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.     

Reducing Pesticide Use and Pesticide Impact by Productivity Growth: the Case of Dutch Arable Farming

This paper employs a dynamic Data Envelopment Analysis (DEA) model to measure the composition of productivity growth of pesticides and the environmental impacts of pesticides. The application focuses on panel data of Dutch arable farms over the period 2003–07. A bootstrap regression model is used to explain farmers' performance, providing empirical evidence of the impact of producer‐specific characteristics and environmental factors. The results show that Dutch arable farms have substantial inefficiency in the use of pesticides and high pesticide environmental inefficiency, and appear rather unconcerned about the environmental impacts of their current pesticide use decisions on next period's production environment.     

Dynamic Inefficiency and Spatial Spillovers in Dutch Dairy Farming

This article examines the presence of spatial spillovers in farms’ dynamic technical inefficiency scores using Data Envelopment Analysis and a second-stage spatial truncated bootstrap regression model. Dynamic inefficiency is measured in terms of variable input contraction and gross investment expansion, while the second-stage model allows an individual’s dynamic inefficiency to be influenced by both own and neighbours’ characteristics. The empirical application focuses on the panel data of specialised Dutch dairy farms observed over the period 2009–2016 and for which exact geographical coordinates of latitude and longitude are available. The results confirm the existence of spatial spillovers in farmers’ dynamic technical inefficiency levels. Although changes in neighbours’ subsidies do not significantly influence an individual’s inefficiency, an increase in neighbours’ age reduces an individual’s performance, while an increase in neighbours’ levels of intensification improves an individual’s dynamic efficiency.     

Purchase of Catastrophe Insurance by Dutch Dairy and Arable Farmers

This article analyzed the impact of risk perception, risk attitude, and other farmer personal and farm characteristics on the actual purchase of catastrophe insurance by Dutch dairy and arable farmers. The specific catastrophe insurance types considered were hail–fire–storm insurance for buildings, disability insurance, crop insurance against hail, storm, and brown rot, and insurance against epidemic animal disease outbreaks. The results suggested that risk perception was a significant variable that influenced purchase of catastrophe insurance by dairy and arable farmers, whereas risk attitude was significant only in arable farming.     

Area Allocation Under Price Uncertainty on Dutch Arable Farms

This paper uses a Mean-Variance utility function to build a dual model that simultaneously determines area allocation and production/input levels under output price uncertainty. Regularity conditions of the indirect utility function (convexity) and producers risk preferences are tested. The framework is applied to a rotating sample of Dutch arable farms. Dutch arable farmers are found to be risk averse, with the size of the risk premium given by 3 per cent of annual profit. A bootstrap resampling method shows that curvature conditions are rejected. Price elasticities are compared for an unrestricted model and for a model with curvature conditions being imposed.     

尼日利亚奥约州作物耕作技术的应用研究

为了促进农业生产，研究人员开发了一些农业技术，这些技术在农民的使用中又表现出不同结果。本文设法对尼日利亚奥约州农民的作物耕作技术的理解和运用进行研究。通过多阶段随机抽样方法（问卷调查），本文选取了120农户对其卡方和皮尔逊积差进行研究，表明没有好处或没有副作用的技术农民也欣然采纳了。化肥使用了68．3％，农场碱残留的处理技术67＋5％，contour bonds使用10％，谷物／豆类套种技术88．3％。 论文运用皮尔逊积差相关系数（PPMC）对非意愿采纳和一些独立变量的关系进行了检验，结果表明获益、采纳、社会参与和与推广机构联系显著，而年龄、农户规模不显著。非意愿采纳和各变量的多元回归结果也表明他们间有显著的关系，最重要的因素是采纳、参加会议频率和禾薯的生产率。     

Farm‐specific Adjustment Costs in Dutch Pig Farming

This paper develops a dynamic model of investment under rational expectations, assuming farm‐specific production technologies and adjustment cost structures. The model distinguishes regimes of negative, zero and positive investments and maintains that it is optimal for a farmer not to invest for a range of shadow prices, depending on thresholds for positive and negative investments. The model is applied to a rotating sample of Dutch pig farms over the period 1980–1996. Farm‐specific parameters of the adjustment cost function and production technology are obtained using Generalised Maximum Entropy estimation. Cluster analysis using the farm‐specific adjustment cost parameters indicates that five groups of farms with distinct adjustment cost structures can be identified. A tobit regression analysis is used to explain the impact of different socio‐economic factors on the size of the threshold between positive and negative investments.     

Spatial Spillovers on Input‐specific Inefficiency of Dutch Arable Farms

Traditional benchmarking implicitly assumes that decision making units operate in isolation from their peers. For arable production systems in particular, this assumption is unlikely to hold in reality. This paper quantifies spatial spillovers on input‐specific inefficiency using data envelopment analysis and a second‐stage bootstrap truncated regression model. The bootstrap algorithm is extended to allow for the estimation of the parameter of the spatial weight matrix, which captures the proximity between producers. The empirical application concerns Dutch arable farms for which latitudes and longitudes are available. The average inefficiency across years was 3.87% for productive inputs and 2.98% for damage abatement inputs under variable returns to scale. For productive inputs technical inefficiency, statistically significant spillover effects from neighbours’ age and their degree of specialisation depended on the type of the spatial weight matrix used (inverse distance or k‐nearest neighbours). Statistically significant spillover effects of subsidy payments were adverse while statistically significant spillover effects from insurance payments were beneficial. For damage abatement inputs technical inefficiency, statistically significant adverse effects were found for neighbours’ age and subsidy payments and beneficial effects from neighbours’ insurance payments and their degree of specialisation.     

Profitability and Efficiency of High Nature Value Marginal Farming in England

The UK Brexit vote triggered a new wave of policy developments for a future outside the EU. In this context, we analyse the business performance of English hill and upland farms, characterised by marginal economic conditions but also high nature value (HNV). The analysis aims to help identify farm-level management and policy options for greater economic, environmental and social sustainability. Business performance is measured as technical efficiency and the occurrence and persistence of abnormal profits, estimated through stochastic frontier analysis and static and dynamic panel-data methods. The results help indicate rationales for recent trends including farm enlargement, farm family diversification, and agri-environment scheme entry. The single farm payment is found to be negatively associated with farm technical efficiency while agri-environmental subsidies were positively associated to short-term farm profitability. Farm adaptation and resilience during a period of likely turbulence in external circumstances is discussed in light of these findings, as well as potential parallels with marginal HNV areas across Europe.     

Linear Input Aggregation Bias in Nonparametric Technical Efficiency Measurement

An attraction of the nonparametric approach to measuring technical efficiency is that no a priori structure is placed on the production process of the firm. However, inputs are typically linearly aggregated, either explicitly or implicitly. It is shown that this introduces bias in the technical efficiency measurement. The computed technical efficiency measure becomes an economic efficiency measure comprised of both technical and allocative efficiency. An empirical application demonstrates the bias.     

A Comment on Weak Disposability in Nonparametric Production Analysis

In his 2005 paper in this journal, Kuosmanen argues that Shephard's specification of weak disposability in activity analysis (DEA) models is not correct. We show that Shephard's specification does satisfy weak disposability and is the "smallest" technology to do so.     

Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs

Weak disposability of outputs means that firms can abate harmful emissions by decreasing the activity level. Modeling weak disposability in nonparametric production analysis has caused some confusion. This article identifies a dilemma in these approaches: conventional formulations implicitly and unintentionally assume all firms apply uniform abatement factors. However, it is usually cost-effective to abate emissions in those firms where the marginal abatement costs are lowest. This article presents a simple formulation of weak disposability that allows for non-uniform abatement factors and preserves the linear structure of the model.     

Weak Disposability in Nonparametric Production Analysis: Reply to Färe and Grosskopf

Färe and Grosskopf (this issue) claim that a single abatement factor suffices for modeling weak disposability in nonparametric production models, and that the Kuosmanen (2005) technology that uses multiple abatement factors is larger than necessary. This article demonstrates by a numerical example that a single abatement factor does not suffice to capture all feasible production plans, and that its use leads to the violation of convexity, one of the maintained assumptions of the model. We also prove that the Kuosmanen technology is the correct minimum extrapolation technology under the stated axioms.     

Production Risk and Technical Efficiency in Organic and Conventional Agriculture – The Case of Arable Farms in Germany

This paper quantifies the importance of production risk and technical efficiency as two possible sources of production variability in German organic and conventional farming. Determinants of production risk and inefficiency are investigated based on a combination of Just and Pope’s stochastic production framework and a Stochastic Frontier Analysis. The empirical analysis is conducted using a balanced panel of farm records from 1999/2000 to 2006/2007 on 37 organic and conventional arable farms, respectively. Euclidian‐Distance‐Matching is used to identify for each organic farm a conventional counterpart with similar structural features. Results indicate that output variability in both production technologies is mainly caused by production risk. Land and labour are identified as risk‐increasing inputs in both farm types whereas higher capital endowment, seed costs and soil quality have risk‐reducing effects.     

四川省耕地生产效率及影响因素分析——基于DEA方法和Tobit模型的运用

运用数据包络分析(DEA)方法,对1999—2008年四川省耕地的生产效率进行测算,并运用Tobit模型分析影响耕地生产效率的主要因素。研究表明:10年来四川省耕地生产效率平均值为0.807,成都市历年来耕地生产效率有效值均为1;耕地生产效率较高的地区要注重规模效率的提高,而耕地生产效率较低的地区应加大技术投入力度;人均GDP、有效灌溉面积、劳动投入强度和耕地复种指数对耕地生产效率都具有不同方向和不同强度的影响。