Agricultural Labor Input Research Articles

Improving mechanization conditions or encouraging non-grain crop production? Strategies for mitigating farmland abandonment in China’s mountainous areas

Food security is a critical global issue, requiring that the challenges of farmland abandonment be addressed. As a vital component of agricultural production in China, farmland use is affected by mechanization conditions and the crop cultivation decisions of rural households. With the decreasing economic viability of farmland in China’s mountainous areas, the effects of mechanization conditions and non-grain crop production on farmland abandonment remain controversial. This study developed a theoretical framework and used unique survey data from 2400 rural households in China’s mountainous areas to analyze the relationship between mechanization conditions, non-grain crop production, and farmland abandonment using multiple models, heterogeneity analysis, and factual characteristics analysis. These findings demonstrate that improving mechanization conditions and encouraging non-grain crop production could mitigate farmland abandonment. Non-grain crop production could mitigate abandonment through increasing agricultural labor input, and improving mechanization conditions could inhibit non-grain crop production. Additionally, improving mechanization conditions had a more significant effect on households with higher education level and lower incomes, while encouraging non-grain crop production showed an opposite trend. Both measures had greater effect in the western and low-altitude regions. Therefore, to protect farmland and ensure food security in mountainous areas, it is necessary to continue land consolidation appropriately, actively encourage non-grain crop production, and comprehensively balance the demands of different management objectives.

Inequality in agricultural greenhouse gas emissions intensity has risen in rural China from 1993 to 2020.

Reducing greenhouse gas (GHG) emissions in crop production while ensuring emission equity is crucial for sustainable agriculture in China, yet long-term large-scale data on GHG emissions intensity (GEI) are limited. Using an extensive dataset based on surveyed farm households (n > 430,000 households) from 1993 to 2020, we reveal that 2015 was a turning point for GEI levels, which dropped 16% in 2020, while inequality-measured as average GHG emissions per unit planted area-increased 13%. The key driving forces behind such trends included farmland input, all other inputs, agricultural labour input and total factor productivity but not capital input. Notably, farmland input and all other inputs contributed to 80% of the inequality, while contribution of total factor productivity gradually declined and was replaced by migration-induced agricultural labour input differences. Reducing GEI levels and guarding against widening inequality require optimizing production factor inputs.

Total-Factor Energy Efficiency and Its Driving Factors in China’s Agricultural Sector: An Empirical Analysis of the Regional Differences

Improving agricultural energy efficiency is essential in reducing energy consumption and achieving agricultural sustainable development. This paper aims to measure the agricultural total-factor energy efficiency in China rather than the partial-factor energy efficiency while taking full account of regional heterogeneity and to investigate the driving factors of agricultural total-factor energy efficiency. The empirical results showed that the average value of agricultural total-factor energy efficiency is 0.814 in China, and the technological gap ratio is 0.853. The regional difference in agricultural total-factor energy efficiency was quite obvious. Higher agricultural energy inputs are associated with higher agricultural total-factor productivity. The total value of potential agricultural energy savings in 30 provinces of China reached 1704.41 billion tons of standard coal. In terms of the absolute amount of agricultural energy saving, the amount was largest in the low-energy-input area, which was 113.87 million tons of standard coal, accounting for 66.81% of the total potential saving amount. Furthermore, we used the Tobit model to analyze the influencing factors of agricultural total-factor energy efficiency. We found that the proportion of agriculture to GDP has a positive impact on agricultural total-factor energy efficiency, while the per capita income of farmers, fiscal support for agriculture, the illiteracy rate of farmers, agricultural labor input, and agricultural capital stock have a negative impact on agricultural total-factor energy efficiency. Finally, we proposed policy implications in terms of agricultural technological progress, agricultural infrastructure, technical training, etc.

Can the Application of Environmentally Friendly Fertilisers Reduce Agricultural Labour Input? Empirical Evidence from Peanut Farmers in China

Environmentally friendly fertilisers (EFFs) can improve the quality of cultivated land, purify the soil environment, and promote reduction in the amounts of fertiliser applied by improving efficiency. However, few studies have analysed the spillover effects of EFF applications on agricultural labour inputs. Hence, this study discusses the impact of EFFs on agricultural labour input, using the propensity score matching method based on the micro-survey data of peanut growers in the main producing areas in China. The results showed that EFFs have a labour-saving advantage, with a significant average reduction in the number of labourers’ input and labour days in agriculture production of 0.127 persons/mu and 0.601 days/mu at the 1% to 10% significance level. Additionally, EFFs improve yield and revenue but significantly raise production costs, ultimately increasing net revenue for farmers. The mechanism of the labour-saving effect is the capability of EFFs to reduce the amount and frequency of fertilisers applications, the amounts of pesticides applied, and irrigation water consumption by their technical characteristics and farmland’s ecological environment enhancement. Accordingly, the time effect strengthens the ecological regulation function and the application reduction effect of EFFs, further decreasing agricultural labour inputs. At the same time, the application of EFFs contributes to the adoption of mechanical deep tillage and fertilisation technology (MDTFT), thereby reducing fertiliser application and ultimately improving the labour-saving effect of EFFs. Heterogeneity analysis revealed that the labour-saving effect of EFFs is more obvious for farmers operating with a larger planting scale. To improve the labour-saving effect of EFFs, the findings imply that the application years of EFFs should be appropriately extended and the MDTFT should be promoted according to local conditions.

Agricultural labor markets and the inverse plot size–productivity relationship: Evidence from China's apple growers

The size–productivity relationship and the reasons for the relationship had puzzled researchers and policymakers for decades. As rural internal labor markets had gradually developed in China, influencing mechanisms of agricultural labor markets on land size–productivity relationship were worth being deeply analyzed. Two main contributions to the existing literature were that: (1) owing to the labor-intensive production characteristics, better-developed rural internal labor markets, and fewer measure errors in self-reported plot size and production, apple growers were used to analyze the plot size–productivity relationship and the reasons for the relationship in rural China for the first time; (2) the household fixed-effect model was used to remove the impacts of household-level unobservable variables, and positive impact of labor input on agricultural productivity was analyzed. The empirical results from 1163 plot-level data indicated that: (1) when labor input was not included, the inverse plot size–productivity relationship was robust for apple growers; (2) agricultural labor input was a key reason for the inverse plot size–agricultural productivity relationship; (3) transaction costs of participating in agricultural labor markets influenced the inverse plot size–productivity relationship by changing the amount of labor input. This line of study was conducive to improving the efficiency of rural internal labor markets and increasing agricultural productivity.

Trends in Agricultural Land in EU Countries of the Baltic Sea Region from the Perspective of Resilience and Food Security

Agricultural land is crucial for the production of food and is, thereby, directly connected to food security. Agriculture is threatened by a multitude of hazards, such as climate change, peak oil, peak soil and peak phosphorus. These hazards call for a more resilient food system that can deliver food security for the global population in the future. In this paper, we analyse the Baltic Sea region’s ten European Union (EU) member states, investigating which trends are to be found in statistics between 2005 to 2016 on the development of agricultural land. In our paper, we analyse these trends of agricultural land by looking at three categories of data: (1) utilised agricultural area, (2) number of farms and (3) agricultural labour input. The results showed a trend that agricultural land is increasingly dominated by large farms, whilst over 1 million predominantly small farms have disappeared, and agricultural-labour input has dropped by more than 26%. These trends point towards a mechanisation of production, where larger and less labour-intensive farms take over production. This could partly be due to the EU common agricultural policy, which tends to favour large farms over small. Further, we argue for the importance of farm-size diversity, and about the dangers to food security that a system that is dominated by large farms possesses. Lastly, we conclude that the concept of resilience needs to be better included in policy development and food-system planning, and that more research needs to be done, analysing how existing agricultural policies impact the parameters studied in this paper.

Output value and productivity of agricultural industry in Central-East Europe

The study analyses the correlations among different economies of selected EU-12 member states based on comparison of agricultural economics variances, namely the output value of the agricultural industry, productivity of input, agricultural gross value added, subsidies on production, agricultural labour input and agricultural income per annual working unit in the period of 2010–2016, based on the Special Program for Social Sciences, as statistical methods. The EU-12 achieved a higher increase in productivity of input, output value of agricultural industry, agricultural gross valued added, as well as agricultural income per agricultural annual working unit compared to the average results of EU-28 for 2010–2016. The output value of agricultural industry and agricultural gross value added per intermediate consumption decreased by 1.35% and by 3.3%, but the factor income – net value added at factor cost – per annual working unit increased by 21%, because of the subsidies on production increased by 3.4% for 2010–2016. In EU-28, the factor income per annual working unit increased, but most of this income was for developing agricultural production technology.

Różnice w wydajności pracy między grupami państw UE w rolnictwie na podstawie Rachunków Ekonomicznych dla Rolnictwa (RER)

Różnice w poziomie wydajności pracy w rolnictwie państw UE stawiają w gorszej sytuacji państwa przyjęte do UE po 2004 roku (UE-13). Wyprowadzone ujęcie analityczne tego problemu zostało zilustrowane empirycznie. Analizowaną wydajność pracy przedstawiono jako wartość dodaną brutto na jednego pełnozatrudnionego. Do badania wykorzystano Rachunki Ekonomiczne dla Rolnictwa oraz Statystykę Rolniczych Nakładów Pracy. Z badań wynika, iż duże różnice w wydajności pracy między grupami państw nadal się utrzymują, jednakże następuje stopniowe ich zmniejszenie. Stwierdzono również negatywny wpływ dopłat bezpośrednich na ten proces.

Convergence of the Labour Productivity in European Union Agriculture

The objective of the paper is to examine the changes in the level of diversification of the labour productivity in the European Union countries in the years 1998-2015, and then to determine whether there is any convergence of the labour productivity among these countries. The labour productivity has been calculated as a relation of the gross value added at constant prices per one full-time employee. The study used the Economic Accounts for Agriculture (EAA) and the Agricultural Labour Input (ALI). The study covered the European Union countries, broken down by the countries of the „old” EU (EU-15) and the countries admitted to the EU after 2004. In order to determine the changes occurring in these countries, sigma-convergence (σ) and beta-convergence (β) have been used. The study shows that after 2011 there was a process of convergence among the EU countries in terms of the labour productivity in agriculture.

Machinery investment decision and off-farm employment in rural China

This paper investigates the endogenous linkages between farmers' machinery investment decision and off-farm employment in China. Both the theoretical model and the empirical results based on a survey of 453 households in Anhui Province indicate that agricultural labor input and small-sized machinery investment are gross complements rather than substitutes when machinery services are available in the market. Consequently, farmers with small-sized machinery are more likely to reduce their off-farm employment time. On the other hand, an increase in off-farm employment is more likely to reduce the possibility of possessing small-sized machineries mainly due to substitution effects of market machinery services. ► Farm labor and farm machinery are gross complements for households in rural China. ► Possessing small machinery reduces off-farm employment time. ► Participation in off-farm activities reduces the possibility of owning farm machinery. ► Subsidizing large machinery could induce off-farm labor supply.

PROSPECTS FOR AGRICULTURAL INCOME IN UE

The medium-term perspectives for the income of the agricultural sector have been compiled on the basis of the medium-term projections for the main agricultural markets and of the economic accounts for agriculture, which constitute the statistical basis of the income measure. The subsidy component of agricultural income has been established on the basis of: the estimated direct payments for the period 2005-2013, the rural development of the European committee, Act of Accession. The agricultural income would grow by 23.2 % between 2005 and 2013 because UE-27 would mask marked differences between EU-15, EU-10 and EU-2. Agricultural income in the EU-10 is steadily rising to exhibit a 37.1 % increase by 2013. The value of cereal production is projected to increase, but remain below the level of 2004. The agricultural labour input in the EU- 10 countries is assumed to fall by 4 % on annual average over the next decade in line with the restructuring of the agricultural sector. This rapid fall in labour force would boost the rise in agricultural income: whereas farm income in real terms would decline marginally by 0.3 % from 2005 to 2013.

Employment and private-sector afforestation in Scotland

One of the main land-use changes in rural Britain in recent decades has been the afforestation of open land, most of which was previously used for hill-sheep farming. The aim of this paper is to consider the implications of afforestation for rural employment. It is concluded that afforestation involves neither the loss nor gain of jobs at the local level in a large majority of afforestation schemes. Afforestation, however, results in a net increase in labour input per unit area, at least in the short term. Labour intensities average between 0.5 and 0.72 man years per year per 100 ha during the first five years after afforestation, while the theoretical displacement of agricultural labour input on the afforested areas is 0.14 man years per 100 ha. The intensity of post-afforestation input was found to vary with type of management and with geographical location, and a weak inverse correlation existed with size of area planted. No evidence of a significant relationship with site characteristics such as agricultural land capability was discovered. Most of the post-afforestation labour was supplied by mobile squads; resident estate workers provided the labour input in only 5% of the sample cases. The significance of afforestation-related employment in terms of labour inputs and origins of workers is considered, and it is concluded that such employment, when measured in terms of absolute numbers involved, is of limited importance.

Distribution of Agricultural Labor Productivity in Japan and Its Change, 1960-1975

The purpose of this study is to present the mesoscale distribution of agricultural labor productivity (A. L. P.) in Japan and its change during the period from 1960 to 1975 and to analyze statistically the relationship between A. L. P. and several factors.A. L. P. is defined as gross agricultural income (ten thousands yen per farm operator mainly engaged in farming). The data sources for this study are the Census of Agriculture in Japan and the Agricultural Income Statistics of Japan. For this study Japan was divided into 305 divisions through agglomerating several municipalities into one statistical unit.The first step of the analysis was the preparation of maps of A. L. P. in 1960, 1965, 1970, and 1975. Then the change of areal distributions of A. L. P. were investigated by comparing these series of maps.Subsequently, the polynominal trend surface analysis was applied for analyzing the general distribution pattern and the change from 1960 to 1975. In addition, multiple regression analysis was used to clarify the relationship between A. L. P. and the main factors.Main results obtained are as follows:1. A. L. P., even if the increase due to inflation of the agricultural price was eliminated, has increased 3.5 times in 1975 compared to 1960. Regional variation of A. L. P. decreased temporary in 1965, but has expanded continuously until 1975. A. L. P. goes in the opposite direction to agricultural land productivity.2. The examination in the types of change of A. L. P. showed that the number of districts remaining in the same class between the census have decreased except for the areas with very high score and very low score. Recently there is general tendency for a gradual increase of the inter-class movement (Fig. 2).3. 1st order trend surface of A. L. P. shows the general distribution pattern which is high in the northeastern parts in Japan, and low in the southwestern Japan from 1960 to 1970. Since 1970, it is high in the north and low in the southern parts of Japan (Fig. 4-7). If we raise the level of generalization of these patterns, we can see the appearance of the tendency for lower A. L. P. in the region facing the Pacific Ocean. The region centered around Tokyo, Kanagawa, and Shizuoka prefecture shows a remarkable decrease of A. L. P. On the other hand, the zone from Hokuriku district to Osaka shows a considerable increase.4. Multiple regression formula developed in this study, contained six variables, i. e., climate, agricultural labor input, management units, level of agricultural technology, level of commercialization, and quality of agricultural labor force as independent variables (Table 3). Using standardized partial regression coefficients, level of commercialization had the largest contributions in 1960, 1965, and 1970, and quality of agricultural labor force was the second. In 1975, the agricultural labor input was the most important, and the level of commercialization ranked next (Table 5). The inspection of the time change of the standardized partial regression coefficients for the three factors during the study period shows that the largest contributions of both the level of commercialization and the quality of agricultural labor force decreased and that of agricultural labor input is increased. These multiple regression formula containing these variables can explain considerable parts of the total three variance in agricultural labor productivity in the each census year.