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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.

The purpose of this paper is to use simulation analysis to assess farmer choice between crop insurance and supplemental revenue options as proposed during development of the Agricultural Act of 2014.

The certainty equivalent of wealth is used to rank farm choices and assess the effects of supplemental revenue options on the crop insurance plan and coverage level chosen by the producer under a range of farm attributes. The risk-reducing effectiveness of the select programs is also examined through their impact on the farm revenue distribution. The dependence structure of yield and prices is modeled by applying copula techniques on historical data.

Farm program supplemental revenue programs generally have no effect on crop insurance choices. Crop insurance supplemental revenue programs typically reduce crop insurance coverage at high coverage levels. An individual plan of crop insurance combined with a supplemental revenue insurance plan may substitute for incumbent area crop insurance plans.

The analysis provides insights into farmers’ possible choices by focussing on alternative crops and farm attributes and extensive scenarios, using current data, crop insurance plans and programs contained in the 2014 Farm Bill and related bills. The results should be of value to policy officials and producers in regards to the design and use of risk management tools.

The purpose of this paper is to determine the sources and factors affecting farm revenue variation on crop and livestock farms in the Northern Great Plains.

A two method approach is used. Variance decomposition analysis is completed on an 18-year balanced panel data set of North Dakota producers to determine the sources of farm revenue variation. The second component of this research uses a random effects estimator to determine the effect of farm characteristics on farm revenue variation measured by coefficient of variation.

Crop revenue is the largest source of farm revenue variation, with crop insurance being the largest source of revenue variation diversification. Small market crops and corn were found to increase revenue variation compared to those operations that received the largest sum of their revenue from wheat. Government payments and insurance payments were also found to increase farm revenue variation indicating they may provide an incentive to plant more risky crops.

This analysis examined specific enterprises that affect farm revenue variation, which has not been examined in earlier work. This distinction allows for focus on potential policy implications of small market crops and new crops in “transitional planting zones”.

The purpose of this paper is to examine the sources and magnitude of variation in accrual adjusted gross farm revenue and farm revenue net of feed purchases on Michigan dairy farms representative of Upper Midwest dairy farms. The paper aims to assess whether adjusted gross revenue‐type insurance instruments meet insurability conditions when applied to dairy farms.

Accrual adjusted dairy farm revenue and revenue net of feed purchased from Michigan dairy farm panel data from 1995 through 2006 were detrended and summarized. Variance decomposition was used to identify sources of variation in adjusted gross revenue and adjusted gross revenue less feed purchases. In‐sample insurance premiums were estimated and Monte Carlo simulations were used to adjust these premiums for out‐of‐sample considerations.

Milk price variation was the largest source of variation while milk production per cow varied little. Farms with smaller herds and those with larger percentages of farm revenue from crop sales had higher relative revenue variability and would trigger a higher frequency of indemnities under a whole farm revenue insurance contract.

Because the data analyzed conclude in 2006, the volatility of the past couple of years is not reflected. Therefore, researchers are encouraged to test the proposed insurance feasibility further with more recent data.

The paper addresses considerations for the development and commercialization of a feasible dairy revenue insurance instrument.

This paper fulfils a need to understand magnitude and source of revenue variation on dairy farms and how insurance might mitigate negative consequences of this variation.

This study evaluates the impacts on gross revenue distributions of the use of alternative crop insurance products across different coverage levels and across locations with differing yield risks. Results are presented in terms of net costs, values‐at‐risk, and certainty equivalent returns associated with five types of multi‐peril crop insurance across different coverage levels. Findings show that the group policies often result in average payments exceeding their premium costs. Individual revenue products reduce risk in the tails more than group policies, but result in greater reductions in mean revenues. Rankings based on certainty equivalent returns and low frequency VaRs generally favor revenue products. As expected, crop insurance is associated with greater relative risk reduction in locations with greater underlying yield variability.

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 research examines factors influencing the adoption of crop and revenue insurance. This is accomplished by estimating a multinomial logit model of insurance choices facing U.S. farmers. Results indicate significant differences in the probabilities of adoption of each insurance plan. The levels of selected explanatory variables, such as operator’s education level, debt‐to‐asset ratio, off‐farm income, soil productivity, participation in production and marketing contracts, and type of farm ownership, appear to be the determinants of the probability of having adopted each insurance plan.

The purpose of this paper is to discuss how wind farms attract wind turbine manufacturers to get involved in wind turbines’ maintenance service with revenue sharing contract of bundled service under which the background of operation and maintenance (O&M) aftermarket of wind turbine exists. The authors also try to extend the results to the application of product plus service business mode on large-scale equipment O&M service. At present, Chinese wind power industry is suffering from production capacity redundancy. The profit levels for both wind farm and wind turbine manufacturers are relatively low. It is significant for Chinese wind power industry development to coordinate the supply chain of wind power in order to reduce O&M costs and increase revenues.

The present paper discusses product plus aftermarket service contract design on the background of closed-loop product service chain and uncertain equipment demand using revenue sharing contract model.

If centralized decision making is assumed, the authors find that the wind turbine order increases as the aftermarket service effort level and aftermarket service profit increase; aftermarket service effort level is positively correlative to the service efficiency. On the other hand, if decentralized decision making is assumed, the wind turbine order increases as share of the aftermarket service chain by manufacturer to wind farm increases and share of product supply chain by wind farm to manufacturer decreases. The optimal effort level of wind farm increases as the share of aftermarket service chain increases while the optimal effort level of the manufacturer is a concave function of share of aftermarket service chain if service quality linear correlates with effort level. Meanwhile, the authors find that the revenues of the product supply chain and aftermarket service chain have a concave relationship. This relationship is not affected by the format of relationship between service quality and effort level (linear or exponential).

The results could potentially be used to provide the wind turbine manufacturer with a greater profit space and satisfy wind farm’s equipment maintenance demand at the same time. It can also guide the practice of revenue sharing in the aftermarket service and manufacturing servitization.

In this model, the authors assumed that both the forward revenue sharing of power generation by wind farm to manufacturer and the backward revenue sharing of maintenance service by the manufacturer to wind farm exist in closed-loop product service chain. Then the authors discussed channel coordination of such cross-revenue sharing contract.

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.

The purpose of this paper is to explore the factors that determine non-farm enterprise revenue and to empirically test the association between access to credit, credit source and firm performance among poor entrepreneurs in rural Bangladesh.

Using a Bangladesh Institute of Development Studies and World Bank survey from over 1,700 households in rural Bangladesh, a panel data model is used to control for unobserved heterogeneity among households and explore the determinants of non-farm revenue.

The findings suggest that village infrastructure and household labor assets have a positive impact on enterprise development. The findings reveal that the use of rural credit as a production input is important in augmenting revenue for the non-farm enterprise, but there are differential effects by credit source.

Because the study uses data from a quasi-experimental survey design, unobserved effects that can bias the results must be controlled for. Also, as credit program impacts can be location-specific, caution in generalizing the results of this study must be exercised.

This study provides evidence on the positive effects of microcredit, family assets and family social capital on economic outcomes and microenterprise growth for poor entrepreneurial households. If enterprise growth is important for development, greater understanding of the determinants of microenterprise performance and the role of credit in the success of microfirms is beneficial for policymakers and the institutions that finance small-scale production.

If it is agreed that entrepreneurship is important in promoting development, self-sufficiency and positive economic outcomes (Yunus, 2007), then credit program design should focus on both the credit needs of the poor and the dynamics inherent in enterprise development for this group of entrepreneurs.

This paper expands the limited literature on the determinants of microenterprise growth and the role of credit in microenterprise development by tracing a positive link between village infrastructure, family demographics and access to credit. The identification of the factors that determine non-farm enterprise revenue is important for policymakers because enterprise growth is perceived as essential for economic development.