Fulltext search in archive

Enhancing the resilience of rural households against the impacts of risks and moulding their enduring strength despite modest scale holds paramount contemporary significance for a multitude of developing nations, including China. This study uses the microdata of the China Labor-Force Dynamics Survey (CLDS), systematically measures the rural household resilience index for the first time, analyses the impact of the digital economy on the resilience of rural households, and dissects the group differences and mechanism of action. We found that from 2012 to 2018, the Chinese rural household resilience index had significant differences in time and space, and village market, gentry assistance, economic organisation, and income from collective operation were the most important indicators affecting the rural household resilience index. The improvement of the digital economy index, to some extent, suppressed the improvement of the rural household resilience index. Meanwhile, heterogeneity analysis suggested that depending on family size and housing property rights, the impact of the digital economy on the resilience of rural households will be divided. Moreover, mechanism analysis showed that the digital economy further affected the resilience of rural households through the employment comprehensive effect, income structure effect and member security effect.

In China’s agricultural catastrophe insurance market, issues of non-equilibrium are prominent. To understand the causes of non-equilibrium in agricultural catastrophe insurance and to develop prevention strategies, this study employs an Evolutionary Game Model, incorporating disaster and insurance data for three types of cereal crops in Henan Province to analyse the Evolutionarily Stable Strategies in the agricultural catastrophe insurance market. The research also considers government policies and disaster reinsurance as implicit participants in the model. The findings reveal significant differences in the impact of non-equilibrium in the agricultural catastrophe insurance market and the choice of game strategies, dependent on the scale of farm operations, the type of crops cultivated, and regional variations. Significantly, decision-making evolutionary paths vary between small and medium-scale farmers, with rice growers emphasising income insurance more. In regions prone to frequent catastrophes, the insurance rates for agricultural catastrophe insurance exhibit greater flexibility. By scientifically delineating agricultural catastrophe risk zones, appropriately expanding the scale of cultivation, reducing insurance rates, and adjusting agricultural catastrophe insurance products, a balanced development in the agricultural catastrophe insurance market can be promoted.

The issue of productivity and performance in agriculture is significant because it affects a country’s competitiveness, sustainability, and self-sufficiency in agricultural production and is reflected in European policy. This study aims to determine which country had the most efficient large farms compared to other V4 countries and whether efficiency in each country translates into the performance of large farms. The data were obtained from the EU FADN (Farm Accountancy Data Network) database from 2005 to 2019. These data were then evaluated using the statistical methods DEA: CCR-O (Data Envelopment Analysis: constant returns to scale), DEA: BCC-O (Data Envelopment Analysis: variable returns to scale), and Pearson correlation coefficient. Regarding international comparisons in achieving efficiency as measured by DEA, Hungary is the best performer among the countries compared, followed by Czechia, Poland, and Slovakia. The correlation between efficiency and performance measured by Farm Net Value Added was demonstrated only for Hungary. The international comparison provided information about which country had the most efficient large farms, what the ranking of countries was in terms of efficiency, and for which countries efficiency had / did not have a potential impact on performance. At the same time, the relationships regarding the efficiency and performance of farms with an economic size above EUR 500 000 of standard output were clarified.

Advancing agricultural carbon emission efficiency and farmers’ income simultaneously is crucial for the sustainable progress of agriculture. Our study centered on 31 provinces and cities in China and investigated regional variances and the dynamic evolution aspects of coordinated development in farmers’ income and agricultural carbon emission efficiency, utilising panel data from 2005 to 2021. The analysis revealed the following trends: Firstly, China’s overall agricultural carbon emission efficiency was steadily increasing, mainly because of technological advancements. Secondly, the correlation between farmers’ income and agricultural carbon emission efficiency in China had notably improved from 0.318 to 0.775. Throughout the observation period, disparities in the levels of coordinated development were observed in various provinces with a diminishing fluctuation, indicating regional disparities as the primary instigator. Thirdly, the level of coordinated development highlighted positive clustering attributes, demonstrating an ‘east high, west low’ pattern; the evolution of coordinated development levels exhibited stability in maintaining the current status. This study holds significant value for developing countries in enhancing farmers’ income and agricultural carbon emission efficiency in a coordinated manner.

The agricultural production in China is gradually transitioning from extensive agriculture to green agriculture. In this context, identifying the driving factors and dimensions of farmers’ green production behaviour can contribute to promoting sustainable agricultural development. Existing studies lack investigation into the identification of driving factors and dimensions of green production behaviour among farmers of different scales. This study examined 1 142 farm households from five major grain-producing provinces in the North China Plain in 2019. We employed probit-ISM (interpretive structural modelling) models to analyse the driving factors of green production behaviour among farmers of different scales and identify dimensional differences. The study concluded the following: i) Personal characteristics, household characteristics, operational characteristics, social network characteristics, organisational characteristics, and cognitive characteristics were factors driving green production behaviour among small-scale farmers. However, social network characteristics and organisational characteristics had insignificant effects on green production behaviour among large-scale farmers. ii) Personal characteristics, number of agricultural workers, scale of operation, degree of land fragmentation, and whether relatives and friends are civil servants were the deep-rooted factors driving farmers’ green production behaviour. Part-time farming status, proportion of grain income, types of agricultural machinery, relationship with local farm machinery operators, and organisational characteristics were middle indirect factors. Cognitive characteristics represented the direct surface factors. This study can provide crucial information for government departments, which formulate differentiated policies to promote green production behaviour among farmers of different scales.

This study investigates peer effects and agglomeration impacts on the cost efficiency of South Korean rice farms using a five-year panel dataset of production costs. We employed a time-varying stochastic frontier cost function approach to estimate cost efficiency and a linear-in-means model to quantify peer influences. The findings underscore peer effects as central to understanding and enhancing farm productivity, particularly in rice farming regions. Both specialisation and diversity of agglomeration positively influenced efficiency, with specialisation having a larger impact. Peer effects were stronger in highly rice-specialised areas. These findings indicate the necessity of incorporating peer influences and regional specialisation in agricultural policymaking for productivity enhancement. A nuanced, evidence-based approach leveraging peer dynamics and agglomeration economies is advocated to boost the efficiency of farming practices.

This study comprehensively examines multifaceted risk factors influencing wheat production among Turkish farmers, aiming to deepen understanding of how these factors shape farmers’ perceptions and decision-making processes. Utilising Structural Equation Modeling (SEM), we analysed the interplay of climate-related issues (F1), market dynamics (F2), and external events (F3), like COVID-19 and wars, alongside socio-demographic factors such as education, income, and land ownership. Findings revealed that higher education and increased agricultural income reduced price-related risks while expanding wheat cultivation areas heightened risk perceptions. Farmers in irrigated regions prioritised cyclical risks, whereas those in dry areas perceived climatic risks as more severe. Capital-intensive practices and storage facilities mitigate climate change and market variability risks, with committed wheat producers showing lower climate change risk perceptions. External factors like the Russian-Ukrainian war and the COVID-19 pandemic disproportionately impact irrigated area farmers. This study contributes to the existing literature by using empirical evidence from Turkish wheat farming to explore diverse risk perceptions, employing SEM to unravel complex risk factors and decision-making processes, thereby offering new insights for future agricultural risk management research.

The main research objective of this study is to present the dynamics of land productivity changes in EU agriculture in the years 2012–2020 and evaluate the influence of direct subsidies received by farmers on land productivity. The source data for 2012–2020 are secondary and come from Eurostat. The research results were prepared for the entire European Union (EU-28), and divided into ‘old’ countries (EU-15) and ‘new’ countries (EU-13). The results were developed using the method of assessing convergence (in terms of differences in land productivity in individual countries) using the coefficient of variation and the relative index of changes in individual Member States in relation to the EU average over the period under study. Results showed that between 2012 and 2020, average land productivity in the EU increased by 7%. At the same time, differences in land productivity between EU countries decreased. The correlation analysis confirmed a statistically significant relationship between land productivity and the amount of direct payments per ha of agricultural land. Additionally, results of the correlation between productivity per 1 ha and the total area of agricultural land in EU countries confirmed the law of decreasing marginal productivity of land.

This article aims to highlight the importance of climate and environmental challenges for agricultural economics and policy. Empirical research based on the Data Envelopment Analysis (DEA) method determined the average technical efficiency and scale efficiency of farms in the European Union in total and in economic size classes in the period 2004–2020. The results indicate that agriculture is generally characterised by high technical efficiency and scale efficiency. Analysis by economic size classes of farms, defined by the standard sum of their agricultural output, shows that the relationship between the scale of production and technical efficiency of farms is U-shaped. The highest technical efficiency and scale efficiency are characterised by small, large and very large farms economic classes. Economies of scale shift the burden of food production to large farms, which provide food security and are technically efficient but excessively burdensome for the climate and the environment. Small farms produce environmentally friendly food but on a small scale. Therefore, increasing the technical efficiency of medium-sized farms can contribute to more sustainable food production that meets both food security and climate and environmental objectives. The Common Agricultural Policy 2023–2027 provides greater access to financial support for moderate-scale farms and farms undertaking ecosystem restoration activities. This may affect the strength and direction of the relationship between farm scale and productivity, including technical efficiency.

The objective of the study is to determine the impact of shock from climate change, such as drought and flood, on various technology adoptions in rice production in Vietnam. This study utilised VARHS (The Vietnam Access to Resources Household Survey) panel data from 2012 to 2018 and employed regression analysis following the application of propensity score matching (PSM) to address potential selection bias caused by drought and flood shocks. The findings indicated that households tend to adopt the improved variety of rice and organic fertilisers since households suffer the shock from the drought. Another finding showed that households used more chemical fertiliser and reduced the probability of using improved seeds in rice production since the household was affected by floods. Based on the findings, policies should prioritise promoting and implementing environmentally friendly farming methods that are customised to address specific climate-related difficulties.

As an important path to breaking the urban-rural dual system and promoting agricultural modernisation in China, the process of urbanisation might have a strong influence on promoting agricultural economic resilience (AER). Using panel data from provincial-level administrative regions of China’s mainland, we constructed a novel indicator system to measure AER, and employ the system generalised method of moments model to examine the impact of urbanisation on AER and the moderating roles of land transfer and heterogeneous human capital. Our study yielded three notable findings. First, the urbanisation process can significantly enhance AER. This finding remained robust after conducting multiple robustness tests and addressing endogeneity using the instrumental variable method. Second, the influencing mechanism analysis results indicated that land transfer and human capital had significant moderating roles, and the level of land transfer and educational improvement can enhance the positive impact of urbanisation on AER, while the migratory human capital weakened this positive effect. Third, the heterogeneity analysis revealed regional differences in the impact of urbanisation on AER, demonstrating that the promotional effect of urbanisation was much greater in the major grain-producing areas. Our study offers a new perspective and evidence for researchers and policymakers investigating how to enhance AER.

In this study, we examine the effect of Agricultural Socialisation Services (ASS) on green grain production efficiency in Jiangsu Province, China, by using data from the China Land Economy Survey. We used the generalised random forests model in this research to address potential issues of farming household self-selection into ASS and unobserved heterogeneity in treatment effects. The results show that participation in ASS significantly improves green production efficiency, particularly for small-scale farmers. Efficiency gains are most pronounced in critical agronomic operations such as pest control, seeding and planting, whereas smaller efficiency effects are observed in plowing, harvesting and straw treatment. The findings suggest that targeted expansion of ASS could substantially enhance sustainable farming practices, especially for resource-constrained farms. This study provides important policy insights for promoting agricultural sustainability through improved access to and delivery of agricultural services, contributing to more efficient and ecofriendly grain production.

This research employed co-word clustering analysis to classify 62 geographical indication (GI) protection policies from 2009 to 2023 into three distinct types. Employing Sankey diagrams, we dynamically analysed the evolution of these policy tools. These insights provide valuable experiential guidance for reforming and innovating China’s GI protection system and agricultural sustainable development.

Air pollution is beyond an environmental or health issue. The impact of air pollution on farmers' decisions on agricultural mechanisation has always been overlooked and debate persists over subjective and objective pollution. Adopting data set from the China Labour Force Dynamics Survey, we investigate the influence of air pollution perceptions on farmers' mechanised farming. The endogeneity problem is addressed through the instrumental variable method. The consequences reveal that air pollution perceptions strengthen farm mechanisation, and reduced farming time is the key intrinsic mechanism through which perceived air pollution affects farmers' decisions on agricultural machinery. Additionally, this impact is more pronounced in male household heads and farmers in the plains. These findings render valuable policy implications for farmers chronically exposed to air pollution and for agricultural modernisation in China, including the necessity of improving air conditions and encouraging agricultural machinery services.

Contract farming is regarded as an effective strategy for smallholder farmers in developing countries to enhance their agricultural competitiveness. However, limited research exists on its potential to promote green, sustainable development. This paper investigates the impact of contract farming participation on farmers' green technology efficiency using data from a sample of 627 vegetable growers in Shandong, China and employs the propensity score matching method. Our findings are as follows: i) Under the counterfactual assumption, participation in contract farming increases green technology efficiency from 0.560 to 0.614. The efficiency of contract production bases, ranked from highest to lowest, is as follows: self-owned base, stock-sharing base, and contractual base. ii) The provision of productive services serves as a significant mediating factor in enhancing green technology efficiency, with a more substantial impact than issuing planned instructions. iii) Increasing purchase prices, as an effective means of providing motivational incentives, significantly amplifies the effect of contract farming on green technology efficiency in self-owned and stock-sharing bases. As organisational models evolve toward greater integration, the enhancing effect of price incentives on green technology efficiency strengthens. This study concludes with several public policy and agricultural management recommendations.

The paper explores the influence of global pandemic uncertainty (GPU) on food prices (FP) by using the mixed-frequency vector autoregression (MF-VAR) model. Empirical findings indicate that the influence of GPU on FP varies across different scenarios, exhibiting either positive, negative, or insignificant effects. A positive influence implies that GPU fuels panic-buying and stockpiling behaviours, thereby boosting food demand. Concurrently, disruptions in agricultural production and food export restrictions tighten the market supply, potentially pushing FP upwards. Conversely, a negative effect suggests that the global economic downturn and food safety anxieties stemming from pandemic-related uncertainty may dampen food demand, causing FP to decline. In some instances, FP remains unaffected mainly by GPU due to the competing pressures from adverse climate change risks on the food market. Notably, FP's predictive error variance decomposition underscores that the net impact of GPU on FP is stimulatory. This overall effect aligns with the inter-temporal capital asset pricing model (ICAPM), which posits a positive influence of GPU on FP. The findings recommend that consumers and investors diversify their food sources, while policymakers should bolster food supply chain resilience, promote sustainable agriculture, establish emergency reserves and coordinate aid.

This study explores the impact of contract farming on household income and rural poverty alleviation using measures outlined by World Bank among 410 smallholder Kenyan poultry farmers. Using endogenous switching regression and propensity score matching models, we found that contract farming significantly boosts household income, with participants experiencing a 74% increase. If non-participants had engaged in contract farming, their income could have risen by 45.59%. The average treatment effect on the treated was USD 0.21 per capita per day, corresponding to a 9.83% reduction in extreme poverty and a 16.90% reduction in poverty severity. Written contracts proved the most effective in poverty alleviation, contributing to reduction of 12.17% and 20.93% in extreme poverty and poverty severity respectively. Spot transactions resulted in a 10.35% reduction in extreme poverty and a 17.80% reduction in poverty severity, while unwritten contracts had the least impact, with reductions of 7.92% and 13.62%, respectively. These findings demonstrate the substantial benefits of contract farming in improving household income and alleviating rural poverty. They highlight the importance of implementing and supporting written contracts to maximise poverty reduction. Targeted policy interventions and support for contract farming could further enhance its effectiveness and contribute to sustainable rural development.

Innovation is the driver of sustainable business development and is essential to promote high quality econo-mic development in the country. Are more bank loans better for small and medium-sized enterprises (SMEs) innovation? Therefore, based on mixed cross-sectional data of county sweet potato processing enterprises, this study applied the econometric model to explore the impact of bank loans on county agrifood SMEs innovation. We find that there is an 'inverted U-shaped' relationship between bank loans and county agrifood SMEs innovation. The analysis of the mechanism shows that bank loans can not only alleviate the problem of innovation financing constraints for agrifood SMEs, but also provide financial support for the innovation activities of agrifood SMEs as a result of trade openness. This study has important practical implications for promoting county agrifood SMEs innovation in China and promoting high-quality county economic development.

Agroecosystems provide a number of ecosystem services that are essential to human well-being.  The valuation of these services by stakeholders offers important information that can be used to manage them more efficiently. In agroecosystems, individual stakeholder preferences can be heterogeneous and even opposing. This paper puts forward a novel analytical framework based on game theory to integrate the valuation of ecosystem services by different stakeholders into agroecosystem management. To illustrate it, the agricultural region of Los Vélez (south-eastern Spain) is used and three game modalities are applied (prisoner’s dilemma, common-pool resource game and battle of the sexes). Results indicate that the use of game theory contributes to more effective conflict resolution between stakeholders with different interests and priorities, making it easier to reach consensus on optimal management strategies. This approach can guide policymakers in the design and implementation of socially accepted agroecosystem management policies.

This paper evaluates the risk-adjusted performance of multivariate agricultural portfolios using the Stutzer ratio, an advanced measure that accounts for non-normal return distributions and downside risk. Three four-asset portfolios – grains, softs, and meats – are analysed in this study. The Stutzer ratio incorporates a risk-aversion parameter (θ) that penalises tail risk, providing a more accurate assessment of skewed and fat-tailed returns. Results show that Stutzer-optimised portfolios outperform naïve equal-weight portfolios in risk-adjusted terms, as optimisation effectively balances expected returns and downside exposure. Among the three portfolio categories, the softs portfolio exhibits the highest Stutzer ratio, with the meats portfolio following closely behind. Both portfolios have a relatively high tail-adjustment parameter (theta), indicating a reduced exposure to downside risk and a lower likelihood of extreme negative returns. Consequently, their risk-adjusted performance suggests greater return stability, making them particularly attractive to long-term investors.

This study examines the factors influencing adherence to the Mediterranean diet from a socioeconomic perspective, focusing on Italy as a representative Mediterranean country. The observed decline in adherence to this diet in favour of Western dietary patterns highlights the need for a deeper understanding of the factors influencing this trend. Specifically, the analysis investigates sociodemographic and economic variables that may influence adherence to the Mediterranean diet. On the other hand, it assesses the role of individual characteristics related to environmental concerns and pro-environmental behaviours, considering that the Mediterranean diet is widely recognised not only as a healthy but also a sustainable dietary model. The study utilises secondary data from the Italian National Institute of Statistics, based on a representative sample of 34 151 individuals, employing an ordinal logistic regression model. The findings reveal that sociodemographic factors – such as gender, age, education, economic status, family structure, and region of residence – significantly and positively affect adherence to the Mediterranean diet. Regarding environmental concerns and behaviours, the study finds a strong association between environmental awareness and higher adherence. Therefore, policy interventions and educational campaigns aimed at promoting the Mediterranean diet should adopt a holistic approach that includes the environmental dimension.

Spain is one of the few EU countries that adopted genetically modified maize as a crop (1998) and has continued to harvest it ever since. This article aims to contribute to the history of the adoption of transgenic maize in the EU, where the Mediterranean (Sesamia nonagrioides) and European (Ostrinia nubilalis) corn borers are two of the most destructive pests. Our aim is to identify Spanish farmers' motivations and opinions on adopting this technology. Our model is a binary logistic regression that estimates the probability of adopting Bt maize. Our results reveal that the odds of adopting Bt are at least 44.0 times greater if the farm is in an area with corn borer infestation episodes than if it is not.  The odds of adopting Bt are at least 4.9 times greater if farmers place a high importance on economic outcomes than if they do not. More adopters than non-adopters believe that Bt corn causes less damage to the environment than sulphates against the borer. No other opinion variable was clearly significant. We conclude that the most important reasons for Bt adoption were exposure to corn borer and concerns about the economic losses the borer could cause to the crop.

Enhancing cropland carbon efficiency (CCE) is vital for carbon-neutral and sustainable agricultural development. In this paper, we use the minimum distance to strong efficient frontier with undesirable outputs model and survey data from wheat–maize farmers in the Yellow River Basin of China in 2020 to investigate the effect and mechanism of different tillage practices on CCE. The results show that the average CCE in the study area is 0.592 6, which has large potential for improvement. Among the tillage practices, reduced tillage with straw returning (RTS) achieves the highest mean CCE, followed by no-tillage with straw returning (NTS), and conventional tillage with straw returning performs the worst. Both NTS and RTS are positively associated with higher CCE, with a stronger effect for NTS. Mechanism test results indicate that these practices enhance CCE primarily by increasing yield and net carbon sequestration. NTS improves CCE by reducing energy use and emissions, and RTS tends to increase fertiliser and energy inputs, partially offsetting its efficiency gains. Heterogeneity analysis results further indicate that the positive effects are stronger among small-to-medium-scale, less-educated and elderly farmers. These findings provide micro-level evidence that conservation tillage can promote low-carbon and efficient agricultural production in China.

The conflict between Russia and Ukraine has caused serious disruption to agricultural markets, affecting both food prices and food security. In our study, we examine how global economic problems, such as COVID-19 or wartime conditions, affect corn prices and their predictability. We used deep neural network models [Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU)], experimenting with both simple and hybrid versions, as well as univariate and multivariate types. The results show that the GRU model outperformed the other models in predicting corn prices. It was also found that multivariate models tended to yield more accurate results than their univariate counterparts, suggesting that forecast quality can be significantly improved by including additional variables. In the robustness analysis, it was shown that the COVID-19 crisis in 2020 and the Russia–Ukraine war in 2022 led to a deterioration in model performance. The research contributes to the development of forecasting methods for the corn market and provides a basis for decision-making strategies for market players. To ensure methodological rigour, the forecasting results were statistically validated using the Diebold–Mariano test.

The specificity of the agricultural sector (seasonality, the methods of obtaining human resources and so on) affects the situation in the labour market. The demand of agriculture companies for qualified workers is relatively high; unfortunately, people still prefer to work in the related or other fields where they have more suitable work conditions related. Building the brand of the employer, improving the awareness of the public and increasing the loyalty of the present employees can raise the offer of vacancies and obtain new qualified employees. The aim of the paper is to identify the benefits of human resource branding in businesses arising therefrom. A partial aim is to identify the present key managerial challenges of agriculture businesses. In the work, the data collected from a questionnaire survey (n = 108) were used together with the information from the Czech Statistical Office, in the opinion of which the labour market in the agricultural sector does not exhibit a positive trend. As a part of the evaluation, a factor analysis was carried out identifying three categories of benefits (the stabilisation of workers, organisational processes, and other benefits) crucial for the employer branding in agriculture.

Food safety systems that implement Hazard Analysis and Critical Control Points (HACCP), certification, traceability, brands as well as in geographical indications and private branding require dedicated investments in physical resources, human resources and in re-organising the production processes and control activities. Investment decisions can be made according to legal requirements or based on voluntary decisions. In this study, we address the two following research questions: do the inducements due to the regulatory framework influence the decision to invest in the implementation of food safety strategies and what is the size of this potential influence? Does the allocation of the decision right to invest influence the investment decision and does this potential influence vary across food safety systems? We carried out an empirical investigation on investment decisions in the Italian meat sector, comparing systems dedicated to safety and marketing strategies. The knowledge of such an influence provides a better understanding of the micro-level motivations of food safety investments in a critical area and contribute to the design of regulatory strategies.

The paper examines empirically the impacts of agricultural sector value added and financial development on unemployment, using yearly data from 1995-2015. Eleven developing Southern African Development Community countries were selected for the study. The empirical analysis was carried out using second-generation econometric methods. The regression results revealed that both agricultural value added and financial development are important determinants of unemployment within the region. The results specifically show that agricultural value added is negatively associated with unemployment in both the short and long-run, although the long-run effect is many times bigger than the short-run impact. The results also show that in the long-run, both financial depth and financial efficiency are negatively associated with unemployment. Interactions between agricultural value added financial development and unemployment were further tested via panel bootstrap causality tests. The causality test results revealed the existence of significant one-way causality from agricultural value added to unemployment and from financial depth to unemployment for the region. It also showed that causality varies across individual countries within the region with different conditions, indicating the heterogeneous nature of the countries that make up the regional bloc.

Does the growth in non-agricultural sectors spill over to the agricultural sector of an economy? There is limited evidence available on the issue for the developing world, especially for Pakistan which has undergone large structural changes since its independence. This study examined the impact of sectoral growth linkages on agricultural output of Pakistan for the period of 1960-2016. We have estimated an econometric model which incorporates inter-sectoral linkages of Pakistan economy using a Vector Error Correction Model (VECM). Our analysis revealed that the economy of Pakistan has shifted from an agricultural dominant economy to services-based economy during the past six decades. Results of VECM show that the industrial sector has a negative impact on the performance of agricultural output whereas services sector is influencing the output of agriculture sector positively in the long run. Short run results show that industrial sector is affecting the performance of agricultural output positively whereas services sector is influencing the output of agriculture sector negatively. Negative impacts of industry in the long run and services in the short run imply that agricultural sector should be given its due share in public investment and the role of middle man should be minimised at the time of sale of agricultural production in the markets.

The European Green Deal to tackle climate change sets emission reduction targets for 2050. Particular attention has been paid to the agricultural sector, where there is a strong need to reduce carbon emissions and re-establish the natural carbon cycles. The concept of carbon neutrality is emerging in a scenario where it is necessary to reduce carbon dioxide (CO₂) emissions from cultivation to near zero. The quantification of carbon emissions was carried out by the carbon footprint (CF) of conventional, organic and zero residue potato cultivation in Sicily. In order to provide farmers and consumers with answers regarding the most sustainable cultivation regime, the results showed that the organic and zero residue methods have the best results in terms of emissions; the latter instead revealed the positive results in economic terms. It becomes a new model to follow in the pursuit of sustainability as it is based on the reduction of synthesis inputs and is free from the constraints imposed by organic production standards.

A public private partnership can be an effective approach to deal the projects with modern agricultural development in Sub Saharan Africa. A former financial analysis of a development project, carried out by the authors, showed that public and private partners can effectively join in a mutually satisfactory venture capital. The same project is now complemented with a bankability study, considering lenders options, equity allocation, collaterals and likely applicable interest rates, available cash flow and sustainable debt service repayment to provide a through financing scenario for each partner's perspective assessing the relevant Debt Service and Loan Life Cover Ratios. Cash flow and interest rates fluctuation impacts are eventually investigated with a sensitivity analysis to prove the robustness of the proposed scenario.