2015
DOI: 10.1787/5jrw8ffbzf7l-en
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Dynamics of dairy farm productivity growth

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Cited by 9 publications
(12 citation statements)
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References 26 publications
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“…1 Consequently, country cases considered in the analysis depend on OECD members' voluntary participation in the project in the form of data access and advice. This project links to previous OECD work on productivity growth and dynamics, structural change and farms' clustering as well as innovation behaviour and performance links (Kimura and Sauer, 2015;Bokusheva and Čechura, 2017;Sauer, 2017). It significantly adds to this work by explicitly considering multiple dimensions of farms' performance and characteristics in a statistically robust way.…”
Section: Context and Scopementioning
confidence: 88%
“…1 Consequently, country cases considered in the analysis depend on OECD members' voluntary participation in the project in the form of data access and advice. This project links to previous OECD work on productivity growth and dynamics, structural change and farms' clustering as well as innovation behaviour and performance links (Kimura and Sauer, 2015;Bokusheva and Čechura, 2017;Sauer, 2017). It significantly adds to this work by explicitly considering multiple dimensions of farms' performance and characteristics in a statistically robust way.…”
Section: Context and Scopementioning
confidence: 88%
“…They find that policy factors strongly influence the dynamics of productivity growth, but differently in different countries. Broadly speaking, productivity growth occurs either due to technology adoption (in productivity frontier terms, an expansion of the frontier) or due to adjustments such as farm exit and consolidation which allow reallocation of resources towards more efficient farms (Kimura and Le Thi, 2013 [56]). When MPS occurs in the form of production quotas, binding quotas "tend to slow down structural change of the sector and maintain inefficiencies.…”
Section:  21mentioning
confidence: 99%
“…the category "environmental subsidies". Moreover, notwithstanding the recent FLINT initiative 56 to extend the coverage of FADN on environmental variables, this database does not include 54 OECD (2016, p. 189 [41]) states: "the [PSE] indicator database in its current version does not lend itself to modelling agri-environmental policies. These policies are characterized by an "input constraint" label, indicating whether the input constraint is voluntary, and whether it has an environmental objective.…”
Section: Improving the Evidence Basementioning
confidence: 99%
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“…The total factor productivity growth, before the phasing out of the milk quota, was almost entirely driven by a decline in input use. However, currently the main driving force of TFP growth in the Dutch dairy farm sector became the expansion of milk output (Kimura and Sauer, 2015).…”
Section: │ Synergies and Trade-offs Between Adaptation Mitigation Anmentioning
confidence: 99%