Using Aggregated Farm Location Information to Predict Regional Structural Change of Farm Specialisation, Size and Exit/Entry in Norway Agriculture

In this paper, we extend the analysis of farm structural change with respect to farm specialisation, size and exit in Norway by, first, explicitly incorporating the location information of farms generating a number of neighbouring farms within a certain range and, second, by predicting farm numbers...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Sebastian Neuenfeldt [verfasserIn] Alexander Gocht [verfasserIn] Thomas Heckelei [verfasserIn] Klaus Mittenzwei [verfasserIn] Pavel Ciaian [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	farm structural change MCI model farm location production specialisation farm entry and exit

Übergeordnetes Werk:	In: Agriculture - MDPI AG, 2012, 11(2021), 7, p 643
Übergeordnetes Werk:	volume:11 ; year:2021 ; number:7, p 643

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/agriculture11070643

Katalog-ID:	DOAJ015152839

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allfieldsSound	10.3390/agriculture11070643 doi (DE-627)DOAJ015152839 (DE-599)DOAJ8048962e6be144948f7bb4ddb5edee85 DE-627 ger DE-627 rakwb eng S1-972 Sebastian Neuenfeldt verfasserin aut Using Aggregated Farm Location Information to Predict Regional Structural Change of Farm Specialisation, Size and Exit/Entry in Norway Agriculture 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, we extend the analysis of farm structural change with respect to farm specialisation, size and exit in Norway by, first, explicitly incorporating the location information of farms generating a number of neighbouring farms within a certain range and, second, by predicting farm numbers in addition to farm group shares, which allows for consideration of the exit farm group. We use Norwegian single-farm full census data for the period 1996–2015. Four production specialisations and seven size classes represent farm groups, as well as a residual and an exit farm group at the regional level. The estimates indicate the explanatory power and importance of aggregated farm location information in the model. Simulation analysis showed that the farm groups develop differently, given a change in the number of neighbouring farms with respect to the farm numbers and farm group shares. farm structural change MCI model farm location production specialisation farm entry and exit Agriculture (General) Alexander Gocht verfasserin aut Thomas Heckelei verfasserin aut Klaus Mittenzwei verfasserin aut Pavel Ciaian verfasserin aut In Agriculture MDPI AG, 2012 11(2021), 7, p 643 (DE-627)686948173 (DE-600)2651678-0 20770472 nnns volume:11 year:2021 number:7, p 643 https://doi.org/10.3390/agriculture11070643 kostenfrei https://doaj.org/article/8048962e6be144948f7bb4ddb5edee85 kostenfrei https://www.mdpi.com/2077-0472/11/7/643 kostenfrei https://doaj.org/toc/2077-0472 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 11 2021 7, p 643
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source	In Agriculture 11(2021), 7, p 643 volume:11 year:2021 number:7, p 643
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callnumber-first	S - Agriculture
author	Sebastian Neuenfeldt
spellingShingle	Sebastian Neuenfeldt misc S1-972 misc farm structural change misc MCI model misc farm location misc production specialisation misc farm entry and exit misc Agriculture (General) Using Aggregated Farm Location Information to Predict Regional Structural Change of Farm Specialisation, Size and Exit/Entry in Norway Agriculture
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topic_title	S1-972 Using Aggregated Farm Location Information to Predict Regional Structural Change of Farm Specialisation, Size and Exit/Entry in Norway Agriculture farm structural change MCI model farm location production specialisation farm entry and exit
topic	misc S1-972 misc farm structural change misc MCI model misc farm location misc production specialisation misc farm entry and exit misc Agriculture (General)
topic_unstemmed	misc S1-972 misc farm structural change misc MCI model misc farm location misc production specialisation misc farm entry and exit misc Agriculture (General)
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title	Using Aggregated Farm Location Information to Predict Regional Structural Change of Farm Specialisation, Size and Exit/Entry in Norway Agriculture
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title_sort	using aggregated farm location information to predict regional structural change of farm specialisation, size and exit/entry in norway agriculture
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title_auth	Using Aggregated Farm Location Information to Predict Regional Structural Change of Farm Specialisation, Size and Exit/Entry in Norway Agriculture
abstract	In this paper, we extend the analysis of farm structural change with respect to farm specialisation, size and exit in Norway by, first, explicitly incorporating the location information of farms generating a number of neighbouring farms within a certain range and, second, by predicting farm numbers in addition to farm group shares, which allows for consideration of the exit farm group. We use Norwegian single-farm full census data for the period 1996–2015. Four production specialisations and seven size classes represent farm groups, as well as a residual and an exit farm group at the regional level. The estimates indicate the explanatory power and importance of aggregated farm location information in the model. Simulation analysis showed that the farm groups develop differently, given a change in the number of neighbouring farms with respect to the farm numbers and farm group shares.
abstractGer	In this paper, we extend the analysis of farm structural change with respect to farm specialisation, size and exit in Norway by, first, explicitly incorporating the location information of farms generating a number of neighbouring farms within a certain range and, second, by predicting farm numbers in addition to farm group shares, which allows for consideration of the exit farm group. We use Norwegian single-farm full census data for the period 1996–2015. Four production specialisations and seven size classes represent farm groups, as well as a residual and an exit farm group at the regional level. The estimates indicate the explanatory power and importance of aggregated farm location information in the model. Simulation analysis showed that the farm groups develop differently, given a change in the number of neighbouring farms with respect to the farm numbers and farm group shares.
abstract_unstemmed	In this paper, we extend the analysis of farm structural change with respect to farm specialisation, size and exit in Norway by, first, explicitly incorporating the location information of farms generating a number of neighbouring farms within a certain range and, second, by predicting farm numbers in addition to farm group shares, which allows for consideration of the exit farm group. We use Norwegian single-farm full census data for the period 1996–2015. Four production specialisations and seven size classes represent farm groups, as well as a residual and an exit farm group at the regional level. The estimates indicate the explanatory power and importance of aggregated farm location information in the model. Simulation analysis showed that the farm groups develop differently, given a change in the number of neighbouring farms with respect to the farm numbers and farm group shares.
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title_short	Using Aggregated Farm Location Information to Predict Regional Structural Change of Farm Specialisation, Size and Exit/Entry in Norway Agriculture
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Using Aggregated Farm Location Information to Predict Regional Structural Change of Farm Specialisation, Size and Exit/Entry in Norway Agriculture

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