-scale arable land resource with a special priority to the project of arable land consolidation and protection in PGSG, to change the focal point of financial support and land consolidation to improve the efficiency of agricultural infrastructure, to solve the scarcity of agricultural labor by measures such as the cognizance of agricultural producers, and to promote agricultural mechanization with an emphasis to plain agricultural area, and which in all will help stabilize and increase grain yield in China.

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[3]
Chen Y, Li X, Tian Yet al., 2009. Structural change of agricultural land use intensity and its regional disparity in China.Journal of Geographical Sciences, 19(5): 545-556.Based on the cost-income data of farm produce and the China Agricultural Yearbook,this paper divided the intensity of cultivated land use into labor intensity and capital intensity,then analyzed their temporal and spatial change at both country and provincial scale in the period of 1980-2006.The results showed that:(1) On country scale,labor intensity of food crop farming decreased from 398.5 day/ha in 1980 to 130.25 day/ha in 2006;and shows a continuous decrease with a steep decline in 1980-1986,a slower decline in 1987-1996,and another steep decline in 1997-2006.On the contrary,capital intensity shows an increasing trend from 1980.In the internal composition of capital intensity,the proportion of seed,chemical fertilizer and pesticide input decreased from 90.36% to 73.44% ;the proportion of machinery increased from 9.64% to 26.56%.The less emphasis on yield-increasing input and more emphasis on labor-saving input are the main reasons for a slow increase of yield per unit area after 1996.(2) On provincial scale,the economically developed areas have lower labor intensity and higher capital intensity.The less developed areas have higher labor intensity but lower capital intensity.From the internal composition of capital intensity view,labor-saving input accounts for more proportion in the developed areas than other areas.That is because in these developed areas,as more and more labors engaged in off-farm work,labor input has become a constraint factor in food production.Farmers increase the labor-saving input for higher labor productivity.However,in less developed areas,the major constraint is the shortage of capital;food production is still depending on labor and yield-increasing inputs.

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[4]
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[8]
Gu L, 2013. Relative analysis of China’s grain yield and influence factors based on criterion of least absolute deviation.Transactions of the Chinese Society of Agricultural Engineering, 29(11): 1-10. (in Chinese)The relations between China- grain yield and some main factors influencing the grain yield, more present the exponential function and few exponent sign function relations. To describe with a new type of exponential production function can obtain a better result because of less error. The paper pointed out that the least absolute deviations (LAD) method, as its excellent properties, may be a best method to find the"implicit function"which is behind the data and control the data. To knead the two together, with the LAD method to fit the exponential production function, trying to find out some rules for China's grain change is a subject that is worth of exploring in theory and application. The paper introduces the LAD method and the exponential production function, establishes correlations between the China- grain yield and its 5 major influencing factors (consumption of chemical fertilizer, total sown area, total area affected by natural disaster, total agricultural machinery power, and total employed persons of primary industry). The production function model was fit with the LAD method, and the data of 1983-2011 were calculated. The results with Mae (mean absolute error) not over 3.93 million tons and Mape (mean absolute percentage error) not more than 0.87% for China- grain yield during the 29 years were obtained, and the conclusions were explained and analyzed; The analysis showed that, in the 29 years of 1983-2011, the growth of China- nation grain yield mainly depended on the consumption of chemical fertilizer and the total agricultural machinery power, of which the consumption of chemical fertilizer is still playing a positive roll up to now, while the total agricultural machinery power is dynamically in a saturated state. Theoretically it should have a "negative" effect now, but in reality it does not. The total sown area was the most influencing "positive" factor. The national grain yield may still grow further without increasing the total sown area, but increasing the sown area can rapidly boost the China- nation grain yield. The total area affected by natural disaster imposed "negative" effect on the growth; However, the trend of its influence is increasing in terms of absolute values, but is decreasing in terms of relative values. By the huge impact and lagged effects of the rapid growing of the total employed population of primary industry in China during 1983-1993 period, the reduction of the total employed population of primary industry to grain growth constituted "negative" impact. With the modernization of agriculture and urbanization development, this "negative" impact continued to reduce. These conclusions give the specific quantitative values. The paper predictes that the grain yield for year 2012 is 8 5.9133 10t, the later result indicates the absolute error is 6 1.78 10t, and the relative error is 0.3%. For year 2013, the prediction is 8 6.1148 10t. In the last the paper gives some discussion about the LAD method, the exponential production functions and so on, and is concluded that the exponential production function under the meaning of LAD criterion to describe the relationships between China's grain yield and the main effect factors, has a certain accuracy and guiding sense.

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Heerink N, Qu F, Kuiper Met al., 2007. Policy reforms, rice production and sustainable land use in China: A macro-micro analysis.Agricultural Systems, 94(3): 784-800.This paper presents a macro-icro analysis of the impact of policy reforms in China on agricultural production, input use and soil quality change for a major rice-producing area, namely Jiangxi province. This is done in three steps. First, a quantitative assessment is made of the impact of market liberalization policies on the economic environment of farm households in Jiangxi province. Econometric analyses based on provincial, national and world market data are used to explain changes in rice and fertilizer prices in Jiangxi province over time. Next, the impact of China- recent income support policy and latest price trends on farm household choices with respect to activity choice (particularly rice and livestock) and input use (fertilizers, pesticides, manure) is assessed for two villages with different degrees of market access in north-east Jiangxi province. Two village-level general equilibrium models are used to analyse household decision-making and interactions between households within these villages. The parameters are estimated and calibrated from an extensive survey held in these villages in the year 2000. Finally, the impact of land tenure policy on farm management decisions (labour, manure and chemical input use), soil quality (available P and K and total N and C) and rice yields is analysed through an econometric analysis of plot-level data for three villages. Two-stage least squares (2SLS) is used to control for interactions with yields and for feedbacks towards input use. The paper ends with a number of suggestions for policy adjustments that would reduce the problem of natural soil compaction in the research area.

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Li L, Wang C, Segarra Eet al., 2013. Migration, remittances, and agricultural productivity in small farming systems in Northwest China.China Agricultural Economic Review, 5(1): 5-23.Purpose - The purpose of this study is to explore the relationship between migration, remittances and agricultural productivity by applying the new economics of labor migration model in the context of north-west China. The specific objectives are to examine the impacts of rural out-migration on agricultural productivity in various farming systems, and whether remittances have been reinvested in agriculture.Design/methodology/approach - Cross-sectional household survey data from three townships were analyzed with the three-stage least squares (3SLS) regression model.Findings - In multi-cropping small farming systems, at least in the short run, the loss resulting from losing family labour on lower-return grain crop production is likely to be offset by the gain from investing in capital-intensive and profitable cash crop production.Originality/value - This study provides empirical evidence for the MELM theory. It expands Taylor et al's studies by comparing investment behavior and production choices among multiple farm activities, and enriches previous studies by showing that the relation between remittances and agricultural investment depends on the farm activities' profitability.

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[12]
Lin J Y, 1992. Rural reforms and agricultural growth in China.The American Economic Review, 82(1): 34-51.This paper employs province-level panel data to assess the contributions of decollectivization, price adjustments, and other reforms to China's agricultural growth in the reform period. Decollectivization is found to improve total factor productivity and to account for about half of the output growth during 1978-1984. The adjustment in state procurement prices also contributed positively to output growth. Its impact came mainly from the responses in input use. The effect of other market-related reforms on productivity and output growth was very small. Reasons for slowdown in agricultural growth after 1984 are also analyzed.

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[13]
Lipton M, 1980. Migration from rural areas of poor countries: The impact on rural productivity and income distribution.World Development, 8: 1-24.There is overwhelming evidence to suggest that past and present governmental policies in developing countries are frustrating migrants from rural areas and that rural outmigration benefits neither the migrants themselves nor the rural places of origin. In fact the rural outmigration movement worsens the overall income distribution among remaining rural persons among the migrants and between village and town. The poorest rural residents may migrate out of necessity or hope for a better future and sons of the richer farmers may migrate to urban education or urban jobs. The poorer do not have the skills to succeed; only the richer more educated migrants can succeed. The age-sex distribution of the migrants i.e. the predominant youth and maleness of the migrants tends to create a worse situation in the sending area. Sheer costs of migration work against any equilibriation through migration. The impact of absences on the sending village is analyzed. Migrant remittances do not better the economic situation of the sending village because: 1) remittances are generally small; and 2) good remittances more often go to the better-off. Even the return of the former migrants does not better the sending areas situation. Rationalization of the migrant flow requires a positive government policy toward agriculture and agricultural areas.

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[14]
Liu Y, Li Y, 2010. Spatio-temporal coupling relationship between farmland and agricultural labor changes at county level in China.Acta Geographica Sinica, 65(12): 1602-1612. (in Chinese)Cultivated land and agricultural labor force are two core elements for promoting agricultural production and sustainable rural development.During the process of rapid urbanization and industrialization in China,numerous agricultural labors transferred to non-agricultural sector and a huge proportion of farmland was converted to construction land,in particular,these changes were spatially uneven.Theoretically,coupling relationship should be found between farmland and agricultural labor change.The overspeed of farmland conversion or agricultural labor transfer may affect the sustainability of agricultural production and rural development.Policy implications may arise from systematic analysis on spatio-temporal coupling relationship between agricultural labor transfer and farmland conversion.Based on county-level statistical data of farmland and agricultural labor,this paper gives an exploratory study in this area,by using GIS technology and mathematical modeling approach.The results showed that: (1) both the total amount of farmland and agricultural labor of the 1914 studied counties increased from 1996 to 2000 and then went through a process of reduction.The amount of farmland and agricultural labor increased by 2.70% and 1.40% from 1996 to 2000,and then decreased by 1.51% and 8.18% from 2000 to 2005,respectively.(2) "Hu Huanyong Line" which links Aihui and Tengchong cities,is an important dividing line in depicting China's spatial pattern of farmland conversion and agricultural labor transfer.Within the ribbon region along this line,farmland decreased drastically due to Grain for Green Project,however,the agricultural labor transfer lagged behind severely.In the region to the northwest of ribbon region along the HU Line,the reclamation of reserve resources caused a substantial increase of farmland,and the amount of agricultural labor grew steadily.In the region to the southeast of ribbon region along the HU Line,farmland was converted to construction land generally and agricultural labor decreased rapidly.Coupling relationship between farmland conversion and agricultural labor transfer could only be found in the third region.(3) During the study periods from 1996 to 2000 and from 2000 to 2005,447 and 505 counties experienced a benign agricultural transfer in the process of farmland loss,respectively.Labor-farmland elastic coefficient (LFEC) of 90% of these counties ranged with a median of 4.58 and 2.97,respectively,which means that the efficiency of agricultural labor transfer decreased during the process of rapid farmland loss.(4) By developing a clustering method based on Self-organization Mapping (SOM) Neural Network on the software platform of ArcGIS and MATLAB,the coupling relationship between farmland conversion and agricultural labor change was divided into nine regional types,and also the control orientation for each region was put forward.Multi-scenario simulation analysis predicted that the trend value of LFEC during 2005-2015 was 2.55,and this could be a standard parameter for coordinating the relationship between farmland conversion and agricultural labor change in the next 10 years in China.

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[15]
Long H, 2014. Land consolidation: An indispensable way of spatial restructuring in rural China.Journal of Geographical Sciences, 24(2): 211-225.The implementation of new type industrialization and urbanization and agricultural modernization strategies lacks of a major hand grip and spatial supporting platform, due to long-term existed “dual-track” structure of rural-urban development in China as well as unstable rural development institution and mechanism. It is necessary to restructure rural production, living and ecological space by carrying out land consolidation, so as to establish a new platform for building new countryside and realizing urban-rural integration development in China. This paper develops the concept and connotation of rural spatial restructuring. Basing on the effects analysis of industrialization and urbanization on rural production, living and ecological space, the mechanism of pushing forward rural spatial restructuring by carrying out land consolidation is probed. A conceptualization of the models of rural production, living and ecological spatial restructuring is analyzed combining with agricultural land consolidation, hollowed villages consolidation and industrial and mining land consolidation. Finally, the author argues that a “bottom-up” restructuring strategy accompanied by a few “top-down” elements is helpful for smoothly pushing forward rural spatial restructuring in China. In addition, the optimization and restructuring of rural production, living and ecological space will rely on the innovations of regional engineering technology, policy and mechanism, and mode of rural land consolidation, and more attentions should be paid to rural space, the foundation base and platform for realizing urban-rural integration development.

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[16]
Long H, 2015. Land use transition and land management.Geographical Research, 34(9): 1607-1618. (in Chinese)With the introduction of land use transition to the academic circle of China since the turn of the new millennium, related researches combining with the characteristics of China's socio-economic development have been carried out extensively. Recently, issues related to land use transition in China have attracted interest among a wide variety of researchers as well as the government officials. Land use transition refers to the changes in land use morphology including dominant morphology and recessive morphology of a certain region over a certain period of time driven by socio-economic change and innovation. In general, dominant land use morphology refers to the quantity, structure and spatial pattern of land use, and recessive land use morphology includes land use features in terms of aspects of quality, price, property rights,management mode, input and productive ability, and function. This paper puts forward the theoretical model of regional land use transition as the following: with the socio-economic development, the transformations between different land use types during a certain period of time arise the changes of regional land use morphology pattern from strong conflict to weak conflict, i.e., coordination, which enable a new balance between different land use morphology patterns reflecting the development trend of different economic departments, and then realize the transformation of urban- rural land use system from quantitative change to qualitative change. Then, the mechanism of mutual feedback between land use transition and land management was probed based on a three-fold framework of natural system-economic systemmanagerial institution system. Generally, land use transition is affected by land management via economic measures, land resources engineering, policy and institution. Land use transition can also contribute to the adjustment of land management measures via socio-ecological feedback.Therefore, policy-makers need to adjust their land management policies taking into account the continuous change of land use morphology and different phases of regional land use transition.Under the background of urban- rural transformation development, the researches of land use transition and land management may focus on how to measure the transitions of land use dominant morphology and recessive morphology and the subsequent transition of the function of land use system, how to measure the socio-economic and environmental effects of land use transitions, how to refine the popular model of regional land use transition, and how to adjust land use transition via socio- economic and engineering measurements. Finally, the author argues that more attentions need to be paid to the recessive morphology of land use, the change of which is the key to policy and institution innovation and improving land management.

[17]
Long H, Li Y, Liu Yet al., 2012. Accelerated restructuring in rural China fueled by ‘increasing vs. decreasing balance’ land-use policy for dealing with hollowed villages.Land Use Policy, 29: 11-22.Rapid industrialization and urbanization in China has produced a unique phenomenon of ‘village-hollowing’, shaped by the dual-track structure of socio-economic development. This paper analyzes the phenomenon of ‘village-hollowing’, identifying the processes and influences that have driven their evolution, and highlighting the challenge that the locking-up of unused rural housing land in ‘hollowed villages’ presents for China in the context of concerns over urban development and food security. The paper examines the ‘increasing vs. decreasing balance’ land-use policy has been adopted by the Chinese government in response to the problem, which seeks to balance increases in urban construction land with a reduction in rural construction land. The implementation of the scheme is discussed through a case study of Huantai county in Shandong province, drawing attention to its contested and contingent nature. It is argued that the policy is a top-down approach to rural restructuring that necessarily requires the acquiescence of local actors. However, it is noted that failures to adequate engage with local actors has led to resistance to the policy, including violent protests against the demolition of housing. The paper suggests that lessons might be learned from Europe by incorporating elements of ‘bottom-up’ planning into the process. As such, the paper demonstrates that rural restructuring in China is a dynamic, multi-scalar and hybrid process that shares common elements and experiences with rural restructuring in Europe and elsewhere, but which is also strongly shaped by the distinctive political, economic, social and cultural context of China.

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[18]
Long H, Tu S, Ge Det al., 2016. The allocation and management of critical resources in rural China under restructuring: Problems and prospects.Journal of Rural Studies, 47: 392-412.Rapid and far-reaching development transition has triggered corresponding restructuring in rural China especially since the turn of the new millennium. Recently, there has been an increasing trend emphasizing regional resources in formulating rural development policy and restructuring rural areas. This paper analyzes the rural restructuring in China affected by the allocation and management of critical resources including human resource, land resource and capital, by establishing a theoretical framework of “elements-structure-function” of rural territorial system. It is argued that rural restructuring is a process of optimizing the allocation and management of the material and non-material elements affecting the development of rural areas and accomplishing the structure optimization and the function maximum of rural development system. Due to the constraints from the maintained urban–rural dualism of land ownership and household registration, the rapid rural restructuring under both globalization and the implementation of the national strategies on industrialization, urbanization, informatization and agricultural modernization, the changes of the allocation of critical resources have brought about many problems and challenges for the future development of rural China, such as the nonagriculturalization, non-grain preference and abandonment of farmland use together with the derelict and idle rural housing land, the weakening mainbody of rural development, the unfair urban–rural allocation of capital and its structural imbalance, and so on. Aiming at how to resolve the problems and adapt to the challenges, it is pivotal to restructure the rural development space, rural industry, and rural social organization and management mainbody. Furthermore, it is necessary to restructure the contours of state intervention in rural societies and economies and allocate and manage the critical resources affecting rural development, from the perspectives of integrating urban and rural resources, improving the efficiency of resources utilization, and fully understanding the influences of globalization on rural restructuring in China.

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[19]
Lu W, Mei Yan, Li Y, 2008. Regional change in China’s grain production: Effects of labor-land ratio, off-farm employment opportunities and labor compensation.Chinese Journal of Population Science, (3): 20-28. (in Chinese)From the perspectives of regional differences in population and economic development,the paper investigates the regional change and its causes in production of rice,wheat and corn since 1978 by using spatial error model and panel data of 1978-2006 from all Chinese provinces.The empirical results show that there exists an obvious regional correlation in Chinese grain production.A production increase in a province can induce an output decline in its neighbours.Besides natural and technical factors,the regional differences in man-land relation,non-agricultural employment and labour payment have significant effects on the regional grain production in China,which applies particularly to the production of rice and wheat.With growing differences in regional development,China's grain production will be transferred to and concentrated in economically less developed areas with relatively rich arable land per capita,few opportunities for non-farming employment and lower labour remuneration.

[20]
Oseni G, Winters P, 2009. Rural nonfarm activities and agricultural crop production in Nigeria.Agricultural Economics, 40(2): 189-201.Abstract Although most rural households are involved in the farm sector, the nonfarm sector has grown significantly in recent decades, and its role in rural development has become increasingly important. This article examines the effect of participation in nonfarm activities on crop expenses of farm households in Nigeria. The relationship is modeled using a nonseparable agricultural household model that suggests that participating in nonfarm activities can relax the credit constraints facing farm households and reduce risk thereby helping households improve farm production and smooth consumption over time. The results show that participation in nonfarm activities by Nigerian farmers has a positive and significant effect on crop expenses and in particular on payments for hired labor and inorganic fertilizers. Separate analysis of the six geopolitical zones in Nigeria indicates that it is in the South-South and South-East zones where nonfarm participation appears to induce more hiring of labor. The results support the hypothesis that nonfarm participation helps relax liquidity constraints but suggests how that liquidity is used is zone-specific. In general, the results also indicate that liquidity is used more to pay for inputs into staple production as opposed to cash crops.

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[21]
Qi L, 2007. Development Economics. Beijing: Higher Education Press. (in Chinese)

[22]
Ranis G, Fei J C H, 1969. A theory of economic development.American Economic Review, 51(4): 533-565.

[23]
Rozelle S, Taylor J E, DeBrauw A, 1999. Migration, remittances, and agricultural productivity in China.The American Economic Review, 89(2): 287-291.No abstract is available for this item.

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[24]
Shao J, Zhang S, Li X, 2014. Farmland marginalization in the mountainous area: Characteristics, influence factors and policy implications.Acta Geographica Sinica, 69(2): 227-242. (in Chinese)Based on SPOT-5 images, 1:1 million topographic maps, the maps of the returning farmland to forest project and the Chongqing forest project, social and economic statistics, etc., this paper identifies the features and factors influencing farmland marginalization. The results showed: (1) During 2002–2012, the rate of farmland marginalization was 16.18%, which was mainly found in the high areas of northern Qiyao mountains and the medium-altitude areas of southern Qiyao mountains. And this farmland marginalization will increase, associated with non-agriculturalization of rural labourers and aging of the remaining labourers. (2) Elevation, distance radius from villages and road connections had a great influence on farmland marginalization. Farmland marginalization rates showed an increasing trend with the increase of elevation, and 60.88% of the total farmland marginalization area is found at an altitude greater than 1000 m above sea level. The marginalization trend also increases with slope and distance from the distribution network. (3) Farmland area per labourer and the average age of farm labourers were major factors driving farmland marginalization. Farmland transfer and small agricultural machinery sets affect farmland marginalization with respect to management and productivity efficiency. (4) Farmland with “comparative-disadvantage-dominated marginalization” accounted for 55.32% of the total farmland marginalization area, followed by “location-dominated marginalization” (33.80%). (5) According to the specifics of each real situation, different policies are suggested to mitigate the marginalization. A “continuous marginalization” policy will encourage the return of farmland to forest in “terrain-dominated marginalization”. An “anti-marginalization” policy is suggested to create new rural accommodation and improve the rural road system to counteract “terrain-dominated marginalization”. And another “anti-marginalization” policy is planned to improve management and micro-mechanization for “comparative-disadvantage-dominated marginalization”. A new idea was developed to integrate high resolution remote sensing and statistical data with survey information to identify land marginalization and its driving forces in mountainous areas.

DOI

[25]
Song J, Wang E, 2001. The mode and tendency of agriculture surplus labor force transformation in China.Chinese Journal of Population Science, (6): 46-50. (in Chinese)

[26]
Taylor J E, López-Feldman A, 2010. Does migration make rural households more productive? Evidence from Mexico.The Journal of Development Studies, 46(1): 68-90.The migration of labour out of rural areas and the flow of remittances from migrants to rural households are an increasingly important feature of less developed countries. This paper explores ways in which migration influences incomes and productivity of land and human capital in rural households over time, using new household survey data from Mexico. Our findings suggest that a massive increase in migration to the United States increased per-capita incomes via remittances and also by raising land productivity in migrant-sending households. They do not support the pessimistic view that migration discourages production in migrant-sending economies, nor the view implicit in separable agricultural household models that migration and remittances influence household incomes but not production.

DOI

[27]
Tian Y, Li X, Chen Yet al., 2010. A review on research advances in farm labor migration and its impacts on farm land use.Journal of Natural Resources, 25(4): 686-695. (in Chinese)Farm labor migration is an inevitable phenomenon during the period from agricultural society to industrial society.Currently,with the increasing of peasant worker's wage and improving of policies about peasant worker flow,farm labor opportunity cost is increasing in China,which will affect labor rural-to-urban migration and eventually affect the farm land-use change.This paper reviews major lines of theoretical and empirical research on farm labor migration.Several contributions point out that research perspective is more microcosmic,non-economic driving factors of labor migration are widely considered and impacts of differential individuals and settings on farm labor moving out are taken into account.Meanwhile,it reviews research advances in impacts of farm labor migration on farm land use.Due to complexity of influencing mechanisms,there are no generalization results about this issue yet.Hence,it needs further study the effects of farm labor migration on farm land use.

DOI

[28]
Wang X, Han L, Huang Jet al., 2016. Gender and off-farm employment: Evidence from rural China.China & World Economy, 24(3): 18-36.The goal of the present paper is to examine how the expansion of the economy from 2000 has affected rural off-farm labor market participation. Specifically, we seek to determine whether off-farm labor increased after 2000, what forms of employment are driving trends in off-farm labor and whether gender differences can be observed in off-farm employment trends. Using a nationally representative dataset that consist of two waves of surveys conducted in 2000 and 2008 in six provinces, this paper finds that off-farm labor market participation continued to rise steadily in the early 2000s. However, there is a clear difference in the trends associated with occupational choice before and after 2000. In addition, we find that rural off-farm employment trends are different for men and women. Our analysis also shows that the rise of wage-earning employment corresponds with an increasing unskilled wage for both men and women.

DOI

[29]
Wang X, Huang J, Rozelle S, 2017. Off-farm employment and agricultural specialization in China.China Economic Review, 42: 155-165.While it is well known that China's off farm labor market is emerging rapidly, less is known about the effect of movement off the farm on the farming practices of those that have continued to farm. The overall goal of this paper is to analyze the effects of changes in China's off farm employment on one aspect of the performance of China's agricultural sector: the emergence of specialization in farming. To achieve this goal, we have three specific objectives. First, we document the changes in the flow of labor out of China's villages. Second, we examine how specialization in farming has changed over time. Third, we examine the association between off farm labor flows and specialization. Using panel data from a national representative data collected by the authors between 1999 and 2008, the analysis finds that off farm employment is indeed rising rapidly. At the same time, specialization is occurring off and on the farm. There is a strong and robust correlation between off farm employment and on farm specialization. The results imply that China's agriculture has responded dynamically to the modernization happening elsewhere in the economy.

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[30]
Wu Y, 2010. Calculation on the elasticity of agricultural input-output in China: Based on spatial econometrics models.Chinese Rural Economy, (6): 25-37. (in Chinese)

[31]
Yan J, Yang Z, Li Zet al., 2016. Drivers of cropland abandonment in mountainous areas: A household decision model on farming scale in Southwest China.Land Use Policy, 57: 459-469.Cropland abandonment has emerged as a prevalent phenomenon in the mountainous areas of China. While there is a general understanding that this new trend is driven by the rising opportunity cost of rural labor, rigorous theoretical and empirical analyses are largely absent. This paper first develops a theoretical model to investigate household decisions on farming scale when off-farm labor market is accessible and there is heterogeneity of farmland productivity and distribution. The model is capable of explaining the hidden reasons of cropland abandonment in sloping and agriculturally less-favored locations. The model also unveils the impacts of heterogeneity of household labor on fallow decisions and the efficiency loss due to an imperfect labor market. The model is empirically tested by applying the Probit and Logit estimators to a unique household and land-plot survey dataset which contains 5258 plots of 599 rural households in Chongqing, a provincial level municipality, in Southwest China. The survey shows that more than 30% of the sample plots have been abandoned, mainly since 1992. The econometric results are consistent with our theoretical expectations. This work would help policy-makers and stakeholders to identify areas with a high probability of land abandonment and farming practice which is less sustainable in the mountainous areas.

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[32]
Yan J, Zhang Y, Hua Xet al., 2016. An explanation of labor migration and grain output growth: Findings of a case study in eastern Tibetan Plateau.Journal of Geographical Sciences, 26(4): 484-500.Although there has been rapid rural-urban migration in rural China since the 1980s, the total grain production of China saw a continuous increase. As of today, the relationship between labor migration and grain output growth remains partial and contradictory. The main aim of this empirical study is to examine some specific measures adopted by peasants to deal with labor shortage and maintain grain output growth. Using tracking survey, participatory rural appraisal methods, and land plot investigation, we investigate 274 households and 1405 arable land plots in four villages in two stages in Jinchuan county, southwestern China. The results show that continuous emigration of labor from the four villages caused the abandonment of a small amount of land, decreased labor intensity, and reduced multiple cropping index, shifting from “corn-wheat” multiple cropping pattern to the “corn” cropping pattern, which means labor shortage in some households. At the same time, owing to surplus labor in the villages, the peasants utilize a series of means to offset the negative impacts of labor migration on grain output, such as cropland transfer, labor exchange in the busy seasons, and the substitution of capital and technology for labor. The econometric analysis also shows that labor migration boosts grain production. This study provides a reasonable explanation of grain output growth under rural-urban migration.

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[33]
Zhang X, Yang J, Wang S, 2011. China has reached the Lewis turning point.China Economic Review, 22(4): 542-554.In the past several years, labor shortage in China has become an emerging issue. However, there is heated debate on whether China has passed the Lewis turning point and entered a new era of labor shortage from a period of unlimited labor supply. Most empirical studies on this topic focus on the estimation of total labor supply and demand. Yet the poor quality of labor statistics leaves the debate open. In this paper, China's position along the Lewis continuum is examined though primary surveys of wage rates, a more reliable statistic than employment data. Our results show a clear rising trend of real wages rate since 2003. The acceleration of real wages even in slack seasons indicates that the era of surplus labor is over. This finding has important policy implications for China's future development model.Highlights? This paper examines the Lewis turning point using primary village surveys over different periods. ? Rural wage has accelerated since 2003 in both harvest and slack seasons. ? Male and female wages have experienced the same trend - slow growth prior to 2003 and a rapid increase since 2003. ? The era of surplus labor is over.

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[34]
Zheng H, Tong J, Xu Y, 2007. Spatio-temporal changes of farmland resources and their driving forces in developed areas.Transactions of the Chinese Society of Agricultural Engineering, 23(4): 75-78. (in Chinese)According to the statistical and survey data of land use in Shaoxing city,the trend and laws of farmland change,especially,the temporal and the spatial differences,were analyzed.As a result of the principal component analysis(PCA) and multiple stepwise regressive analysis,the main driving forces of farmland changes were discussed.Results show that the spatial-temporal features of farmland changes in Shaoxing are notable,and the farmland decreases year by year.Moreover,the farmland decrease in Shaoxing city in recent years is mainly due to the rapid development of economic,the improving of people's lives and the increasing of capital input,market-oriented agricultural restructuring and city construction have occupied majority of farmland.Research results are not only provide scientific basis for reasonably use and protection of farmland,for sustainable agricultural development in Shaoxing city,but also provide the important reference for further study on farmland changes in the developed littoral areas.

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[35]
Zou J, Long H, 2009. The variation of farmland use and the security pattern of grain production in China since 1978.Journal of Natural Resources, 24(8): 1366-1375. (in Chinese)With rapid development of China's economy,the farmland use pattern has greatly changed since economic reforms were launched in 1978.On the one hand,rapid industrialization and urbanization has resulted in the agricultural to non-agricultural land conversion,and some farmland idle due to the massive and sustained flow of rural-to-urban labor migration;on the other hand,economic development may ensure the improvement of infrastructure for agricultural production,and the enhancement of farmland intensive use level.The dual variation of farmland both in quantity and quality brought about the effects to different degrees on grain production.This paper analyzes the spatio-temporal pattern of China's farmland intensive use level between 1978 and 2004,and develops a farmland-grain elasticity coefficient to reflect the interrelationship between farmland and grain production,using the agricultural statistical data from local governments.The outcomes indicated that,since 1978,the pressure of tremendous farmland loss on grain security has been relaxed,to some extent,due to the increased investment and subsequent quality improvement in farmland.Since the initiation of economic reforms,China's farmland intensive use level has been generally improved due to rapid economic development,and the improving speed takes on a situation of gradient declining from southeast coastal China to hinterland,just as the declining gradient of economic development level.Furthermore,the existing posture will be passed from coastal China to hinterland with the economic development.However,unceasing improvement of farmland intensive use level can not always bring about the sustainable and steady growth in grain outputs.Therefore,considering the law of diminishing marginal utility,in the economy relatively developed countries,the quantity of farmland will play a key role in maintaining the security pattern of grain production,which also provides a practical scientific basis for nowadays constituting strict farmland protection objective and strategy in China.

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