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The purpose of this study is to examine the relative importance of climate normals (average long-term temperature and precipitation) in explaining net farm revenue per hectare (NRh) for supplementary irrigated and rainfed cocoa farms in Nigeria.

NRh was estimated for 280 cocoa farmers sampled across seven Nigerian states. It was regressed on climate, household socio-economic characteristics and other control variables by using a Ricardian analytical framework. Marginal calculations were used to isolate the effects of climate change (CC) on cocoa farm revenues under supplementary irrigated and rainfed conditions. Future impacts of CC were simulated using Six CORDEX regional climate model (RCM) ensemble between 2036-2065 and 2071-2100.

Results indicate high sensitivity of NRh to Nigerian climate normals depending on whether farms use supplementary irrigation. Average annual temperature increases and precipitation decreases are associated with NRh losses for rainfed farms and gains for supplementary irrigated cocoa farms. Projections of future CC impacts suggest a wide range of NRh outcomes on supplementary irrigated and rainfed farm revenues, demonstrating the importance of irrigation as an effective adaptation strategy in Nigeria.

This paper uses novel data sets for simulating future CC impacts on land values in Nigeria. CORDEX data constitute the most comprehensive RCMs projections available for Africa.

The purpose of this paper is to explore the impacts of climate change on crop net revenue by region. Particularly, the authors focus on the impact differences between north and south regions.

The authors applied the Ricardian approach which assumes that each farmer wishes to maximize revenue subject to the exogenous conditions of their farm. The climate data are based on actual measurements in 753 national meteorological stations and the socio-economic data covers 8,405 farms across 28 provinces in China.

On average, the rise of annual temperature will hurt farms both in the north or south. The impacts of climate change on both precipitation and temperatures have different seasonal impacts on producers in the north and the south of China. As a consequence, the impact on net farm revenues varies with farms in the north and the south being adversely affected (to different degrees) by a rise in the temperature, but both benefiting from an anticipated increase in rainfall. The results also reveal that irrigation is one key adaption measure to dealing with climate change. Whether in the north or south of China, increasing temperature is beneficial to irrigated farms, while for rainfed farms, higher temperature will result in a reduction in net revenues. The results also reveal that farms in the north are more vulnerable to temperature and precipitation variation than that in the south. Irrigated farms in the south are more vulnerable to precipitation variation than that in the north; but rainfed farms in the north are more vulnerable to precipitation variation than that in the south.

Applying empirical analysis to identify the differences of climate change impacts between north and south regions will help policy makers to design reasonable adaptation policies for various regions.

This paper examines the performance of smallholder rice farms established using improved planting technologies – broadcasting, dibbling and transplanting – under different production systems – rain-fed and irrigation – in Ghana.

Using recent cross-sectional data of 200 smallholder rice farmers from the upper east region of Ghana, this study employed multinomial logit model and descriptive and inferential statistics for the analysis.

The results revealed that rice production under irrigation system contributes significantly to increasing farm productivity and profitability. Rice farmers who adopted dibbling and transplanting technologies under both irrigation and rain-fed production system obtained higher productivity and profitability than those who used broadcasting technology. Adoption of improved rice planting technologies by smallholder farmers is significantly influenced by education, farm size, improved rice varieties, sales outlets, hired labour and percentage of paddy sold.

The sample size is relatively small, even though findings are still very important in terms of policy formulation for improved smallholder farm performance in a developing country like Ghana.

This study calls for collaborative efforts by government, donor agencies and NGOs to establish irrigation facilities and/or expand existing ones, increase sensitization and dissemination of improved planting technologies, as well as intensify the input subsidy programme in Ghana.

To the best of the authors knowledge, this is the first study that focuses on farmers' choice of rice planting technologies under irrigation and rain-fed production systems, and how these technologies impact on smallholder farm performance in Ghana.

The purpose of this paper is to provide an overview of the current state of knowledge on the economic performance of genetically modified (GM) cotton worldwide based on a wide range of data and source from available literature, and second to assess yield gain and economic performance.

A systematic review was captured to provide the evidence of potential benefits of GM cotton. A country-specific analysis was conducted in order to compare economic indicators and employed meta-analysis to find out the significance of the different of GM cotton over its counterpart.

This paper depicts positive impact of commercialized GM cotton in terms of net revenue, and the benefits, especially in terms of increased yields, are greatest for the mostly farmers in developing countries who have benefitted from the spill over of technology targeted at farmers in industrialized countries.

Due to the variability of the data which came from different methodologies, it is difficult to determine the differences of the performances each individual study.

This, it is believed that results from this study can be useful for operations of all sizes as the authors think about what needs to be focussed on for long-term producers survival.

The paper clearly indicates that China is the highest cotton yield of GM cotton, the lowest cost of GM seed and the lowest cost of chemical spray compare to any other countries. Therefore, this is the fact that the adoption of GM cotton has been widely spread among the farmers across the regions in China.

Rapid transformation of agrifood value chains because of population growth, urbanization, rising consumer incomes and increased demand for food quality and safety has resulted in the need for smallholder farmers to coordinate horizontally through group formation and collective marketing to improve farm performance in developing countries. This paper aims to examine the factors that influence farmer group membership and collective marketing decisions and their impacts on smallholder farm performance in rural Ghana.

Using data from a recent survey of 447 rice farmers in rural Ghana, an endogenous switching regression model is employed to account for selection bias arising from both observable and unobservable farmer attributes.

The data reveal that group members and collective marketing participants obtained higher prices and also incurred lower input costs. The econometric estimates show that age, access to credit, mobile phone ownership, distance to market and road status are the main drivers of group membership and collective marketing decisions. The authors also find positive and significant impacts of farmer group membership and collective marketing on farm net revenues.

The findings from this study suggest that government and donor support for the formation of farmer groups during implementation of agriculture and value chain interventions should as well incorporate strategies to facilitate collective marketing.

To the best of the authors’ knowledge, this study is the first to examine the role farmer groups and collective marketing play in improving smallholder farm performance.

Climate change is the most concerned issue in the global economy; increase in climate variability and uncertain climate events have caused distress in agriculture sector. The study estimates economic effect of climate change on agriculture income for the Indian state of Karnataka. The study reports the difference of result from past studies, where estimates from present study indicate higher negative impact of rise in temperature.

Fixed effect panel regression method was used to examine change in agriculture revenue to climate response. Climate variables were classified based on the crop calendar to capture the damage caused by climate change. The authors use fine scale climate data set constructed at regional context for 20 districts and time period of 21 years (1992–2012).

The result showed that with 1-degree rise in average maximum temperature, the revenue declined by 17–21%. The prediction behavior of the different models was evaluated using out-of-sample forecast approach by training and testing historical data set.

The study adopts recent data sets on agriculture and the updated climate variables to estimate the climate change impact on agriculture. The study yields the better results when compared to previous traditional models applied in literature in Indian context. The study further evaluates the prediction behavior and robustness of the estimated models using out-of-sample forecast method.

Hail risk management is essential for successful farm management in German fruit production, particularly because hail events and associated losses have increased in recent years. The purpose of this paper is to conduct a detailed risk analysis comparing different strategies to manage hail risk, taking into account farmers’ risk aversion and farm-specific conditions.

Within an expected utility framework, two different strategies for managing hail risk are compared: one belonging to the group of financial instruments (hail insurance) and the other to the group of technical instruments (anti-hail net). A unique data set comprising a ten-year time series of orchard-specific hail damage and hail insurance data is used.

For orchards with low local hail risk and low yield potential, not using hail risk mitigation is most efficient. For orchards with high local hail risk and high yield potential, anti-hail nets provide the highest certainty equivalents. For orchards with high local risk, but low yield potential, hail insurance is most efficient. For orchards, with low local risk, but high yield potential, the certainty equivalents are higher for anti-hail net, when the farmer is risk neutral or slightly risk-averse. With increasing risk aversion, hail insurance is most efficient, which can be explained by the greater degree of the instrument’s flexibility.

The novelty of the study lies in the direct comparison of the risk effects of anti-hail nets and hail insurance in fruit production.

The purpose of this study is to examine the effects of agricultural policy reform – specifically the change from market to direct payment support – on income variability of Swiss farming households. In addition, the observed heterogeneity in income risks across farms and time is explained in terms of farm and regional characteristics.

Unbalanced farm‐level panel data of the Swiss farm accountancy network (FADN) are used to construct coefficients of variation of five‐year overlapping time intervals for total household income and gross farm revenues over the period 1992 to 2009. Linear fixed effect models are applied to measure the effect of specialization, off‐farm income, direct payments, farm size, and liquidity on the variability of gross farm revenues and household income in the valley, hill, and mountain regions.

The switch from market‐based support to direct payments has decreased the variability of farm revenues and household income. The strong reliance on direct payments serves as insurance for most farmers and reduces both household income and revenue risk. Off‐farm income can be used by farmers to reduce household income risk but it increases revenue risk in the valley regions. In all of the regions considered, farm size has a positive effect on household income risk and a negative effect on revenue risk. A high degree of specialization increases both gross revenue and household income risk. Potential revenue insurance contracts should specify farmers' off‐farm employment, the degree of specialization, farm size, and regional specific risk profiles.

This paper assesses the complementary effects of specific farm characteristics and risk management strategies with regard to both farm revenue and household income risk. Influences of agricultural policy changes on income risks are also empirically assessed at different spatial scales.

This study investigates the economic outcomes of organic farming controlling for the four major aspects of a cropping system, including climate, genotypes, management and soil. Considering possible variations in treatment responses, this study also presents empirical evidence of heterogeneous treatment effects associated with spatial agglomeration or farm covariates.

Rice farm households data taken from the 2015 Agriculture Census is merged with township-level seasonal weather data, crop suitability index and average income per capita in Taiwan. To address the selection bias problem, the authors apply the Probit-2SLS instrumental variable (IV) method in the binary treatment model under homogeneous and heterogeneous assumptions.

It is found that organic farming leads to a significantly positive effect on rice farms' economic performances in terms of cost reduction and profit growth. This positive treatment effect is more sizable with spatial agglomeration. Furthermore, the treatment effect of organic farming is found to vary with the farm characteristics such as farmland area and the number of hired workers.

Two important implications for the promotion of sustainable agri-food production are inferred: (1) establishing organic agriculture specialized zones may benefit rural development; (2) providing economic incentives to small farms to expand their scale may be a more effective policy means to promote sustainable agri-food production.

The findings in this study complement the body of knowledge by drawing insights from the agriculture census data and providing profound evidence of the heterogeneous outcomes of organic farming due to spatial clustering and farm covariates.

Hailstorms are a major risk in agriculture. In order to mitigate the negative consequences on farm revenues, in the present paper the authors analyse the choice between insurance contracts and anti-hail nets. Furthermore, the authors discuss the consequences of anti-hail nets adoption on the actuarial soundness of the insurance market.

In this paper the authors firstly develop a theoretical model based on expected utility theory to compare the profitability of no-hedging against insurance and anti-hail nets. Subsequently, they test their theoretical model predictions with data of South Tyrolean apple producers.

The authors find that the benefit of anti-hail nets compared to insurance is an increasing function of the overall risk of hail damages, of the farmers' level of risk aversion and of the worth of the agricultural output.

Given the authors’ findings that anti-hail nets are more profitable for riskier, risk-averse and high-profitable farmers, the diffusion of anti-hail nets could be beneficial for the actuarial soundness of insurance markets.

The model developed in the paper is specifically designed to compare the profitability of different agricultural hedging options and can be easily extended to cover other hazards.