Learning in switching to organic farming

This paper estimates technical efficiency of organic and conventional dairy farming and its development over time. We control for possible selection bias and regional heterogeneity. The results suggest that technical efficiency measured as a ratio between actual and maximum obtainable output (relative to the peer group) at first diminishes when the conversion towards organic production starts. After 6-7 years from the switch, technical efficiency starts to increase again

Lowland farming system inefficiency in Benin (West Africa):

This paper uses a directional distance function and a single truncated bootstrap approach to investigate inefficiency of lowland farming systems in the Benin Republic. First, we employed a dual approach to estimate and decompose short-run profit inefficiency of each farming system into pure technical, allocative and scale inefficiency and also into input and output inefficiency. Second, an econometric analysis of factors affecting the inefficiency was generated using a single truncated bootstrap procedure to improve inefficiency analysis statistically and obtain consistent estimates. In the short run, scale, allocative and output inefficiency were found to be the main sources of inefficiency. Based on inefficiency results, the inefficiency of lowland farming systems is the most diverse. Compared to a vegetable farming system, technical inefficiency is significantly higher if farmers switch to a rice farming system. Scale, allocative, output, and input inefficiency are significantly lower with an integrated ricevegetable farming system and there was high prevalence of increasing returns to scale in the integrated rice-vegetable farming system. Water control and lowland farming systems are complements and play a significant role in the level of inefficiency. Input inefficiency shows the difficulty that the producers face in adjusting the quality and quantity of seeds and fertilizers. The paper provides empirical support for efforts to promote an integrated rice-vegetable farming system in West Africa lowlands to increase food security. Keywords Lowlands . Inefficiency . Bootstrap . Beni

Creating a typology of tobacco farms according to determinants of diversification in Valle de Lerma (Salta-Argentina)

The objective of this article is to identify typical tobacco farms according to determinants of diversification that can be used to explore possibilities of diversification in the province of Salta (Northwest of Argentina). National Agriculture Census data of 278 farms in the main tobacco production area of Salta were used for the analysis. The variables selected concerning determinants of diversification were: land area, irrigation, general capital goods and specific capital goods, ownership of land, education, off-farm work, and labour availability. The analysis of the principal components applied to 16 selected variables allowed to reduce the dimensionality of the data to four components. Those components were used to apply K-means cluster approach to classify the farms. Four clusters were determined. Cluster 1 and Cluster 2 are the largest clusters. These concern highly specialized tobacco farms. They differ regarding determinants for diversification due to different levels of education of the farmer and different levels of off-farm work. Both clusters are interesting for further analysis regarding diversification alternatives to maintain or improve income and to reduce soil degradation. Cluster 3 concerns large tobacco farms being somewhat less specialized than the farms in Clusters 1 and 2. Intensive tobacco production makes this group interesting for exploring diversification alternatives to improve soil conditions. Farms in Cluster 4 already have a high level of diversification with substantial livestock production. The presence of perennial pastures suggests a better soil management than the other clusters. This cluster looks appealing to investigate what can be done regarding diversification

Resilience of food companies to calamities - perceptions in the Netherlands

Calamities such as extreme droughts and trade or infrastructure breakdowns potentially hamper the continuity of individual food companies, as well as the continuity of food supply in Europe at large. There is a lack of insight into food companies’ resilience in case of cumulative calamities or calamities that did not happen before in recent history. In this context, an expert elicitation study among feed and food companies in the Netherlands was undertaken. Results show that lengthy or structural unavailability of electricity and a lengthy crisis of road transport are perceived as the most threatening calamities.Outcomes also show a relatively limited implementation of BCM (business continuity management) at company level. Complete BCM programs for top-3 calamities perceived to threaten the continuity of food supply in Europe are reported by 0% to 30% of the companies. For calamities perceived to be important for business continuity this is between 20% and 40%. In the field of risk management a leading role is attributed to the public sector for improving international governance and setting up a so-called masterplan with measures such as larger raw-materials stocks and broad sourcing. Findings suggest that further actions are needed, starting with prioritised calamities and the design of a masterplan. Yet, stakeholders are also urged to pro-actively “think the unthinkable

Anomalous dielectric behaviour of La(III) substituted lead titanate ceramics

In La(III) substituted PbTiO3 ceramics the behaviour of the reciprocal dielectric constant in the paraelectric phase can be described by the relation [...] with the exponent 1 γ<2 depending on the composition. This γ-value is an intermediate of values for Curie-Weiss behaviour (γ = 1) and of values connected with diffuse phase transitions (γ = 2) and increases with increasing La(III) concentration.\ud \ud An excellent agreement between experimental and calculated permittivity curves in the paraelectric phase can be achieved using an alternative equation consisting of a linear and a quadratic term with coefficients varying systematically with the composition. The last equation can be derived and interpreted by means of a physical model assuming the existence of heterophase fluctuations

Dynamic Efficiency Analysis using a Directional Distance Function

Input-based dynamic efficiency measures are derived from an adjustment-cost directional distance function approach. A dynamic input directional distance function can be generated from an adjustment-cost technology where the dynamics are explicitly incorporated in the form of the properties of the input requirement sets with respect to the quasi-fixed factors. The properties of the dynamic input directional distance function are inherited from the properties of the technology. The efficiency measures are then applied to a panel data set of Dutch horticulture firms over the period 1991-1995.Productivity Analysis,

Learning in Organic Farming An Application on Finnish Dairy Farms

Organic farming technology may be relatively unknown to farmers at the time when they switch from conventional into organic farming. Therefore, experience gained over time and learning by doing may be important determinants in the efficiency of organic farming. It may also take time to reach the optimal nutrient stock of soil and optimal nutrient supply for arable crops under organic farming. Thus, efficiency of organic farming can either grow or decrease over time depending on the nature of the technology and the learning process. This paper estimates technical efficiency of organic farming and its development over time. We control for possible selection bias and regional heterogeneity when estimating a stochastic frontier distance functions for a sample of conventional and organic dairy farms in Finland. The results suggest that organic dairy farms are less technically efficient than conventional farms. Technical efficiency at first diminishes when the conversion towards organic production starts. After 6 years from the switch, technical efficiency starts to increase again. The estimates signal that the length of the conversion and learning process of organic farming is in average 6-7 years.technical efficiency, technical change, output distance function, SFA, Research and Development/Tech Change/Emerging Technologies, C23, D24, D83, O30, Q12,