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.

中文翻译：

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衡量挪威奶牛场之间的技术和绩效差异

目的

该研究衡量了挪威奶牛场在农场异质性方面的技术差距和绩效。

设计/方法/途径

该分析基于 1991-2014 年来自挪威五个地区的 417 个专门从事乳制品生产的挪威农场的元前沿和不平衡农场级面板数据。

发现

分析结果提供了技术效率、技术差距比率 (TGR) 和投入使用方面的区域差异的经验证据。因此，本文提供了一些关于提高全国所有地区乳制品生产效率的政策的见解。

研究局限性/影响

作者使用元边界方法基于单一产出生产函数规范对区域差异进行建模。自 Battese等人以来，这种方法已普遍用于经济学文献中。(2004)。为了获得更多信息和有用的结果，有必要在多个输入输出框架内重复分析，例如，使用输入距离函数方法。此外，作者使用非参数方法估计元边界，因此如果使用参数方法估计的值不同，也需要进一步分析。

实际影响

对农民（及其顾问）的一个影响是，所有地区的奶牛场都未充分利用该地区的可用技术。因此，那些落后于表现最好的农场的人需要了解表现最好的农民的经营方式。政策制定者可以通过培训缩小差距，包括从一个地区到另一个地区共享相关技术的信息，前提是所共享的技术适合落后地区的工作环境。此外，他们使用的一些乳制品技术可能不适合其他地区，这表明旨在鼓励高效乳制品生产的农业政策，例如通过研发创新改良技术（如育种、公牛选择和改良饲料品种），需要考虑到地区之间的环境差异。

社会影响

对于纳税人和消费者而言，一个含义是他们为补贴奶农而支付的捐款似乎在提高牛奶生产效率方面带来了一些好处，这反过来又增加了某些食品的供应，从而可能使食品价格更实惠.

原创性/价值

这篇论文以多种方式对文献做出了贡献。与 Battese等人相反。(2004)，作者通过应用 Greene (2005) 设计的模型来解释农场层面的绩效差异，因此可以作为未来在更多地方层面或其他行业进行研究的模型。此外，作者有幸能够使用1991年至2014年的大型农场级面板数据。