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This paper aims to build a theoretical model of the impact of farmers’ adoption behavior of soil and water conservation measures on the agricultural output to analyze the impact of farmers’ adoption behavior of soil and water conservation measures on agricultural output.

Based on the field survey data of 808 farmers households in three provinces (regions) of the Loess Plateau, this paper using the endogenous switching regression model to analyze the effect of farmers’ adoption behavior of soil and water conservation measures on agricultural output.

Soil erosion has a significant negative impact on agricultural output, and soil erosion has a significant positive impact on farmers’ adoption of soil and water conservation measures. Farmers adopt soil and water conservation measures such as engineering measures, biological measures and tillage measures to cope with soil erosion, which can increase agricultural output. Based on the counterfactual hypothesis, if farmers who adopt soil and water conservation measures do not adopt the corresponding soil and water conservation measures, their average output per ha output will decrease by 2.01%. Then, if farmers who do not adopt soil and water conservation measures adopt the corresponding soil and water conservation measures, their average output per ha output will increase by 12.12%. Government support and cultivated land area have a significant positive impact on farmers’ adoption behavior of soil and water conservation measures.

The research limitation is the lack of panel data.

Soil erosion has a significant negative impact on agricultural output, and soil erosion has a significant positive impact on farmers’ adoption of soil and water conservation measures. Farmers adopt soil and water conservation measures such as engineering measures, biological measures and tillage measures to cope with soil erosion, which can increase agricultural output.

The conclusion provides a reliable empirical basis for the government to formulate and implement relevant policies.

The contributions of this paper are as follows: the adoption behavior of soil and water conservation measures and agricultural output are included into the same analytical framework for empirical analysis, revealing the influencing factors of farmers’ adoption behavior of soil and water conservation measures and their output effects, enriching existing research. Using endogenous switching regression model and introducing instrumental variables to overcome the endogenous problem between the adoption behavior of soil and water conservation measures and agricultural output, and to analyze the influencing factors of farmers’ adoption behavior of soil and water conservation measures and its impact on agricultural output. Using the counter-factual idea to ensure that the two matched individuals have the same or similar attributes, to evaluate the average treatment effect of the behavior of soil and water conservation measures, to estimate the real impact of adaptation measures on agricultural output as accurately as possible and to avoid misleading policy recommendations.

The purpose of this paper is to analyze the relationship between farm size and agricultural production efficiency from the aspects of output and profit in order to find an optimal farm size that achieves both output and profit efficiency in agricultural production in China.

This study uses the 2012 China Family Panel Studies survey data and employs the stochastic frontier analysis (SFA) models to investigate empirically the relationship between farm size and agricultural production efficiency.

The study finds that there is an inverted-U curve relationship between farm size and output efficiency and a U-shaped curve relationship between farm size and profit efficiency in agricultural production in China. Based on the empirical results, the study estimates that the appropriate farm size is around 10–40 mu and the optimal farm size is around 20–40 mu both in terms of output efficiency and profit efficiency in Chinese agricultural production under the current agricultural technology and land management system.

The findings of this study suggest that appropriate land consolidation will bring more benefits to farmer households and agricultural production efficiency. There are some policy implications. First, governments should give long term and more stable land using rights to farmers through extending the period of land contract and verifying land using rights. Second, governments should encourage transfers of land using rights and promote land consolidation. But the implementation of this policy should consider regional differences and not be used for blindly pursuing increasing land size. Third, land consolidation should be accompanied with the development of specialized agricultural services.

The paper makes two major contributions to the literature. First, the authors use the SFA model to investigate the relationship between land size and agricultural production efficiency. Second, the authors establish two SFA models – the stochastic frontier output analysis model and the stochastic frontier profit analysis model – to estimate the optimal land size to achieve both output and profit efficiency of agricultural production in China.

Agricultural carbon productivity considers the dual goals of “agricultural economic growth” and “carbon emission reduction”. Improving agricultural carbon productivity is a requirement for promoting green and low-carbon development of agriculture. Agricultural production agglomeration is widespread worldwide, but the relationship between agricultural production agglomeration and agricultural carbon productivity is inconclusive. This paper aims to study the impact of agricultural production agglomeration on agricultural carbon productivity, which is conducive to a better understanding of the relationships among agglomeration, agricultural economic development and carbon emission, better planning of agricultural layout to build a modern agricultural industrial system and achieve the goal of carbon peaking and carbon neutrality.

Based on China's provincial data from 1991 to 2019, this paper uses non-radial directional distance function (NDDF) and Metafrontier Malmquist–Luenberger (MML) productivity index to measure total factor agricultural carbon productivity. Subsequently, using a panel two-way fixed effect model to study the effect and mechanism of agricultural production agglomeration on agricultural carbon productivity, and the two-stage least squares method (IV-2SLS) is used to solve endogeneity. Finally, this paper formulates a moderating effect model from the perspective of the efficiency of agricultural material capital inputs.

The empirical results identify that Chinese provincial agricultural carbon productivity has an overall growth trend and agricultural technological progress is the major source of growth. There is an inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity. The input efficiency of agricultural film, machine and water resources have moderating effects on the inverted U-shaped relationship. Agricultural production agglomeration also promotes agricultural carbon productivity by inhibiting agricultural carbon emissions in addition to affecting agricultural input factors and its internal mechanisms are agricultural green technology progress and rural human capital improvement.

This paper innovatively adopts the NDDF–MML method to measure the total factor agricultural carbon productivity more scientifically and accurately and solves the problems of ignoring group heterogeneity and the shortcomings of traditional productivity measurement in previous studies. This paper also explains the inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity theoretically and empirically. Furthermore, from the perspective of agricultural material capital input efficiency, this paper discusses the moderating effect of input efficiency of fertilizers, pesticides, agricultural film, agricultural machines and water resources on agricultural production agglomeration affecting agricultural carbon productivity and answers the mechanism of carbon emission reduction of agricultural production agglomeration.

Aside from oil, the Nigerian economy is largely agrarian, which is rain-fed. Hence the criticality of understanding climate change and its impact on agricultural output is more pressing than ever. This is in line with Sustainable Development Goal 13 which is to take urgent action to combat climate change and its impacts. Regardless, Nigeria has in the past five decades experienced a significant increase in temperature, in the range of 10 to over 30 degree Celsius. Therefore, managing the effect of climate change on agricultural output now has the colouration of a developmental challenge.

In light of this, this study gives due consideration to the impact of climate change on agricultural output between the years 1986 and 2015. For the purpose of analysis, descriptive statistics, unit root test and the ordinary least square (OLS) estimation technique were employed.

Findings from the study reveal that the average annual rainfall, temperature and forest area positively influence agricultural output, whereas drought, floods and agricultural nitrous oxide (N₂O) emissions have negative impact on agricultural output. The study suggests the need for a regulatory framework and also an explicit national agricultural policy essential to offset the negative effects of climate change especially on agricultural output.

As Nigeria look to diversify her economy which relied on oil, agriculture is among the alternative sector hoping to drive her economic growth, therefore, it is pertinent to examine the current output in the sector given the effects of climate change.

The study aims to analyse the role of finance in the agro-industrialisation nexus in Nigeria using annual data on manufacturing value added, agricultural value added and volume of finance availed to the agricultural sector from 1981 to 2015.

To establish the presence of a long-run relationship, the error correction model and bounds cointegration techniques are employed. Likewise, the model is augmented to test whether the associated relationship between industrial output and agricultural output depends on access to finance by farmers with the inclusion of an interaction term.

Some salient contributions to the literature are as follows: agriculture and finance are strong and positive predictors of industrialisation in the long run; in the short run, past realisations of industrial output and finance have significant asymmetric effects on industrial output; the explanatory power of agriculture decreases with the growth of the financial system; and the long-run results validate the role of finance in the agro-industrialisation nexus.

Given these findings, achieving growth in the agricultural sector that will induce desired industrialisation should be prioritised by the government through agencies such as the central bank, financial intermediaries and other stakeholders with a view to making agricultural financing a major concern for sustainable domestic consumption and industrial growth.

The purpose of this paper is to estimate shadow prices of agricultural carbon emissions produced by agricultural inputs, rice paddy and burning crop residue, and to explore the impact of cropping pattern on marginal abatement cost (MAC).

The shadow price of agricultural carbon emissions is estimated by applying directional distance function and non-parametric methods.

The estimated shadow price of agricultural carbon emissions ranges from 6.78 to 557.83 yuan/ton, and the average value is 62.50 yuan/ton (or $10.18/ton). The MAC value varies in different provinces and years. The regional difference of MAC shows a decreasing trend during the investigation period. Cropping pattern shows a significant negative impact on agricultural MAC. A 1 percent decrease of rice proportion leads to a 0.31 percent increase in MAC value. This implies that the higher the proportion of rice is, the lower the economic cost to reduce agricultural carbon emissions would be.

It is feasible to draw up appropriate mechanisms for the allocation of emission reduction responsibilities according to conditions in various regions, with emphasis on the local cropping patterns. There is a trade-off between reducing carbon emission and increasing crop yields.

This study calculates agricultural MAC by using the shadow price approach, taking agricultural carbon emissions as undesired environmental output. The study also provides a reference emission right price and provides guidance to make use of cropping structure adjustment and optimization for exploring the emission reduction strategy.

The decline in the share of agriculture in both output and employment is a central feature of structural transformation. The authors present the distinct features between developed and developing countries in the process of agricultural share decline and dig into the real changes that occurred in the agricultural sector during the rapid decline in the agricultural share.

Taking the declining share of agriculture as a clue, the authors depict heterogeneous characteristics in the declining share of agriculture in developed and developing countries. Secondly, by criticizing the factor substitution hypothesis, the authors argue that the essence of agricultural transformation is the process of agricultural industrialization characterized by the combination, reconstruction, and continual changes of agricultural production factors. Finally, based on the theory of agricultural industrialization, this paper analyzes the combination of factors in different stages of declining agricultural share in typical economies.

In this paper, the authors find that the rapid decline in agricultural employment share is accompanied by an increase in the returns to agricultural production in developed economies. In contrast, the decline in agricultural employment share in developing economies lags, and agricultural production efficiency is way much poorer than that of developed economies. Taking the United States and Japan as examples, the authors find that the agricultural sector underwent agricultural industrialization, featured by reconstruction and upgrades of production factors combination.

The authors systematically reveal why huge changes occurred in the agricultural sector in developed economies during structural transformation, and also provide further thoughts and lessons for developing countries to accomplish agricultural modernization.

In this paper, the heterogeneity of the linkages among financial development, productivity and growth across income groups is emphasized.

An empirical analysis is conducted with an illustrative sample of 130 economies over the period 1991–2019 and classified into four subsamples: Organisation for Economic Co-operation and Development (OECD), developing, least developed and net food importing developing countries. Forecast error variance decompositions and panel vector auto-regressive estimations are computed, with insightful findings.

Higher levels of output stimulate the economic development in the agricultural sector, mainly via the productivity channel and, in the most developed economies, also through access to credit. Differently, in developing and least developed economies, the role of access to credit is marginal. The findings have practical implications for stakeholders involved in the planning of long-run investments. In less developed economies, priorities should be given to investments in technology and innovation, whereas financial markets are more suited to boost the development of the agricultural sector of developed economies.

The authors conclude on the credit–output–productivity nexus and contribute to the literature in (at least) three ways. First, they assess how credit access, agricultural output and agricultural productivity are jointly determined. Second, they use a novel approach, which departs from most of the case studies based on single-country data. Third, they conclude on potential causality links to conclude on policy implications.

Mitigating agricultural greenhouse gas (GHG) emissions is an essential part of China's effort to achieve net-zero emissions. This study assesses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies.

The study employs a parametric non-radial distance function approach and estimates the technical abatement potential and marginal abatement cost (MAC) of GHG in China's agricultural sector for the 2008–2017 period.

Agriculture is expected to make a great contribution to China's net-zero emissions progress. This study empirically analyses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies. A parametric non-radial distance function approach is used to derive technical abatement potential and MAC of GHG for the 2008–2017 period. The results indicate that no significant improvement had been achieved in terms of agricultural GHG reduction in China during 2008–2017. The country's agricultural sector could reduce 20–40% GHG emissions with a mean value of 31%. In general, western provinces have larger reduction potential than eastern ones. The average MAC for the whole country is 4,656 yuan/ton CO₂e during 2008–2017. For most western provinces, their MAC values are considerably higher than those for most eastern provinces. Compared with previous sectoral estimates of GHG mitigation cost, this study’s estimates indicate that reducing agricultural GHG emissions in some provinces is likely to be cost-effective. The Chinese government should consider expanding its national carbon market to cover agricultural sector.

The Chinese government should consider expanding its national carbon market to cover agricultural sector.

Existing studies in the field mostly ignore input constraints, which is inconsistent with carbon mitigation policy practice, especially in the agricultural sector. This study’s approach integrates both input and output constraints reflecting differing policy practice.

One of the challenging factors in achieving sustainable growth is the inability of the Nigerian government to diversify the country's revenue base. This study aims to investigate the relationship between cash crop financing and agricultural performance in Nigeria.

Four crops were considered, namely, cotton, cocoa, groundnut and palm oil. The impact of cash crop finance shock on agricultural performance was investigated using the vector error correction model (VECM), while the long-run relationship was examined through the identification of long-run restrictions on the VECM.

The variance decomposition showed that financing shock is more sensitive to cause variation in aggregate employment than aggregate agricultural output in palm oil, while for cocoa, cotton and groundnut showed otherwise. The long-run structural equations exert a positive relationship between cash crop financing and agricultural performance, except for oil palm and cocoa financing that has a negative connection with agrarian employment.

The study is limited to the unavailability of data for agriculture sector capital utilisation, which was not used.

These results show that long-run benefit can be maximised by appropriate funding in cotton and groundnut production to promote sustainable growth.

The study examines the impact of cash crop financing on agricultural performance with the aim to promote sustainable growth in Nigeria using identified VECM.