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This study investigates the impact of board funds, banking credit, and economic development on food production in the context of South Asian economies (India, Pakistan, Bangladesh, Sri Lanka, and Nepal).

This study used data from the World Development Indicators covering the years 1991–2019. To investigate the relationship between the variables of the study, we employed the panel unit root test, panel cointegration test, cross-sectional dependence test, fully modified least squares (FMOLS), and panel dynamic least squares (DOLS) estimators.

The empirical results indicate that board funding significantly increase food production; however, banking credit had a negative impact. Furthermore, the findings indicate that economic development, Arable land, fertilizer consumption, and agricultural employment play a leading role in enhancing food production. The results of the Dumitrescu-Hurlin causality test also show substantiated the significance of the causal relationship among all variables.

South Asian countries should prioritize board funding, bank credit, and economic development in their long-term strategies. Ensuring financial access for farmers through micro-credit and public bank initiatives can spur agricultural productivity and economic growth.

This study is the first to combine board funding, banking credit, and economic development to better comprehend their potential impact on food production. Instead of using traditional approaches, this study focuses on these financial and developmental aspects as critical determinants for increasing food production, using evidence from South Asia.

The European states, which started the industrial revolution by making use of mechanical power, provided their agricultural development by producing new technology tools that will increase the production in the agricultural sector. The Ottoman Empire made many attempts to increase agricultural sector in the nineteenth century and implemented policies to increase production. In this direction, primitive agricultural tools were changed, and many encouraging steps were taken to adopt and spread modern technology in the country. As a result of the policies made, since the second half of the nineteenth century, the use of modern technology has increased in the provinces such as İzmir, Edirne and Adana and then in Konya and Ankara, since the railways reached the interior. Increasing accessibility to international markets with the development of commercial agriculture and railway construction are also important factors that encourage the use of machinery. When the use of machinery increased in the twentieth century, many machine companies opened dealers in the country and attempted to reach the inner parts of the country. With the increase in the use of modern agricultural technology, agricultural production has increased and provided significant benefits to the labor problem, especially in regions where commercial agriculture has developed. The effect of modern technology on the increase in production can be seen in the agricultural numbers in 1909–1914. When the agricultural census is taken into consideration, although the production areas did not increase, the production amount increased. However, the contribution of modern agricultural technology to production was still somewhat limited. The reason for this is that due to the high prices of agricultural machinery, small farm owners cannot supply these machines.

The purpose of this paper is to investigate whether community‐based wildlife conservation can potentially be added in rural farmers’ investment portfolio to diversify and consequently reduce agricultural risk.

The correlation coefficient is computed from national data on the rates of return on agricultural production and wildlife conservation, to find out whether wildlife conservation is a feasible hedge asset.

The correlation coefficient between the returns to agricultural production and wildlife conservation for the period 1989‐1999, for which data exist for both activities, is inferior to unity indicating that rural farmers could use wildlife conservation to reduce the risk they face by engaging in agricultural production only.

Data on communal agricultural production and community‐based wildlife conservation potentially suffer from at least three limitations. First, wildlife is a unique resource that does not require the usual cash investment to acquire and as such the rates of return on wildlife conservation will likely be overstated. Second, some benefits from wildlife are public and non‐monetised; this results in depressed rates of return on wildlife conservation. Lastly, both the data on agricultural production and wildlife conservation are likely to understate physical and human capital investments; this potentially results in abnormally high rates of return.

Even though the paper makes a case for community‐based wildlife conservation at a national level, the benefits of diversification into wildlife conservation are likely to be high only in those rural areas that can sustain wildlife populations sufficient to generate adequate returns from wildlife activities such as tourism, trophy hunting, live animal sales and meat cropping.

This paper empirically investigates whether the risk that rural farmers face could potentially be managed through diversification into community‐based wildlife conservation and provides paramount evidence that wildlife conservation is a hedge asset in rural Zimbabwe. More investment in community‐based wildlife conservation would also help efforts to conserve wildlife.

The purpose of this paper is to analyze the extent of aging in the agricultural labor force and its effect on farm production in a province of China.

The analysis uses panel data for the years 2004 through 2008 from a representative sample of farm households in Liaoning province. Descriptive statistics reveal the age structure of the agricultural labor force and correlations between labor force age and production characteristics. A translog stochastic frontier production function and technical inefficiency model is employed to analyze the effect of aging of the labor force on the technical efficiency of crop production.

The paper finds an accelerating trend towards aging of the agricultural labor force in the data. Results from the stochastic frontier production function and efficiency analysis reveal that household‐level technical efficiency increases until maximum efficiency is reached when the average age of the household labor force is 45, after which efficiency declines.

Aging of China's rural labor force may affect efficiency and productivity in crop production. Agricultural policies may need to pay more attention to the aging of the agricultural labor force. Some measures should be taken to address the pattern of migration, and policies to improve the social and economic environment in rural areas for younger workers should be developed. Also, extension programs could help older farmers to maintain efficient farming methods.

This is one of very few analyses of the effects of aging on production efficiency for a developing country, as well as for China. The analysis uses a unique panel dataset that covers 24 counties, 1,890 rural households, and more than 6,000 individuals, with each household tracked for five years. Most of the literature estimating technical efficiency carries out the analysis at the individual level; in China and other developing countries, farming is carried out at the household level. We have adapted the methodology to apply to situations where the unit of analysis is the household.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

This study examines the impact of agricultural credit on rice farmers' technical efficiency (TE) in Côte d'Ivoire by considering the heterogeneity among credit sources.

A multistage sampling technique was used to collect data from 588 randomly sampled rice farmers in seven rice areas of the country. The authors use the endogenous stochastic frontier production (ESFP) model to account for the endogeneity of access to agricultural credit.

On the one hand, agricultural credit has a significant and positive impact on rice farmers' TE. Rice farmers receiving agricultural credit have an average of 5% increase in their TE, confirming the positive impact of agricultural credit on TE. On the other hand, the study provides evidence that the impact of credit on rice production efficiency differs depending on the source of credit. Borrowing from agricultural cooperatives and paddy rice buyers/processors positively and significantly influences the TE, while borrowing from microfinance institutions (MFIs) negatively and significantly influences the TE. Moreover, borrowing from relatives/friends does not significantly influence TE.

Future research can further explore the contribution of agricultural credit by including several agricultural productions and using panel data.

The study provides evidence that the impact of agricultural credit on agricultural production efficiency depends on the source of credit. This study contributes to the literature on the impact of agricultural credit and enlightens policymakers in the design of agricultural credit models in developing countries, particularly Côte d'Ivoire.

In the context of carbon peaking and neutrality, effectively controlling agricultural carbon emissions has gained academic attention. As an essential form of agricultural service scale management, this study investigates whether and how trusteeship affects the carbon emission behavior in planting production.

The authors established a theoretical framework to analyze the impact of agricultural production trusteeship on carbon emissions from planting. China's provincial panel data in the 2012–2021 period were selected to test the impact, mechanisms and heterogeneity of agricultural production trusteeship on carbon emissions from planting using the bidirectional fixed effect model and the panel correction standard error regression model.

The findings indicate that agricultural production trusteeship significantly inhibits carbon emissions from planting, especially in the dimensions of fertilizer input, pesticide application, agricultural film use and mechanical fuel. Agricultural production trusteeship primarily affects the intensity of these carbon emissions through contiguous farmland management and planting structure adjustment. Further examinations revealed that the influence of agricultural production trusteeship on carbon emissions from planting was heterogeneous with respect to geographical location, proportion of non-farming income and scale of agricultural production.

This study is the first to systematically evaluate the impact of agricultural production trusteeship on carbon emissions from planting.

The purpose of this paper is to realize dynamical grey incidence order of influencing factors of grain production in Henan province using grey systems theory.

Starting from choosing influence factors on grain production and dividing the 30 years (from 1979 to 2009 year) of grain production in Henan province into three periods, the authors calculate grey incidence degree between grain yield and every influencing factor by grey incidence analysis method, respectively, then obtain the grey incidence order of influencing factors in every period. Also based on the three grey incidence orders from different periods, the authors find a changeable tendency of influencing factors on grain production and key influencing factors on grain production in different periods. Finally, to keep Henan province grain production stable and sustainable, several policy suggestions are given.

The results are convincing: it is effective and powerful to analyze dynamically influencing factors of grain production using grey systems theory, and it is urgent to strengthen agricultural science and technology input, and pay close attention to the influence of dosage of pesticide and fertilizers on grain production.

Grey incidence analysis and findings exposed in the paper can be used by agricultural firms to optimize grain production plans, and by government to formulate reasonable agricultural production policies.

The paper succeeds in getting dynamical grey incidence order of influencing factors of grain production in Henan province using grey systems theory.

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.

The purpose of this paper is to analyze the impact of farmers’ agricultural production mode transformation, from the perspective of agricultural division of labor and cooperation, on their agricultural production efficiency including technical efficiency, pure technical efficiency and scale efficiency.

This paper analyzes the impact of the agricultural production mode’s transformation on farmers’ agricultural production efficiency, based on the classical theory of division of labor and specialization, transaction costs and cooperation. It uses 2013 survey data from 396 farms in 15 Chinese provinces to explore the contributing factors of agricultural production efficiency using a double selection model (DSM), which can correct the endogenous selection bias in farmers’ decisions.

Farmers that participate in agricultural division of labor and cooperation means transform their agricultural production from a traditional self-sufficient mode to one that is specialized and intensive. Agricultural division of labor measured by farmers’ participation in an agricultural division of labor in the production stages, or in agricultural products, and agricultural cooperation measured by farmers’ participation in farmers’ cooperatives significantly and positively influence their agricultural production efficiency after correcting farmers’ endogenous selection bias.

This paper proposes a unified framework to analyze the impact of farmers’ agricultural production mode transformation on their production efficiency. Further, it builds a DSM for an empirical analysis to avoid the endogenous biases in farmers’ self-selection behavior. This paper also provides ways for policy makers to improve farmers’ agricultural production efficiency from the modern agricultural production perspective.