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This paper analyses the investment behaviour of Russian farms during the period of economic stabilisation that followed Russia's financial crisis of 1998, and is the first to apply the error-correction investment model to describe farms' investment behaviour in the transitional context. Additionally, the paper employs the error-correction and the adjustment-cost model to test for differences in the investment behaviour between various farm categories. The results show that in general Russian farms exhibited an error-correcting behaviour in the period under investigation. From 1999 to 2005 the output¿capital gap was closed by an average rate of 10% per year. Estimates of the adjustment-cost model show that Russian farm investments are very sensitive to the sales¿capital ratio, suggesting that Russian farms exhibit increasing returns to scale and positive expectations about future revenues. Yet, such farm characteristics as ownership structure, access to input markets and also regional specifics were found to be decisive for farm investment not only in the short but long term too. Finally, the results show that the adjustment-cost model is adequate for the evaluation of differences in short-term investment behaviour, whereas it is noticeably less powerful for investigating differences in the farms' long-term investment behaviour

For nearly 30 years, technologies for more sustainable land use have been developed and promoted in Rwanda. However, these technologies have not been fully adopted. Keeping in mind that the farming population is not homogeneous with respect to socio-economic variables, this paper typifies farm households in Umutara province based on socio-economic factors influencing the adoption of new technology. A multivariate analysis approach that combines Principal Component Analysis and Cluster Analysis allowed us to identify clearly five types of farm households and their socio-economic characteristics. The main differences between the five farm types relate to gender, age, education, risk perception, risk attitude, labour availability, land tenure and income. The five farm types are characterized by respectively having a female head (26% of the farms), being a tenant (7%), having a male and literate head (32%), having an illiterate head with no off-farm activities (18%), and being a large farm with livestock (17%). The respective farm types appeared to have adopted different types of sustainable technologies to a limited extent. Female-headed households adopted the use of compost and green manure. Young male literate farmers were the only ones using chemical fertilizers. Illiterate and full-time farmers applied fallow, manure and erosion control measures to maintain soil fertility. The use of improved livestock is adopted by large farms.

The performance of agricultural cooperatives depends on their business objectives, which are defined in different ways in the literature. We review the theoretical literature on the performance of agricultural marketing cooperatives. Studies can be divided into two classes, those that assume a single objective and those that assume multiple objectives. This classification integrates three views of the cooperatives: ( a) vertical integration of firms, ( b) independent enterprise, and ( c) coalition of firms. Empirical studies on the financial performance of cooperatives are classified into two categories, studies based on the economic theory of the firm and studies that emphasize accounting techniques. Empirical studies have failed to address the cooperatives’ objectives as represented by the theoretical literature on cooperative performance.

We introduce the concept “excess capital capacity” and employ a stochastic input requirement frontier to measure excess capital capacity in agricultural production. We also propose a two-step estimation method that allows endogenous regressors in stochastic frontier models. The first step uses generalized method of moments to get consistent estimates of the frontier parameters in the presence of endogenous regressors. The second step uses maximum likelihood to measure excess capital capacity and evaluate the factors that influence it. The empirical application to Dutch cash crop farms found varying degrees of excess capital capacity. The policy implications of excess capital capacity are discussed. Copyright 2005, Oxford University Press.

Plant import inspection can prevent the introduction of exotic pests and diseases, thereby averting economic losses. We explore the optimal allocation of a fixed budget, taking into account risk differentials, and the optimal-sized budget to minimise total pest costs. A partial-equilibrium market model is used to compute the economic consequences of pest invasion. An application to Dutch imports of chrysanthemum cuttings shows that the optimal allocation of a fixed inspection budget halves the cost of pest invasion compared to allocating the same budget equally over all imports. A budget increase that enables 42 per cent more inspection can reduce total societal costs by 81 per cent compared to smaller, constrained budget that ignores risk differentials. Oxford University Press and Foundation for the European Review of Agricultural Economics 2009; all rights reserved. For permissions, please email journals.permissions@oxfordjournals.org, Oxford University Press.

PurposeMeasurement of the performance of entire supply chains is an important issue because it allows for “tracking and tracing” of efficacy and efficiency failures and leads to more informed decision making with regard to chain design. However, the choice of appropriate supply chain performance indicators is rather complicated due to the presence of multiple inputs and multiple outputs in the system. Therefore, this paper aims to evaluate the usefulness of a novel conceptual model for supply chain performance measurement in an agri‐food supply chain.Design/methodology/approachA conceptual model for integrated supply chain performance measurement is evaluated in a Dutch‐German tomato supply chain by means of a case study approach.FindingsThe proposed conceptual framework is found to be useful for measuring performance of the tomato supply chain. From the case study it is concluded that four main categories of performance measures (i.e. efficiency, flexibility, responsiveness, and food quality) are identified as key performance components of the tomato supply chain performance measurement system.Originality/valueThis research evaluates a novel concept for measuring the performance of agri‐food supply chains. This concept is the first step in developing an integrated performance measurement system that contains financial as well as non‐financial indicators combined with the specific characteristics of agri‐food supply chains. Based on a case study in the tomato supply chain, this concept is found to have potential.

As of January 1st 2005, a system of reduced checks for phytosanitary inspections of certain plants and plant products imported into the European Union (EU) is in place. Under this system, plants and plant products satisfying special criteria may be inspected with a reduced frequency. These criteria are based on EU-wide data on historical volumes of import and interceptions of harmful organisms in particular products. The objective of this paper is two-fold. Firstly, the paper analyses whether proportions of interceptions of harmful organisms associated with cut flowers imported into the Netherlands ? the largest EU importer of cut flowers ? support the application of reduced checks for certain genera and trades (commodity-exporting country combinations) of cut flowers. Secondly, the paper analyses how effective the reduced checks system is in minimizing the expected costs of introduction of harmful organisms in the EU. For that, a theoretically optimal system for allocating inspection effort to commodities is described. Using an illustrative example and stochastic simulations, the expected costs of introduction of harmful organisms under the theoretically optimal system and the current system of reduced checks are compared. Examination of interceptions of harmful organisms supports application of reduced checks for most genera and trades of cut flowers in the Netherlands. The results of stochastic simulations show that reduced checks may not minimize the expected costs of introduction of harmful organisms into the EU. Accounting for possible economic impacts of harmful organisms in determining the frequencies of reduced checks may help optimize the current system

In the Netherlands the greenhouse sector is a major user of energy. It accounts for 7% of the total national energy use and for 79% of the total energy use in agriculture. In order to sustain this sector on the long term, it is important that its use of energy is lowered. One way of reducing energy use by horticultural producers is investing in energy-saving systems. The purpose of this paper is to provide a better understanding of the investment behavior of firm operators in the adoption of energy-saving systems. Research objectives of the paper are (1) to analyze factors underlying the decision to invest, (2) to explore factors underlying the optimal size of investments. Three investment theories were used to construct an empirical model of investment. Consequently, this model was estimated in a two-stage procedure to analyze the factors influencing the decision of farmers to invest and the level of investments. The paper ends with policy implications.

In recent years, supply chain performance measures have been in the spotlight of many authors. Many performance measures have been used. In this paper, efficiency was measured as an indicator of performance in the vegetable supply chain. The study consisted of two stages. In the first, data envelopment analysis (DEA) evaluated technical and scale efficiency of the Dutch vegetable sector relative to the type of final distribution (mixed marketing channels versus traditional auctions). In the second stage, a truncated regression model (TRM) was applied to explain grower efficiency from a managerial point of view. The results of the first stage showed that growers who sell their products through auctions are less efficient. The second stage revealed that variables such as firm size, age, ownership structure, and distribution channel strategy significantly contribute to the explanation of technical efficiency of the growers, while the variables firm location, firm size, and firm age affect their scale.

This article calculates nonparametric measures of total factor productivity growth on Dutch horticultural firms in the period 1976¿1995. Individual components of total factor productivity growth, i.e., efficiency change and technical change are regressed on socioeconomic factors reflecting the effects of the world oil crises, household and demographic characteristics, location, and investment in physical capital. Also, the article investigates the presence of inter-sector spill-overs between groups of firms with different specializations in Dutch horticulture

In corporate finance, the impact of capital structure on firm performance has been widely studied. This article extends the capital structure study to the situation in agriculture, explicitly addressing the difference between family farms and corporate firms. We use the Malmquist productivity growth index as a proxy for performance to study the impact of capital structure (debt) on farm performance. We compare the results with those from the traditional performance model that uses profitability (e.g., return on equity (ROE)) as performance measure. Using data from Dutch arable farms, results show that debt has no effect on ROE, whereas it has a positive effect on productivity growth. Copyright 2006, Oxford University Press.

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.

This paper uses data envelopment analysis (DEA) to investigate the possibilities for improving the technical, economic and environmental performance of Dutch pig farms relative to currently applied technologies and relative to currently available but not yet applied technologies. First, the efficiency is computed relating observed pig farms to the current best practice frontier. This frontier is computed from a sample of observed pig farms, using DEA based on linear programming. Second, potential technological change is computed as the change of the frontier due to addition of virtual farms (based on technologies that are available but not applied in practice yet) to the dataset. It is found that the mean technical efficiency of farms is rather high relative to the currently available technologies. Overall technical performance increases slightly when new technologies are introduced. Environmental performance increases importantly when applying new technologies. In particular, the ammonia emissions can be reduced largely by utilising the up-to-date housing techniques.

Many previous empirical studies on the productivity of pesticides suggest that pesticides are under-utilized in agriculture despite the general held believe that these inputs are substantially over-utilized. This paper uses data envelopment analysis (DEA) to calculate non-parametric measures of the value of the marginal product of pesticides. Furthermore, the effect of pesticides on the value of the marginal product of productive inputs is investigated in order to analyze technical interdependence between pesticides and productive inputs. Results suggest, in general, substantial under-utilization of pesticides, which is consistent with earlier findings of parametric specifications.

This paper analyses the factors underlying the probability that Dutch pig farmers have plans to (a) stop, (b) to increase farm size and/or (re)build a barn, (c) to improve the quality of the production process and (d) to make manure processing facility at the own farm. A computer-based questionnaire was carried out among pig farmers in 1999 and 2000. Farmer plans were analysed using a multivariate probit model. The results show that farm size and life cycle are important variables explaining the probability of farmers having plans. Furthermore, risk averse farmers more frequently have plans to improve the quality of the production process, whereas farmers with a negative attitude towards biological farming search for opportunities to make a manure processing facility at their own farm. Results also reveal that most plans are significantly correlated and that the explanatory power of the model is relatively low, with the latter finding suggesting that more study is required to obtain a good understanding of strategic planning. (C) 2003 Elsevier Ltd. All rights reserved.

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.

This paper develops a short-run microeconomic simulation model of the Dutch glasshouse industry in order to investigate the relation between technical efficiency and marginal abatement costs of CO2 emission. The model is also used to determine the effects of an emission tax and systems of tradable and non-tradable quota for groups of firms with different rates of technical efficiency. The results show that marginal abatement costs are very responsive to changes in technical efficiency. Furthermore, it is found that firms with a low technical efficiency are faced with a higher profit reduction under different abatement policies than firms with a high technical efficiency. (C) 2002 Elsevier Science B.V. All rights reserved.

This paper analyses factors determining the choice between standard and organic farming technology in Finland by numerically iterating a Bellman equation backwards in time. The unknown parameters of a switching-type Probit model are estimated by maximum likelihood estimation. The maximised values of the uncertain revenue streams are stimulated. The results suggest that decreasing output prices and increasing direct subsidies trigger the switch to organic farming. The switch is also more likely on farms having large land areas and low yields. Intensive livestock production and labour-intensive production decrease the probability of switching to organic farming.

This paper uses the Generalized Box - Cox framework and Double Length artificial Regression to test whether different specifications of the profit function are able to mimic the technology underlying panel data of Dutch arable farms for the period 1970 - 1988. To this end, a linear GBC is developed that includes the Generalized Leontief, Normalized Quadratic and Symmetric Normalized Quadratic as special cases. A Lagrange multiplier test that avoids estimation of the linear GBC is used to test (subsets of) functional forms against (simplifications of) the linear GBC. Functional form results are also evaluated in terms of regularity conditions, parameter significance and reasonability of elasticities. On this data set, the NQ outperforms the other forms on most criteria.

One of the key concerns of biogas plants is the disposal of comparatively large amounts of digestates in an economically and environmentally sustainable manner. This paper analyses the economic performance of anaerobic digestion of a given biogas plant based on net present value (NPV) and internal rate of return (IRR) concepts. A scenario analysis is carried out based on a linear programming model to identify feedstocks that optimize electricity production and to determine the optimal application of digestate. In addition to a default scenario, management and policy scenarios were investigated. Economic evaluations of all scenarios, except no subsidy scenario, show positive NPV. The highest NPV and IRR values are observed under reverse osmosis (RO) as a green fertilizer scenario. Our findings show that treating RO as a green fertilizer, as opposed to manure (default scenario), is not only lucrative for the plant but also lessens environmental burden of long distance transportation of concentrates. This paper also concludes that given the uncertainty of regulations concerning RO and the currently low values of digestate and heat, high investment and operating costs limit feasibility of anaerobic digestion of wastes of farm origin and other co-substrates unless subsidies are provided.

Technical change at the farm level or changes in input prices often have an impact on the firm's supply function, which in turn affect their economic and environmental performance. These changes can take place in numerous ways. This paper presents a methodology that increases the consistency of supply responses across various sets of agricultural products and most representative farm typologies in Europe, with a market model based on a statistical response function approach. Since most farm simulation models are limited to a subset of regions and farm types, the linkage to an aggregated model requires a procedure for expanding these results to non-sample regions to achieve full regional coverage. This paper addresses theoretical aspects related to the consistency between micro and market level models. The proposed approach is applied using a consistent set of simulation results from farm models in seven European regions. Our results show a fairly stable behaviour of the farm models considered for the analysis and quite good fit of the estimated response surface. As results are still preliminary we critically reflect on the applicability of this method in addressing further needs on up-scaling of other economic as well as environmental indicators.

The objective of this study was to assess qualitatively, through a participatory approach, the potential for increasing the value added in the Dutch dairy production chain. A workshop involving stakeholders and experts in the Dutch dairy sector developed three scenarios, envisioned according to the strategic interests of the dairy chain in the Netherlands. These scenarios address major trends including changing consumer preferences, increasing pressure for more cost-efficient production, and rising environmental concerns. The scenarios indicate different directions in which the dairy chain in the Netherlands might develop in the next 5 to 20 years. The first scenario envisions the prevalence of producing differentiated raw milk with enhanced health or improved manufacturing properties. The second scenario envisions a dairy chain that is reduced to producing fresher and more individually customized dairy products with improved shelf life. The third scenario envisions ecologically sustainable dairy farming with improved animal welfare. These scenarios show that when improving the dairy sector it is important to consider the entire chain, and hence concerted and co-ordinated actions by the various stakeholders are necessary. Further studies quantifying the consequences of different scenario settings are necessary.

Climate change will affect crop yields and consequently farmers’ income. The underlying relationships are not well understood, particularly the importance of crop management and related factors at the farm and regional level. We analyze the impacts of trends and variability in climatic conditions from 1990 to 2003 on trends and variability in yields of five crops and farmers’ income at farm type and regional level in Europe considering farm characteristics and other factors. While Mediterranean regions are often characterized as most vulnerable to climate change, our data suggest effective adaptation to variable and changing conditions in these regions largely attributable to the characteristic farm types in these regions. We conclude that for projections of climate change impacts on agriculture, farm characteristics influencing management and adaptation should be considered, as they largely influence the potential impacts.

Recently, selective breeding was proposed as a means of changing the fatty acid composition of milk to improve its nutritional quality. Before implementing such breeding objectives, effects on other economically important traits should be investigated. The objectives of this study were to examine 1) the effect of milk fat composition, and 2) the effect of polymorphisms of DGAT1 and SCD1 genes on female fertility in commercial Dutch Holstein-Friesian cattle. Data on 1,745 first-lactation cows were analyzed by fitting linear mixed models. We found that higher concentrations of trans fatty acids within total milk fat negatively affected reproductive performance. Furthermore, results suggested a potential effect of the DGAT1 polymorphism on nonreturn rates for insemination 28 and 56 d after the first service. Our results can be used to assess the correlated effects of breeding for improved milk fat composition on reproduction, thereby allowing for better evaluation of breeding programs before implementation.

In order to assess agricultural adaptation to climate impacts, new methodologies are needed. The translog distance function allows assessing interactions between different factors, and hence the influence of management on climate impacts. The Farm Accountancy Data Network provides extensive data on farm characteristics of farms throughout the EU15 (i.e. the 15 member states of the European Union before the extension in 2004). These data on farm inputs and outputs from 1990¿2003 are coupled with climate data. As climate change is not the only change affecting European agriculture, we also include effects of subsidies and other changes on inputs and outputs of farms throughout Europe. We distinguish several regions and empirically assess (1) climate impacts on farm inputs and outputs in different regions and (2) interactions between inputs and other factors that contribute to the adaptation to these impacts. Changes in production can partly be related to climatic variability and change, but also subsidies and other developments (e.g. technology, markets) are important. Results show that impacts differ per region, and that `actual impacts¿ cannot be explicitly separated into `potential impacts¿ and `adaptive capacity¿ as often proposed for vulnerability assessment. Farmers adapt their practices to prevailing conditions and continuously adapt to changing conditions. Therefore, `potential impacts¿ will not be observed in practice, leaving it as a mainly theoretical concept. Factors that contribute to the adaptation also differ per region. In some regions more fertilizers or more irrigation can mitigate impacts, while in other regions this amplifies impacts. To project impacts of future climate change on agriculture, current farm management strategies and their influence on current production should be considered. This clearly asks for improved integration of biophysical and economic models.

PRATIQUE is an EC-funded 7th Framework research project designed to address the major challenges for pest risk analysis (PRA) in Europe. It has three principal objectives: (a) to assemble the datasets required to construct PRAs valid for the whole of the EU, (b) to conduct multi-disciplinary research that enhances the techniques used in PRA and (c) to provide a decision support scheme for PRA that is efficient and user-friendly. The research will be undertaken by scientists from 13 institutes in the EU and one each from Australia and New Zealand with subcontractors from institutes in China and Russia. They will produce a structured inventory of PRA datasets for the EU and undertake targeted research to improve existing procedures and develop new methods for (a) the assessment of economic, environmental and social impacts, (b) summarising risk while taking account of uncertainty, (c) mapping endangered areas (d) pathway risk analysis and systems approaches and (e) guiding actions during emergencies caused by outbreaks of harmful organisms. The results will be tested and provided as protocols, decision support systems and computer programs with examples of best practice linked to a computerised European and Mediterranean Plant Protection Organization (EPPO) PRA scheme.

Agri-food supply chains are currently being confronted with many requirements regarding the product quality of their products. In recent years, concerns about food quality have risen among consumers as a result of several outbreaks of diseases and various environmental concerns. This has stimulated governments to introduce stricter regulations concerning food quality and safety issues. Besides governmental regulations, retailers also impose food quality requirements and standards on their supply chains. The goal of this paper is therefore to develop a method for analysing the impact of different quality assurance systems (QAS) requirements on the performance of the different stages of the supply chain and of the chain as a whole. Performance in this study includes components of efficiency, flexibility and responsiveness as well as food quality. This study uses perceptions of the Dutch tomato supply chain members in an effort to understand the perceived impact of different QAS requirements on the performance of the tomato supply chain. These perceptions are obtained using an adapted self-explicated method. Results indicate that some QAS requirements are perceived to have a positive impact on some supply chain members' performance, while they are perceived to have a negative impact on other supply chain members' performance. Overall, results reveal that all selected QAS requirements are perceived to have a positive impact on the performance of the supply chain, as a whole, although the total impact is relatively small. The performance measurement model developed in this study allows supply chain members to develop a clear view of the impact of QAS requirements. Also, the model makes it possible to make trade-offs between issues such as production costs and food safety, within the own firm as well as throughout the chain

This paper uses a two-stage approach to analyse efficiency and productivity of Dutch glasshouse firms over the period 1991-1998. The first stages uses DEA to determine productivity growth and technical and scale efficiency; the second stage applies a TOBIT model to explain technical and scale efficiency; OLS is used to explain productivity change. The main explanatory variables are structural changes (innovation and firm growth), socio-economic variables and perceptions classified according to the SWOT-analysis. Variables that are stable over time, i.e. socio-economic variables of the firm and perceptions of the entrepreneur explain the level of technical and scale efficiency. Innovation and firm growth are important factors in the explanation of productivity growth

Micro-econometric models have become a standard and powerful tool in analysing agricultural policies. In this paper we assess the contributions that have been made in the agricultural economics literature to dynamic microeconometric models of firms and households that are estimated using microdata. After discussing developments in dynamic investment models, dynamic household models, dynamic discrete choice models and dynamic efficiency models we give promising directions for future research and discuss implications for future data collection.

We analyse the impacts of the CAP reforms on 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 on the mean and the variances of farm efficiency. We formulate policy variables (e.g. the direct subsidies) and farm characteristics as explanatory variables in the inefficiency effects model. We use the 1995-2004 FADN data to estimate the production frontier, to derive technical efficiency, and to determine the effects of the explanatory variables. The study shows that the 10-year average technical efficiency of olive farms is 69%. Direct transfers have a negative and monotonic effect on technical efficiency, while the degree of specialization has a non-monotonic effect on technical efficiency.

Technical change at the farm level or changes in input prices often entail that the firm's supply function changes. These changes can take place in numerous ways. This paper presents a methodology that increases the consistency in supply responses across various sets of agricultural products and farm types with a market model based on a statistical response function approach. Since most farm simulation models are limited to a subset of regions and farm types, the linkage to an aggregated model requires a procedure for expanding these results to non sample regions, so that full regional coverage is achieved. This paper addresses theoretical aspects related to the consistency between micro and market level models. Next it deals with some empirical findings related to the selection of different functional forms for extrapolation. We conclude with a critical reflection on applicability of this method in addressing further needs on up-scaling of other economic as well as non-economic indicators.

Met behulp van de DEA methode is in dit rapport voor ieder individueel bosbedrijf een efficiëntiescore berekend. Daarnaast kunnen ook de verschillende soorten efficiëntie beoordeeld worden, zodat een bedrijf inzicht krijgt in de oorzaken van de efficiëntie. Tot slot zijn de berekende scores gekoppeld aan een beperkt aantal kenmerken van de bedrijven (grootte, zelf vellen, stedelijkheid voor enkele bedrijven en regio).

Dutch glasshouse firms are facing the introduction of a system of tradable CO2 emission quotas. This paper employs a non-parametric method for modelling tradable CO2 emissions of Dutch glasshouse firms. The method is capable of generating shifts in CO2 emissions across the sample of firms. Moreover, changes in volumes of outputs produced and inputs used are computed. Results show that firms using a conventional heating technology will be net purchasers of CO2 emissions, whereas firms using more advanced heating technologies will sell part of their emission quota

Phytosanitary inspection of imported plants and flowers is a major means for preventing pest invasions through international trade, but in a majority of countries availability of resources prevents inspection of all imports. Prediction of the likelihood of pest infestation in imported shipments could help maximize the efficiency of inspection by targeting inspection on shipments with the highest likelihood of infestation. This paper applies a multinomial logistic (MNL) regression model to data on import inspections of ornamental plant commodities in the Netherlands from 1998 to 2001 to investigate whether it is possible to predict the probability that a shipment will be (i) accepted for import, (ii) rejected for import because of detected pests, or (iii) rejected due to other reasons. Four models were estimated: (i) an all-species model, including all plant imports (136,251 shipments) in the data set, (ii) a four-species model, including records on the four ornamental commodities that accounted for 28.9% of inspected and 49.5% of rejected shipments, and two models for single commodities with large import volumes and percentages of rejections, (iii) Dianthus (16.9% of inspected and 46.3% of rejected shipments), and (iv) Chrysanthemum (6.9 and 8.6%, respectively). All models were highly significant (P < 0.001). The models for Dianthus and Chrysanthemum and for the set of four ornamental commodities showed a better fit to data than the model for all ornamental commodities. Variables that characterized the imported shipment's region of origin, the shipment's size, the company that imported the shipment, and season and year of import, were significant in most of the estimated models. The combined results of this study suggest that the MNL model can be a useful tool for modeling the probability of rejecting imported commodities even with a small set of explanatory variables. The MNL model can be helpful in better targeting of resources for import inspection. The inspecting agencies could enable development of these models by appropriately recording inspection results.

This paper investigates the impact of CAP subsidies on the competitiveness of dairy farms in Germany, the Netherlands, and Sweden. Technical efficiency results show that coupled subsidies have negative impacts in Germany and the Netherlands, but no significant impacts in Sweden. Decoupled subsidies negatively affect technical efficiency in each country and to a larger extent than coupled subsidies. Relative productivity results indicate that Dutch technology leads to the highest output, followed by technologies in Germany and Sweden. Dutch farms can improve their competitiveness by exploring their current production potential. Besides improving efficiency, German and Swedish farms may have options to improve their production technology

Growth and liberalization of world trade have increased the risks of introduction of quarantine plant pests into importing countries. Import inspection of incoming commodities is a major tool for prevention of pest introductions related to world trade, but inspection capacities are limited. This article develops a theoretical and an empirical model for the optimal allocation of inspection effort for phytosanitary inspection of imported commodities when the inspecting agency has a limited capacity. It is shown that the optimal allocation of inspection effort equalizes marginal costs of pest introduction across risky commodity pathways. The numerical illustration finds the optimal allocation of inspection effort of chrysanthemum cuttings imported in the Netherlands. The numerical results suggest that ceteris paribus, greater inspection effort should be allocated to pathways whose inspection yields a greater reduction in the expected costs of pest introduction. The numerical results also suggest that import inspection has a high marginal benefit. In particular, we found that each additional euro of the inspection capacity decreases the expected costs of pest introduction from 18 to 49 euros, depending on the initial inspection capacity.

Quarantine diseases comprise a distinct class of plant diseases. In contrast to other plant diseases, direct losses through crop damage are often limited. Yet, quarantine diseases may have serious economic consequences for a country as they threaten the country¿s export of affected crops. In particular for this category of diseases, it is important to design a control strategy that is optimal from an epidemiological as well as an economic point of view. This chapter presents the development of a bioeconomic model to evaluate control strategies in terms of their cost-effectiveness, specified for brown rot in the Dutch potato production chain. The conceptual model consists of two modules: an epidemiological module, which is a stochastic, spatially explicit simulation model that simulates the spread of potato brown rot over all potato-growing farms and fields in the Netherlands, and an economic module, which calculates the total costs of brownrot prevalence, based on the results of the epidemiological model. The model is applied for two brown-rot policy scenarios, which differ in sampling frequency of harvested potato lots but are otherwise similar. The two scenarios are compared with respect to their effectiveness and efficiency. Concerning the costs of controlling brown rot, a low monitoring level appears to be more cost-efficient; however, when including expected export consequences, a high monitoring level may be preferable. The model presented here strongly facilitates the development of an optimal control strategy as it provides insight into the effectiveness of brown-rot control strategies in relation to their costs. Moreover, the introduced modelling concept can be a useful tool in analysing the epidemiological and economic effects of other (quarantine) diseases.