Analysing Production Technology and Risk in Organic and Conventional Dutch Arable Farming using Panel Data

This paper compares the production technology and production risk of organic and conventional arable farms in the Netherlands. Just–Pope production functions that explicitly account for output variability are estimated using panel data of Dutch organic and conventional farms. Prior investigation of the data indicates that within variation of output is significantly higher for organic farms, indicating that organic farms face more output variation than conventional farms. The estimation results indicate that in both types of farms, unobserved farm‐specific factors like management skills and soil quality are important in explaining output variability and production risk. The results further indicate that land has the highest elasticity of production for both farm types. Labour and other variable inputs have significant production elasticities in the case of conventional farms and other variable inputs in the case of organic farms. Manure and fertilisers are risk‐increasing inputs on organic farms and risk‐reducing inputs on conventional farms. Other variable inputs and labour are risk increasing on both farm types; capital and land are risk‐reducing inputs.     

Effect of yield and price risk on conversion from conventional to organic farming*

Although the benefits of organic farming are already well known, the conversion to organic farming does not proceed as the Dutch government expected. In order to investigate the conversion decisions of Dutch arable farms, a discrete stochastic dynamic utility‐efficient programming (DUEP) model is developed with special attention for yield and price risk of conventional, conversion and organic crops. The model maximizes the expected utility of the farmer depending on the farmer’s risk attitude. The DUEP model is an extension of a dynamic linear programming model that maximized the labour income of conversion from conventional to organic farming over a 10 year planning horizon. The DUEP model was used to model a typical farm for the central clay region in the Netherlands. The results show that for a risk‐neutral farmer it is optimal to convert to organic farming. However, for a more risk‐averse farmer it is only optimal to fully convert if policy incentives are applied such as taxes on pesticides or subsidies on conversion, or if the market for the organic products becomes more stable.     

Off‐farm work,technical efficiency,and rice production risk in Taiwan

This article investigates the differences in yield production, production efficiency, and yield risk for farmers both with and without off‐farm work. Using a nationwide survey of rice farmers in Taiwan, we estimate two stochastic production frontier models that accommodate technical inefficiency and production risk simultaneously for farmers both with and without off‐farm work. The stochastic dominance criterion is then applied to compare the differences in the distributions of the estimated technical efficiency and yield risk between groups. The empirical results indicate that these two groups of farmers use resources in different ways, and off‐farm work is not necessarily associated with lower technical efficiency. For farmers in the lower percentiles of the efficiency distribution, those with off‐farm work are more efficient than their counterparts without off‐farm work. In addition, farmers with off‐farm work face higher production risk and this result is robust for the entire distribution.     

Farmer responses to changing risk aversion,enterprise variability and resource endowments

The focus of this article is on assessing how risk aversion, enterprise variability and resource endowments affect farm land‐use decisions and economic returns. A theoretical model of a two‐enterprise, two‐constraint farm is developed, and then, an empirical illustration for an Australian farm is provided. The methodology used builds on previous expected mean‐variance (EV) models by incorporating land and budget constraints. The Kuhn–Tucker conditions of the EV model are examined to highlight that changes in resource endowments have larger effects on economic returns, than do changes in risk aversion or enterprise gross margin variability. It was also found that combinations of enterprise mixes that do not use all available resources can produce higher economic returns, relative to some enterprise mixes that use all available resources.     

Risk aversion in agricultural water management investments in Northern Ghana: experimental evidence

Sub‐Saharan Africa (SSA) is one of the regions in the world most affected by food price volatility and production variability. Poor small‐scale farmers in this region are particularly vulnerable to this variability. As a result, households may be reluctant to adopt new agricultural water management (AWM) technologies when they involve more risk than what they mitigate. Despite risk's role in AWM investments, there have been few attempts to estimate the magnitude and nature of risk aversion in relation to this type of farm decisions. To partially close this gap, this article uses an experimental approach applied to 137 households in Northern Ghana. We find that more than 70% of households are moderately or slightly risk averse. This contrasts with other studies in SSA, where most household decision‐makers exhibit severe to extreme risk aversion. We also find that households that stand to lose as well as gain something from participation in games are less risk averse than households playing gains‐only games. This result suggests that most farmers’ current wealth put them at risk of falling into a poverty trap. Thus, the losses from the riskiest investments on AWM technologies may fall more heavily on the poor, suggesting that additional efforts be given to the creation of viable insurance mechanisms.     

Calculating environmental cost indicators of apple farm practices indicates large differences between growers

This study evaluates the environmental impact of current apple cultivation practices in Flanders, Belgium. It evaluates integrated production, the most common practice, and it compares this production method with conventional and organic production. The assessment was based on Farm Accountancy Data Network data from 2010 to 2012 for 64 farms in the region and a life cycle approach was used. The findings showed no significant improvement in environmental impacts for integrated farms compared to conventional farms and, even more, the former showed significantly higher average impacts per hectare for the categories ‘acidification’, and ‘non-renewable energy use’ in comparison with the latter. The organic production group showed higher average impacts per kilogram due to lower yields. Secondly, impacts related to the categories ‘acidification’, ‘eutrophication’ and ‘global warming potential’ were monetized based on the shadow price method in order to obtain external costs. Results show that external costs increase the production costs for integrated farming at least with 5%, both when these costs are expressed per kilogram and per hectare. However, the findings show a large variability in impacts and costs per farm. Farm-specific practices have therefore an important influence on the total environmental cost rather than production group-specific practices.     

Adoption of climate‐smart practices and its impact on farm performance and risk exposure among smallholder farmers in Ghana

Increased climate variability during the last four decades has made the agricultural environment in many developing countries more uncertain, resulting in increasing exposure to risk when producing crops. In this study, we use recent farm‐level data from Ghana to examine the drivers of individual and joint adoption of crop choice and soil and water conservation practices, and how adoption of these practices impacts on farm performance (crop revenue) and exposure to risks (skewness of crop yield). We employ a multinomial endogenous switching regression model to account for selectivity bias due to both observable and unobservable factors. The empirical results reveal that farmers’ adoption of crop choice and soil and water conservation leads to higher crop revenues and reduced riskiness in crop production, with the largest impact on crop revenues coming from joint adoption. The findings also show that education of the household head, access to extension and weather information influence the likelihood of adopting these practices. Thus, enhancing extension services and access to climate information and irrigation can reduce gaps in adoption of soil and water conservation and crop choice, considered as climate‐smart practices that will eventually improve crop revenues and reduce farmers’ exposure to climate‐related production risks.     

Production risk,risk aversion and the determination of risk attitudes among Spanish rice producers

Agricultural production is subject to risk and the attitudes of producers toward risk will influence input choices insofar as these affect production risk. Risk attitudes in turn may be affected by certain socioeconomic characteristics of producers. Using 2004 survey data from a cross‐section of 130 Spanish rice farms, we estimate risk‐aversion coefficients of farmers and investigate the influence of a series of socioeconomic variables on their risk attitudes. Our results show that farmers exhibit risk‐averse behavior and that risk attitudes are related to a series of socioeconomic characteristics. In particular, the belief that the farm will continue after the producer retires is found to increase the degree of risk aversion, while age is found to have nonlinear effects on risk aversion. Off‐farm income, especially from nonagricultural activities, is found to reduce risk aversion. Neither the educational level of the producer nor the presence of dependents on the household is found to have an effect on risk preferences. Regarding the production technology, we find that land, labor, and fitosanitary products are risk‐reducing inputs, whereas capital, seeds, and fertilizer all increase risk.     

The carbon footprints of food crop production

The agriculture sector contributes significantly to global carbon emissions from diverse sources such as product and machinery manufacture, transport of materials and direct and indirect soil greenhouse gas emissions. In this article, we use farm survey data from the east of Scotland combined with published estimates of emissions for individual farm operations to quantify the relative contribution of a range of farming operations and determine the carbon footprint of different crops (e.g. legumes, winter and spring cereals, oilseed rape, potato) and farming practices (conventional, integrated and organic). Over all crops and farm types, 75% of the total emissions result from nitrogen fertilizer use (both organic and inorganic)—from production, application, and direct nitrous oxide emissions from the soil resulting from application. Once nitrogen is accounted for, there are no major differences between organic, integrated or conventional farming practices. These data highlight opportunities for carbon mitigation and will be of value for inclusion in full life cycle analyses of arable production systems and in calculations of greenhouse gas balance associated with land-use change.     

Acreage Response to Whole Farm Income Stabilisation Programmes

This article investigates whether Canadian whole farm programmes, which fall under the WTO category of Green Box subsidies, are truly production neutral. Theory suggests that with non‐constant risk aversion, risky decisions can be influenced by both the level of expected wealth (i.e. the wealth effect) and the variability of wealth (i.e. the insurance effect). Unlike previous approaches, this article is able to extend a framework developed by Chavas and Holt to formally incorporate the insurance effect into the acreage allocation decisions. By applying the theoretical model to acreage data in the Canadian Prairies, the results reveal that the whole farm income stabilisation programmes had large impacts on acreage choices through wealth and insurance effects. From a WTO perspective, the results underline the inherent difficulty in designing programmes that will reduce the risk faced by farmers without altering behaviour.     

Is there a future for small farms in developed countries? Evidence from the French case

This research aims to identify the specific characteristics of small farms in developed countries and the factors that influence their survival and growth. Using the case of France, we employ statistical and econometric analysis of data from the Farm Structure Survey (N = 70,000) for the period 2000–2007. The principal findings suggest that small farms are no more likely than other farms to employ “alternative” strategies to the predominant model of increasing farm size, nor are they more likely to diversify on‐farm activities or operate under quality‐labeled production systems, with the notable exception of organic agriculture. However, where small farms do adopt or practice these activities, they are seen to have a favorable effect in ensuring their survival and growth. In contrast, we are unable to conclude that pluriactivity of farm households has a positive impact on the survival of small enterprises. The effect of geographical location on small farms is largely expressed in their concentration in mountainous or disadvantaged regions. Overall, the trajectory of small farms is marked by farm exit, principally as the result of farmers retiring at the end of their careers. The small farm sector is also revitalized by both larger farms declining and thus being reclassified as small farms, as well as the progressive entry into agriculture of small farm holders whose income was previously derived largely off‐farm.     

Comparing economic performance of organic and conventional U.S. beef farms using matching samples*

Economic performance measures of organic and transitioning‐to‐organic cow–calf farms are compared with those of non‐organic cow–calf farms. A method of matching samples is used for the comparison, estimating sample average treatment effects for the subpopulation of the treated. Each organic farm is matched with one non‐organic farm that is involved in the same beef industry segments and farm size classes, and in the same region. Furthermore, farmer demographic, farming system, and technology variables are used to identify matches. Bias is reduced by estimating separate weighted regression functions for the treated and untreated groups. Results suggest that higher cost of organic production is due primarily to higher capital recovery, taxes and insurance, and overhead costs. Evidence is found for differences in beef enterprise profitability by organic status.     

Agricultural Policy Reform and Off‐farm Labour Decisions

Off‐farm labour decisions of a sample of Kansas farmers are evaluated. The central question of our analysis pertains to whether 1996 US farm policy reforms may have altered the decisions to work off the farm. The effects of policy decoupling on off‐farm labour are complex: different aspects of policy changes can have opposing effects on off‐farm work decisions. Essentially, this makes this issue an empirical question. Results show that the introduction of fixed, decoupled payments in 1996 might have reduced the likelihood of off‐farm labour participation. However, the new policy environment may have increased farm households’ revealed aversion to risk, motivating a higher participation in non‐farm labour markets. The effects of 1996 policy reforms on farm income variability could have been attenuated by changes in US crop insurance programmes and by an increase in emergency assistance payments towards the end of the 1990s. The reduction in price supports may have increased the motivation for working off the farm. The net effect of the overall reforms on off‐farm work participation is not likely to have been large.     

Specialization,diversification, and productivity: a panel data analysis of rice farms in Korea

This article examines the microeconomics of productivity associated with specialization/diversification in production activities, with an application to Korean rice farms. Korean rice farms tend to be very small and highly specialized. Our analysis examines the productivity effects associated with both farm size and farm specialization/diversification in Korean agriculture. Relying on farm‐level panel data, the analysis studies farm productivity in a multi‐input multi‐output context, accounting not only for changes in inputs and technical change in rice production, but also for the role of diversification in the production of other crops in current and previous periods. We find positive but small productivity gains from farm diversification. These gains come mostly from complementarity effects across farm outputs, with minimal effect of scale economies. The positive complementarity effects work against nonconvexity effects, which provide strong productivity incentives for rice farms to specialize.     

Farm machinery use,off‐farm employment and farm performance in China

We analyse the joint impacts of farm machinery use and off‐farm employment on maize yields and agrochemical expenses from a household survey of 493 farmers in China. Our findings are obtained from an innovative two‐stage econometric procedure that combines a bivariate ordered probit model with an endogeneity‐corrected ordinary least square regression model. The results show that farmers are jointly making decisions to use farm machines and to work off the farm and that these two household activities affect maize yields and agrochemical expenses in different ways. We show that farm machinery use significantly increases both maize yields and agrochemical expenses, while off‐farm employment significantly decreases agrochemical expenses. Our findings highlight the importance of additional machinery use in increasing farm production; the need to account for possible endogeneity in estimation; and the statistical significance of key household characteristics (gender, education, and household size) on overall farm production.     

Survey and Analysis of Labour on Organic Farms in the UK and Republic of Ireland

A survey of 1144 organic farms in the UK and Republic of Ireland (IE) was used to assess whether organic agriculture provides more labour than conventional (nonorganic) farming. The sampled farms comprised 23% of all organic farms. The jobs per farm and per area varied greatly with enterprise type and farm size, and between regions. Comparison of the survey with national statistics showed that organic farms employ 135% more FTE (full time equivalent jobs) per farm than conventional farms. The mean jobs per area was markedly lower for organic farms (1.35 compared to 2.43 FTE per 100 ha), because they are larger (216 ha compared to 51 ha). Even when corrected for the different size distribution, organic farms had more jobs per farm than the national averages (2.52 and 1.49 FTE for the UK and IE, compared to 1.28 and 1.16 FTE). The farm size weighted FTE per area for organic farms in the UK (4.33 FTE per 100 ha) was almost twice that for conventional farms. We predict there would be 19% and 6% more farming jobs in the UK and IE if 20% of the farms of both countries were to become organic (compared to the present 1–2%).     

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.     

Bayesian Clustering of Farm Types Using the Mixtures Model

A Bayesian method of classifying observations that are assumed to come from a number of distinct subpopulations is outlined. The method is illustrated with simulated data and applied to the classification of farms according to their level and variability of income. The resultant classification shows a greater diversity of technical charactersitics within farm types than is conventionally the case. The range of mean farm income between groups in the new classification is wider than that of the conventional method and the variability of income within groups is narrower. Results show that the highest income group in 2000 included large specialist dairy farmers and pig and poultry producers, whilst in 2001 it included large and small specialist dairy farms and large mixed dairy and arable farms. In both years the lowest income group is dominated by non‐milk producing livestock farms.     

Self‐protection from weather risk using improved maize varieties or off‐farm income and the propensity for insurance

We investigate how self‐protection from the adoption of Improved Maize Varieties (IMV) and off‐farm income affects risk premiums for smallholder maize producers in Uganda. To unbundle these effects, we specify the cost of risk to explicitly capture four risk components—mean, variance, skewness, and kurtosis. Using unique plot‐level panel data for Uganda, we estimate and test moments of a flexible production function based on an expanded form of the Johnson S_U family distribution and proceed to simulate the degree of responsiveness of risk premiums and welfare estimates to marginal changes in the share of land under IMV and off‐farm income. Scenarios of joint adoption of IMV accompanied with low and high application of inorganic fertilizer, and the effect of off‐farm income when there is high and low supply of farm labor are examined. Results show that the use of IMV and off‐farm income substantially reduces risk premiums and the individual effect is much higher under low fertilizer application and high supply of farm labor, respectively. Thus implying that self‐protection is likely to reduce the propensity for index insurance especially if its design fails to consider the reduction in downside risk.     

Production Risks and Food Security under Alternative Technology Choices in Malawi: Application of a Multinomial Endogenous Switching Regression

Employing nationally representative data, we investigate the impact of Sustainable Intensification Practices (SIPs) on farm households’ food security, downside risk and the cost of risk in Malawi. The analysis relies on a flexible moment‐based specification of a stochastic production function in a multinomial endogenous switching regression framework to correct for the selection bias stemming both from observed and unobserved heterogeneity. A quantile moment approach is used to estimate the cost of risk. After controlling for the effects of unobserved heterogeneity and several observable variables on maize production and downside risk functions, estimation results show that the adoption of SIPs increases food security and reduces downside risk exposure and the cost of risk. We estimate greater food security and larger reduction in downside risk from simultaneous adoption of both crop diversification (maize–legume intercropping and rotations) and minimum tillage, suggesting that there are complementary benefits from these practices. We find most of the cost of risk comes from exposure to downside risk. Our findings imply that in dealing with production risks development agents should encourage the adoption of agronomic and resource‐management practices along with other risk mitigation and food security improving strategies.