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.     

Heterogeneity of Long‐run Technical Efficiency of German Dairy Farms: A Bayesian Approach*

In parametric efficiency studies, two alternative approaches exist to provide an estimate of the long‐run efficiency of firms: the dynamic stochastic frontier model and the generalised true random‐effects model. We extend the former in order to allow for heterogeneity in the long‐run technical efficiency of firms. This model is based on potential differences in firm‐specific characteristics and in firms’ inefficiency persistence. The model is applied to an unbalanced micro‐panel of German dairy farms over the period 1999 to 2009. Estimation of long‐run technical efficiency and inefficiency persistence is based on an output distance function representation of the production technology and estimated in a Bayesian framework. The results suggest that heterogeneity in long‐run technical efficiency of farms is mostly attributed to discrepancies in farm‐specific factors rather than differences in farms’ inefficiency persistence. Farm size is positively related to long‐run technical efficiency while subsidies exert a negative effect on the long‐run technical efficiency of farms. Inefficiency persistence is found to be very high, but heterogeneity in this persistence is low.     

Spatial dependency and technical efficiency: an application of a Bayesian stochastic frontier model to irrigated and rainfed rice farmers in Bohol,Philippines

We investigated the role of spatial dependency in the technical efficiency estimates of rice farmers using panel data from the Central Visayan island of Bohol in the Philippines. Household‐level data were collected from irrigated and rainfed agro‐ecosystems. In each ecosystem, the geographical information on residential and farm‐plot neighborhood structures was recorded to compare household‐level spatial dependency among four types of neighborhoods. A Bayesian stochastic frontier approach that integrates spatial dependency was used to address the effects of neighborhood structures on farmers’ performance. Incorporating the spatial dimension into the neighborhood structures allowed for identification of the relationships between spatial dependency and technical efficiency through comparison with nonspatial models. The neighborhood structure at the residence and plot levels were defined with a spatial weight matrix where cut‐off distances ranged from 100 to 1,000 m. We found that spatial dependency exists at the residential and plot levels and is stronger for irrigated farms than rainfed farms. We also found that technical inefficiency levels decrease as spatial effects are more taken into account. Because the spatial effects increase with a shorter network distance, the decreasing technical inefficiency implies that the unobserved inefficiencies can be explained better by considering small networks of relatively close farmers over large networks of distant farmers.     

Farms’ technical inefficiencies in the presence of government programs*

We focus on determining the impacts of government programs on farms’ technical inefficiency levels. We use Kumbhakar's stochastic frontier model that accounts for both production risks and risk preferences. Our theoretical framework shows that decoupled government transfers are likely to increase (decrease) DARA (IARA) farmers’ production inefficiencies if variable inputs are risk decreasing. However, the impacts of decoupled payments cannot be anticipated if variable inputs are risk increasing. We use farm‐level data collected in Kansas to illustrate the model.     

The extent of resource use inefficiencies in cotton production in Pakistan's Punjab: an application of Data Envelopment Analysis

This paper attempts to identify sources of resource use inefficiency for cotton production in Pakistan's Punjab. The use of a non‐parametric method, Data Envelopment Analysis (DEA), is developed to study the relative technical and allocative efficiencies of individual farms which use similar inputs, produce the same product and operate under comparable circumstances. In the ‘cotton‐wheat’ system of Pakistan, there are a considerable number of farms that are both technically and allocatively inefficient. The use of DEA shows that the technique provides a clear identification of both the extent and the sources of technical and allocative inefficiencies in cotton production. However, both the interpretation of the farm level results generated and the projection of these results to a higher level require care, given the technical nature of the agricultural production processes.     

Analysis of the spatial relationship between small olive farms to increase their competitiveness through cooperation

Small olive farms typically find it hard to compete with their larger competitors due to unfavourable conditions in terms of labour costs, land fragmentation and structural capital. These conditions result in higher production costs that reduce their competitiveness, leading to progressive exclusion from domestic and international markets and the abandonment of farming. In this scenario, cooperation between farmers to increase farm size and reduce land fragmentation may be an innovative strategy to improve the competitiveness of small agricultural holdings and avoid farm abandonment. The aim of this paper is to characterize the spatial structure of the traditional olive grove in the province of Jaén (South of Spain), the world’s leading olive oil producer, to identify the areas where farmer cooperation can be effectively implemented. The results of this study confirm that there are large numbers of small, barely viable olive groves and show different ways to promote cooperation between farmers according to the structural characteristics of their farms and their spatial relationships. In particular, when small olive farms have large neighbours, assisted cooperation systems should be implemented, while when small olive farms are concentrated in areas without larger farms, shared cultivation systems would be more efficient. This paper also provides information for the design of public policies aimed at enhancing the competitiveness of small agricultural holdings.     

Plot-level technical efficiency accounting for farm-level effects: Evidence from Chilean wine grape producers

This paper applies alternative panel data models to a cross-sectional dataset that contains observations at the plot level for a sample of wine-grape farms in Central Chile. The input–output data as well as key attributes of the production system are at the plot level, at which individualized management exists. However, plots belonging to a particular farm are also subject to overall centralized (farm-level) management. Thus, this data configuration offers the possibility of analyzing technical efficiency (TE) both across plots and across farms. A Generalized True Random Effects model, which permits the separate identification of farm-level and plot-level inefficiency while controlling for unobserved farm-level heterogeneity, shows that TE varies across farms but not among plots within the same farm. Geographical location also affects grape production and agro-climatic conditions influence production levels, with grape farms located on cooler zones producing significantly less than their counterparts in warmer zones, as expected. The analysis underscores the value of using recent methodologies typically applied to panel data when cross-sectional information is available for individual plots within a farm unit or in similar settings.     

The Technical Efficiency Impact of Farm Credit Programmes: A Case Study of Northern Germany

We analyse the technical efficiency of dairy farms in Schleswig‐Holstein that took part in the European Farm Credit Programme over the period 1987 to 1994. One goal of this programme is to increase the productivity of farms. We test whether participants show higher technical efficiency. We utilise a stochastic frontier model that allows for heteroscedasticity and estimation of determinants of technical inefficiency. Statistical tests indicate dominance of this model over alternative specifications. On average, we observe a high level of technical efficiency between 1987–94, but participation in the programme has rather led to a slight decrease. Thus, the programme seems to have failed to increase the competitiveness of farms.     

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.     

Predator or prey? Effects of farm growth on neighbouring farms

We provide explorative insights on how farms which manage strong and successful growth affect farms in their neighbourhoods through spatial competition for land. The study is based on an exploratory analysis of repeated framed experiments within the business game FarmAgriPoliS (Appel & Balmann, Ecological Complexity, 40, 2019). In particular, we analyse the spatial influences of different behavioural clusters of farm managers. Our analysis finds that farms which manage strong growth substantially affect the development of farms in a spatial neighbourhood of some 10 km. Although the influence on the neighbourhood decreases with distance, the functional correlations of farm growth as well as exits are neither linear nor exponential, but eventually rather wave-like. We further discuss the spatial interdependence of farms and the related overlaps of the predator–prey phenomenon with the phenomena of farms' path dependency and agricultural structural change. We conclude that along with farmers' strategies and their abilities, the characteristics of their neighbours and the distances between neighbouring farms also determine who is ‘predator’ and who is ‘prey’.     

IDENTIFICATION OF FACTORS WHICH INFLUENCE THE TECHNICAL INEFFICIENCY OF INDIAN FARMERS

The agricultural production of Indian farmers is investigated using a stochastic frontier production function which incorporates a model for the technical inefficiency effects. Farm-level data from the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) are used. Variables considered in the model for the inefficiency effects include the age and level of education of the farmers, farm size and the year of observation. The parameters of the stochastic frontier production function are estimated simultaneously with those involved in the model for the inefficiency effects. This approach differs from the usual practice of predicting farm-level inefficiency effects and then regressing these upon various factors in a second-stage of modelling. The results indicate that the above factors do have a significant influence upon the inefficiency effects of farmers in two of the three villages considered.     

Integrating spatial dependence into Stochastic Frontier Analysis

An approach to incorporate spatial dependence into stochastic frontier analysis is developed and applied to a sample of 215 dairy farms in England and Wales. A number of alternative specifications for the spatial weight matrix are used to analyse the effect of these on the estimation of spatial dependence. Estimation is conducted using a Bayesian approach and results indicate that spatial dependence is present when explaining technical inefficiency.     

Generalized Moments Estimation for Spatial Panel Data: Indonesian Rice Farming

We consider estimation of a panel data model where disturbances are spatially correlated in the cross-sectional dimension, based on geographic or economic proximity. When the time dimension of the data is large, spatial correlation parameters may be consistently estimated. When the time dimension is small (the usual panel data case), we develop an estimator that extends the cross-sectional model of Kelejian and Prucha . This approach is applied in a stochastic frontier framework to a panel of Indonesian rice farms where spatial correlations represent productivity shock spillovers, based on geographic proximity and weather. These spillovers affect farm-level efficiency estimation and ranking.     

Farm size,relative efficiency and agrarian policy in Côte d'Ivoire: profit function analysis of rice farms

This paper examines the relative economic efficiency of small and large rice farms in Côte d'Ivoire using a profit function approach. No differences in the relative economic efficiency of small and large farms were found. This conclusion is robust under alternative model specifications. Agrarian reforms directed towards further concentration of landholding for large farms in Côte d'Ivoire cannot be justified based on economic efficiency. Results show that access to credit and use of modern rice varieties significantly increase profits. To improve technical efficiency of rice farms, an accelerated program to provide information, credit, improved seeds and other inputs is needed. When all the farms (i.e. large and small) are taken together, there is evidence of allocative inefficiency. Strategies are needed to remove such management related inefficiencies in rice production either through the development of a better market price information system or effective farmer-oriented technical training programs by rice extension workers.     

Supply response in Ethiopia: accounting for technical inefficiency

Few empirical studies of supply response using the profit function have accounted for technical inefficiency. Using farm‐level panel data from Ethiopia, this study examines the effect of incorporating technical inefficiency in estimating the supply response of peasant farmers. Two systems of output supply and input demand equations are estimated and compared: the conventional model in which technical efficiency is assumed and another in which technical inefficiency is explicitly incorporated. The model with technical inefficiency is preferred on grounds of theoretical consistency and improved estimates, although model comparison tests are not conclusive. Incorporation of inefficiency generally increases the magnitudes and the statistical significance of own price elasticities, substantially so in the case of fertilizer and fertilizer‐intensive crops, and alters the priority attached to nonprice factors. An important result is that only the specification with inefficiency reveals a significant effect of access to extension services on output. Only this specification finds that output increases with household size, which one expects as the farms in the sample are largely subsistence and producing for own consumption. Furthermore, the results demonstrate that farmers' response to incentives is considerably restricted by inefficiency, suggesting that the traditional model would overstate response by excluding the efficiency variable.     

家庭农场经营效率及其差异分析*——基于山东234个示范家庭农场的调查

[目的]文章通过对山东省家庭农场经营效率的实证分析,旨在厘清技术、规模对农场经营效率的促进作用,通过比较分析找出各类型家庭农场短板,针对性地提出政策建议。[方法]以山东234个家庭农场数据为例,运用DEA模型对家庭农场全样本及纯种植、种养结合、种植兼休闲、种养兼休闲4类家庭农场的经营效率进行了测算和分解。[结果]首先,家庭农场综合技术效率仅为0. 170,纯技术效率和规模效率分别为0. 235和0. 786,规模效率相对充分纯技术效率不足是经营效率较低的主要原因;其次,种养结合类农场发展势头较好,纯种植类家庭农场发展滞后且综合技术效率和纯技术效率最低,种养兼休闲类农场的规模效率最低。[结论] 4类农场差异明显,应降低生产技术使用门槛,引导农场主参加职业教育,提升纯种植类农场纯技术效率,同时出台相关政策,实现土地流转的降费提效,改善种养兼休闲类农场规模效率。     

Patterns in Technical Efficiency and Technical Change at the Farm‐level in England and Wales, 1982–2002

English and Welsh farm‐level survey data are employed to estimate stochastic frontier production functions for eight different farm types (cereal, dairy, sheep, beef, poultry, pigs, general cropping and mixed) for the period 1982 to 2002. Differences in the relative efficiency of farms are explored by the simultaneous estimation of a model of technical inefficiency effects. The analysis shows that, generally, farms of all types are relatively efficient with a large proportion of farms operating close to the production frontier. However, whilst the frontier farms of all types are becoming more efficient through time because of technical change, it is also the case that the efficiency of the average farm for most farm types is increasing at a slower rate. In addition, annual mean levels of efficiency for most farm types have declined between 1982 and 2002. The factors that consistently appear to have a statistically significant effect on differences in efficiency between farms are: farm or herd size, farm debt ratios, farmer age, levels of specialisation and ownership status.     

Nonparametric analysis of technical,pure technical,and scale efficiencies for food crop production in East Java,Indonesia

Nonparametric analysis of technical efficiency for irrigated farms in the Madiun regency in the west-central part of East Java, Indonesia is conducted using linear programming techniques. This procedure allows the relative technical efficiency for each farm to be determined and for inefficiencies to be decomposed into pure technical inefficiency and scale inefficiency and does not require restrictions or assumptions regarding functional form to be placed on the data. Farmers in Madiun generally are efficient relative to each other. Farmers operating inefficiently do so more often because of scale inefficiencies rather than pure technical inefficiencies. A majority of the farms operate in the region of decreasing returns to scale rather than increasing returns to scale. Farmer age, the level of diversification of cropping activities, and high school education were found to be related to technical efficiency in the rainy season under irrigated conditions. Other socioeconomic factors were not statistically significant. The results imply that inefficient farms use excessive levels of inputs, particularly nitrogen fertilizer. This is perhaps due to the lingering effects of past input subsidization policies, particularly of fertilizers, in Indonesia, or to risk-reducing behavior. The results also imply that current government policies to encourage diversification of cropping practices in Java may lead to greater technical inefficiencies in production. In addition, extension education targeted to younger farmers with low levels of formal education would improve efficiency.     

Input Disposability and Efficiency in Dutch Arable Farming

This paper develops a test for disposability of individual inputs based on non‐radial efficiency measures. Furthermore, the paper analyses the impact of congestion on overall technical efficiency for individual inputs. The application uses panel data from Dutch cash crop farms over the period 1989–1992. A significant difference between the efficiency measures under different assumptions on input disposability is detected by a t‐test, indicating that all inputs are weakly disposable. Analysis of the composition of overall technical efficiency reveals that weak disposability constitutes the largest component of inefficiency. Moreover, congested farms on average have a less effective management and operate on a larger, though less efficient, production scale.     

The role of family life-cycle events on persistent and transient inefficiencies in less favoured areas

Family farms dominate less favoured areas (LFAs) within Europe, and family life-cycle conditions, such as succession and retirement, affects how these farms adapt to changing circumstances. Past studies of on-farm technical efficiency have not directly addressed these conditions, but they may explain why some farms are more efficient than others, especially as the farm family model dominates most farming systems. Motivated by the UK's withdrawal from the EU and the debate around establishing replacement support policies, we apply a multi-step model to measure both transient and persistent inefficiencies using a panel of LFA cattle and sheep farms in Scotland over the period 2003–2020. We find a greater prevalence of persistent compared to transient inefficiency, which suggests that structural problems still exist. Farms with planned succession are found to have higher persistent efficiencies, whereas farmers nearing retirement have lower levels. Other factors, such as dependence on subsidy, off-farm activity and classification as severely disadvantaged tend to compound these lower efficiencies. We argue that life-cycle conditions should not be ignored in studies of farm technical efficiency. Within the scope of framing a new agricultural policy for UK administrations, these results inform the debate on support for LFAs, as well as the promotion of support towards generational renewal to ease transition across farm family life-cycle events.