Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2004
Authors
Klaus Mittenzwei Maria Loureiro Wenche Dramstad Wendy Fjellstad Ola Flaten Arnt Kristian Gjertsen Sjur Spildo PrestegardAbstract
The level of support to Norwegian agriculture is partly justified with reference to agriculture’s multifunctionality. The concept of multifunctionality involves the provision of so-called “public goods» by agriculture, in addition to the production of food and fibre. Examples of these public goods include cultural landscape, biodiversity, ecological functions, cultural heritage, the viability of rural areas, and food security. The overall aim of the research project “Operationalization of multifunctionality using the CAPRI modeling system» is to study the effects of policy instruments on agriculture’s multifunctionality by defining quantitative indicators for selected elements of agriculture’s multifunctionality that can be implemented in the agricultural sector model CAPRI. This working paper takes a first step towards the appropriate regionalization when multifunctionality is concerned. The current regionalization of the CAPRI model is at the county level. This approach fails when multifunctionality is concerned, because many issues of multifunctionaliy (e.g., cultural landscape aspects) are independent of administrative borders at that level. As the aim of the overall project is to study the effects of policy instruments on agriculture’s multifunctionality, it is important to design regions within the CAPRI model that to a greater extent exhibit similar characteristics with respect to aspects of agriculture’s multifunctionality. Accordingly, it is reasonable to assume that policy changes will have quite similar effects on the multifunctionality indicators within each of these CAPRI regions. This task has been addressed by performing a cluster analysis by which Norwegian municipalities have been grouped with respect to their performance on variables that are expected to describe different aspects of the multifunctionality of agriculture. This information will then later on be used to regionalize the CAPRI model accordingly. […]
2003
Abstract
No abstract has been registered
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Authors
Grete StokstadAbstract
Several factors influence the value of a lamb carcass throughout the slaughtering season, and therefore have implications for the optimal slaughtering time of lambs. The expected price of the carcass varies through the season due to: Variations in the weight of the lambs, and the growth through the season. The classification of the carcass, i.e., the price per kg changes as the lambs grow. The prices of the various quality changes throughout the season. The quality of the grazing fields limits the possible weight gain and influences the classification of lams. The grazing resources are in general limited, and will affect the possibility of fattening lambs in the fall. The objective with this study is to come up with a tool to help in determining when to slaughter which lambs in the fall when resources are limited. In order to make good decisions, the first step is to calculate the profitability of various slaughtering decisions. I use known characteristics of the lambs as weight, sex etc. to determine expected value of the carcass if slaughtered at various point in time in the future. In order to determine expected quality for the carcasses I have used a multinomial ordered probit regression model to determine the probability for obtaining a particular classification. A linear programming model is used to choose the best alternatives given limited grassing resources. The model can be used to determine optimal slaughtering decisions given a particular group of lambs and resources. By limiting the possible choices in the model, the model user may also investigate the losses associated with alternative slaughtering schemes. In this paper I describe the forecasting models for determining the value of the carcass, I describe the general linear programming model and show some results from running the model.
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This report contains all papers presented at the OECD Expert meeting in Oslo October 7th - 9th 2002, in addition to the list of participants. The topic of the meeting was the development of landscape indicators. In brief, the Expert Meeting agreed that interested OECD Member countries should consider the following recommendations; • Invest in the scientific understanding and further development of an indicator framework for agricultural landscapes, representing the linkages between landscape structure, function and management, • Build upon the existing national and international experiences in policy monitoring, evaluation and predictive scenarios, • Encourage pro-active collaboration, information exchange and methodological integration, • Contribute to, and cooperate with, other international initiatives related to developing agricultural landscape indicators, • Establish an informal expert network to follow up recommendations of the meeting.
Abstract
At present there are nearly 20 000 milk producers in Norway, and approximately 10 per cent of them are members of the Norwegian Dairy Financial Recording (NDFR). The NDFR is an important basis for production and financial advice given by the dairies. There is a great interest among milk producers and advisors in comparing results from different farms to find out why some are doing well and some are doing not so well, and to learn from those doing well. Gross margin (GM) per litre of milk produced is the traditional indicator for efficiency. This data, as other data on milk production, indicate that there is a wide variation in gross margin per litre of milk between farms with seemingly similar conditions for producing milk. This is interpreted as a potential for improving the efficiency of many producers. However, for many reasons gross margin per litre of milk is not an ideal indicator. A new version of the NDFR contains more information, for instance information on fixed costs of roughages produced on the farm. It is hoped that the new version of the NDFR makes it a better tool for improving the profitability of milk production. In an ongoing project we try to use the NDFR to analyse who are doing well and why. We use a combination of Data Envelopment Analysis (DEA) and statistical analysis. For each farm we produce an efficiency index, and then we apply statistical methods to find factors that can explain the index. So far we have only very preliminary results. Management factors are important, but the NDFR data-base have very little information on management factors. It is planned to collect such data for a sample of farmers and include that in the study at a later stage.
2002
Authors
Wenche Dramstad Wendy Fjellstad Geir-Harald Strand Henrik Forsberg Mathiesen Gunnar Engan Jogeir N. StoklandAbstract
No abstract has been registered
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2001
Abstract
No abstract has been registered