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Publikasjoner

NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.

2021

Sammendrag

Previous application of the stochastic frontier model and subsequent measurement of the performance of the crop sector can be criticized for the estimated production function relying on the assumption that the underlying technology is the same for different agricultural systems. This paper contributes to estimating regional efficiency and the technological gap in Norwegian grain farms using the stochastic metafrontier approach. For this study, we classified the country into regions with district level of development and, hence, production technologies. The dataset used is farm-level balanced panel data for 19 years (1996–2014) with 1463 observations from 196 family farms specialized in grain production. The study used the true random effect model and stochastic metafrontier analysis to estimate region-level technical efficiency (TE) and technology gap ratio (TGR) in the two main grain-producing regions of Norway. The result of the analysis shows that farmers differ in performance and technology use. Consequently, the paper gives some regionally and farming system-based policy insights to increase grain production in the country to achieve self-sufficiency and small-scale farming in all regions.

Sammendrag

Purpose The study measures the technology gap and performance of the Norwegian dairy farms accounting for farm heterogeneity. Design/methodology/approach The analysis was based on a meta-frontier and unbalanced farm-level panel data for 1991–2014 from 417 Norwegian farms specialized in dairy production in five regions of Norway. Findings The result of the analysis provides empirical evidence of regional differences in technical efficiencies, technological gap ratios (TGRs) and input use. Consequently, the paper provides some insights into policies to increase the efficiency of dairy production in the country across all regions. Research limitations/implications The author used a meta-frontier approach for modeling regional differences based on a single-output production function specification. This approach has commonly been used in the economics literature since Battese et al. (2004). To get more informative and useful results, it would be necessary to repeat the analysis within terms of multiple input-output frameworks using, for instance, the input distance function approach. Moreover, the author estimated the meta-frontier using the non-parametric approach, thus it is also a need for further analysis if the values are different by estimating using a parametric approach. Practical implications One implication for farmers (and their advisers) is that dairy farms in all regions used available technology in the area sub-optimally. Thus, those lagging the best-performing farms need to look at the way the best-performing farmers are operating. Policymakers might reduce the gap is through training, including sharing information about relevant technologies from one area to another, provided that the technologies being shared fit the working environment of the lagging area. Moreover, some of the dairy technologies they use may not fit other regions, suggesting that agricultural policies that aim to encourage efficient dairy production, such as innovation of improved technology (like breeding, bull selection and improved feed varieties) through research and development, need to account the environmental differences between regions. Social implications For both taxpayers and consumers, one implication is that the contributions they pay that go to subsidize dairy farmers appear to bring some benefits in terms of more efficient milk production that, in turn, increases the supply of some foods so possibly making food prices more affordable. Originality/value The paper contributes to the literature in several ways. In contrast to Battese et al. (2004), the author accounts for farm-level performance differences by applying the model devised by Greene (2005), thus may serve as a model for future studies at more local levels or of other industries. Moreover, the author is fortunate to able to use a large level farm-level panel data from 1991 to 2014.

Sammendrag

Growing environmental concerns have prompted governments to make sustainable choices in agricultural resource use. Evaluating the sustainability of agricultural systems is a key issue for the implementation of policies and practices aimed at revealing sustainability. This study aimed to evaluate the performance of Norwegian dairy farms, accounting for marginal effects of environmental (exogenous) variables. We adopted the dynamic parametric approach within the input distance function framework to estimate the performance of Norwegian dairy farms, focusing on the technical efficiency and determinates. For comparison, we also estimated the static parametric model, which was used by previous studies. We used unbalanced farm-level panel data for the period 2000–2018. The result shows a mean technical efficiency score of 0.92 for the dynamic model and 0.87 for the static models. The empirical result shows that the previous studies that focused on the static model reported a biased result on the performance of dairy farms. The dynamic efficiency score suggests that Norwegian dairy farms can reduce the input requirement of producing the average output by 8% if the operation becomes technically efficient. The environmental variables have a different effect on the performance of the farmers; thus, policymakers need to place special focus on these variables for the sustainable development of the dairy sector.

Sammendrag

NIBIO, avdeling for kulturlandskap og biologisk mangfold, ved Synnøve Nordal Grenne, har utført et oppdrag som besto i å kartlegge status for utbredelsen av sitkagran på Storfosna i Ørland kommune. Hensikten med dette prosjektet var å gi en oversikt over arealer med den fremmede arten sitkagran (Picea sitchensis) begrenset til øya Storfosna i Ørland kommune. Forarbeidet besto i at kartleggingsområdet ble flybildetolket, områder med potensiell sitkagran ble digitalisert og avgrenset vha. kartverktøy (GIS) før feltarbeidet. Tilgjengelige flyfoto (Norge i Bilder) og arealressurskart (AR5) ble benyttet som datagrunnlag for flybildetolking. Feltarbeidet har verifisert om de forhåndsdigitaliserte områdene er sitkagran. Ved sitkagranobservasjoner ble det satt av punkter i en artsapp som er utviklet av Miljødirektoratet. Resultatet av prosjektet er levert i denne rapporten, i tillegg til shapefiler og bildefiler fra kartleggingen. Punktene satt av i artsapp er levert i en egen shapefil.