Differential uncertainties and risk attitudes between conventional and organic producers: the case of Spanish arable crop farmers

The growing importance of economic factors in farmers' decisions to go organic has raised interest in characterizing the economic behavior of organic versus conventional farms. In general, published analyses so far have not considered differential uncertainties, abilities to control production risk, and farmers' risk preferences between conventional and organic practices when comparing these techniques. Our article attempts to assess this issue. We use a model of farmer decision under risk to analyze the differential values between organic and conventional Spanish arable crop farms and to assess the incentives for adoption of organic practices. Results show that organic and conventional farms do have different production risks as well as different aversions to risk. Organic price premiums and subsidies are found to be powerful instruments to motivate adoption of organic techniques.     

Outsourcing and efficiency: the case of Spanish citrus farming

Outsourcing in agriculture has traditionally been seen as a managerial strategy of smaller farms to achieve higher levels of efficiency. In this article, we provide empirical evidence supporting the existence of a positive relationship between outsourcing and efficiency in Spanish citrus farming. Outsourcing is measured by the proportion of outsourced labor and capital in farms' total use of these production factors, i.e., the higher the proportion of outsourced inputs, the higher the degree of outsourcing. Making use of data envelopment analysis techniques, we compute input‐specific reductions required to achieve technical efficiency at the farm level. Our results show that attainment of technical efficiency leads to a reduction in the use of both farms' own and outsourced production factors. Furthermore, the degree of outsourcing increases as farms move to their technically efficient productive plans. In addition, outsourcing labor and capital allows farms to achieve efficiency regardless of their size. In our view, this result has a clear implication for policy makers. Instead of trying to improve Spanish citrus farms' competitiveness by pursuing an increase of their average size, policy measures should be adopted to enhance farmers' managerial skills and the efficiency of those external service firms and co‐operatives that are effectively performing basic cultivation tasks.     

Feasibility of risk‐based inspections in organic farming: results from a probabilistic model

A risk‐based inspection system might improve the efficiency of the organic farming certification system and ultimately provide a basis for increased competitiveness of this sector. This requires the definition of an effective inspection procedure that allows statistical evaluation of critical risk factors for noncompliance. In this article, we present a study based on data from selected control bodies in five European countries that is aimed at determining the feasibility of risk‐based inspections in the organic sector according to the data that are currently routinely recorded. Bayesian networks are used for identification of the factors that can affect the risk of noncompliance. The results show that previous/concurrent noncompliant behavior explains most of the risk, and that the risk increases with farm size and the complexity of their operations. The data currently recorded by control bodies appear to be insufficient to establish an effective risk‐based approach to these inspections.     

Farmers’ Income and Production Responses to Rural Taxation Reform in Three Regions in China

The relationship between agricultural taxation and production efficiency has been thoroughly explored for many countries. Recently, China has taken various measures including the rural taxation reform (RTR) to promote grain production and to increase farmer incomes. In this study, we investigate whether the Chinese policy of abolishing rural taxation has improved farm households’ incomes and affected their production decisions. Using household survey data obtained from three regions in China, we estimate the effect of the RTR on farmers’ income. Results show that the RTR has significantly improved farmers’ post‐tax net income by 9.2% in Shandong, 16.9% in Shanxi and 16.8% in Zhejiang. These increments, mostly from farm income rather than from off‐farm income, are much higher than the direct income increase from the tax savings. In addition, we examine the dynamic impact of farmers’ net income, and find that the RTR has a sustained positive income effect in Shandong and Shanxi, whereas its positive effect in Zhejiang appears temporary. We also examine farmers’ production responses to the RTR. Results show that farmers in the three regions respond in different ways: farmers in Shandong significantly increase their labour input, farmers in Zhejiang increase intermediate inputs, whereas Shanxi farmers augment their intermediate inputs and enlarge their crop acreage. It appears that the farmers’ responses to the taxation reform vary due to the agronomic and economic factors in these three regions, suggesting that diverse post‐RTR supplemental policies should be implemented in different regions.     

Heterogeneous information exposure and technology adoption: the case of tissue culture bananas in Kenya

Classical innovation adoption models implicitly assume homogenous information flow across farmers, which is often not realistic. As a result, selection bias in adoption parameters may occur. We focus on tissue culture (TC) banana technology that was introduced in Kenya more than 10 years ago. Up till now, adoption rates have remained relatively low. We employ the average treatment effects approach to account for selection bias and extend it by explicitly differentiating between awareness exposure (having heard of a technology) and knowledge exposure (understanding the attributes of a technology). Using a sample of Kenyan banana farmers, we find that estimated adoption parameters differ little when comparing the classical adoption model with one that corrects for heterogeneous awareness exposure. However, parameters differ considerably when accounting for heterogeneous knowledge exposure. This is plausible: while many farmers have heard about TC technology, its successful use requires notable changes in cultivation practices, and proper understanding is not yet very widespread. These results are also important for other technologies that are knowledge‐intensive and require considerable adjustments in traditional practices.     

Social learning and technology adoption: the case of coffee pruning in Peru

A unique natural experiment involving a coffee pruning technology is used to study social learning. The yield effects of pruning take two years to appear, a characteristic that aids in identifying social learning apart from correlated unobservable variables that are a concern in the social learning and technology adoption literature. Panel data are employed that start with a private initiative which introduced systematic pruning in central Peru and that contain the population of participating growers. Results show a jump of at least 0.15 in the probability of adoption two years after the first pruning in a grower's group.     

Farm-level determinants of product conversion: Organic milk production

We investigate the role of technology in the decision of dairy farmers to convert to organic production methods. We measure the characteristics of the production technology using data from the USDA Agricultural Resource Management Survey and a recently developed functional form that allows for a global approximation to the unknown distance function without compromising approximation at the data boundaries. Conventional dairies with lower technical efficiency, higher returns to scale, and the ability to easily substitute away from restricted inputs are more likely to convert to organic production. Findings suggest further consolidation in the conventional industry as low-performing farms exits for the organic industry.     

Modelling the Crop Variety Demand of Semi‐Subsistence Households: Bananas in Uganda

We propose an approach to model the derived demand for crop varieties among semi‐subsistence farmers in a developing economy, and apply it to smallholder banana producers in Uganda. We model variety planting decisions as being composed of an extensive margin decision to grow a subset of locally available varieties (variety choice); and an intensive margin decision about the scale or extent of variety cultivation per farm (variety demand). We estimate variety demand equations using a more complete representation of the choice set upon which observed planting decisions are made. Computed elasticities of variety demand with respect to variety attributes indicate that the relative importance of consumption and production attributes varies by location and proximity to markets, from which we draw implications for the social and economic impact of crop improvement. The approach that we propose has broad appeal for analysing adoption decisions for modern or traditional varieties of both major and minor crops in developing countries.     

The increasing importance of nonfarm income and the changing use of labor and capital in rice farming: the case of Central Luzon, 1979–2003

There have been sharp increases in nonfarm income among farm households in Central Luzon for the last few decades. This study attempts to identify the effects of the increasing nonfarm income on the use of tractors and threshers and on the employment of hired labor as a substitute for family labor. We found that while the increased nonfarm income positively affects the ownership of tractors, it has no significant impact on the use of agricultural machines due presumably to the development of efficient machine rental markets. We also found that the increased nonfarm income leads to the increased use of hired labor, thereby releasing family labor to nonfarm jobs.     

The impact of coffee certification on small‐scale producers’ livelihoods: a case study from the Jimma Zone,Ethiopia

What is the impact of product certification on small‐scale farmers’ livelihoods? To what extent does the participation of Ethiopian small‐scale coffee farmers in certified local cooperative structures improve their socioeconomic situation? To answer these questions, this article employs household data of 249 coffee farmers from six different cooperatives collected in the Jimma zone of Southwestern Ethiopia in 2009. Findings show that the certification of coffee cooperatives has in total a low impact on small‐scale coffee producers’ livelihoods mainly due to (1) low productivity, (2) insignificant price premium, and (3) poor access to credit and information from the cooperative. Differences in production and organizational capacities between the local cooperatives are mirrored in the extent of the certification benefits for the smallholders. “Good” cooperatives have reaped the benefits of certification, whereas “bad” ones did not fare well. In this regard the “cooperative effect” overlies the “certification effect.”     

The Impact of Direct Income Transfers of CAP on Greek Olive Farms’ Performance: Using a Non‐Monotonic Inefficiency Effects Model

We analyse the impacts of direct income transfers on the technical efficiency of Greek olive farms. We use a production frontier function and a non‐monotonic inefficiency effects model, which incorporates the influences of exogenous variables (subsidies, farm characteristics, etc.) on technical efficiency. The model is applied to 1995–2004 FADN data. The results show that direct transfers of the CAP had a negative and monotonic effect on technical efficiency, whereas the degree of specialisation had a non‐monotonic effect on technical efficiency.     

Determinants of off‐farm work and its effects on farm performance: the case of Norwegian grain farmers

Limited attention has been given in the literature to the impact of off‐farm work on farm performance. More knowledge about the determinants of part‐time farming and its effects on farm performance could help policymakers to introduce better targeted rural development policies. The aim in this article is to fill part of the above‐mentioned gaps by analyzing factors that influence the choices of off‐farm work by either the farmer alone or jointly by both the farmer and partner; and simultaneously examining how off‐farm work influences farm performance. These analyses were based on an unbalanced panel data set from Norwegian grain farms during 1991 to 2005. Among the determinants of off‐farm work hours, we found that, in addition to demographic, time trend, and some regional effects, there was a significant negative effect of farm output on farmers' off‐farm work hours. The production function results revealed that off‐farm work had a positive effect on farm output, at first increasing but then decreasing with increase in hours spent in off‐farm work. Furthermore, our analysis revealed no systematic effect of off‐farm work on farm technical efficiency.     

The producer welfare effects of trade liberalization when goods are perishable and habit‐forming: the case of asparagus

Asparagus is a perishable, highly seasonal crop. We find that out‐of‐season imports of asparagus caused habit formation that increased demand in the U.S. growing seasons. We find that habit effects offset about 64% of the welfare losses to U.S. asparagus producers from increased Mexican imports under NAFTA and all of the U.S. producer welfare losses from increased Peruvian imports under the Andean Trade Preference Act. We estimate that the U.S. producer welfare losses from NAFTA are less than the annualized value of market loss assistance provided them in the 2008 Farm Bill.