Drivers of farm performance in Czech crop farms

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027251%3A_____%2F20%3AN0000006" target="_blank" >RIV/00027251:_____/20:N0000006 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.agriculturejournals.cz/web/agricecon.htm?type=article&id=231_2019-AGRICECON" target="_blank" >https://www.agriculturejournals.cz/web/agricecon.htm?type=article&id=231_2019-AGRICECON</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.17221/231/2019-AGRICECON" target="_blank" >10.17221/231/2019-AGRICECON</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Drivers of farm performance in Czech crop farms

Popis výsledku v původním jazyce

When analysing drivers affecting the farm performance, the presence of different technologies should be taken into account. We assume that the technology used by crop farms is not the same for all producers and therefore we use latent class model to identify technological classes at first. Class definition is based on multidimensional classification and determination of indices given by the values of individual components. The principal components analysis is applied to estimate significant and robust weights for the index components. FADN (Farm Accountancy Data Network) database, Czech crop farms data from 2005 to 2017 were used and three groups of technology classes of farms were identified with a determinant influence of the structure index and localisation. The other indices characterise sustainability, innovation, technology, diversification, and individual characteristics. Three distinct classes of crop farms were found, one major class and two minor classes. Family driven farms are usually smaller farms in terms of acreage. Highly sustainable crop farms are most likely located in lower altitudes and not in less-favoured areas. Innovative farms are also likely to be more productive. The results indicate that agricultural production farms with a more sustainable way of farming are most likely to be more productive.

Název v anglickém jazyce

Drivers of farm performance in Czech crop farms

Popis výsledku anglicky

When analysing drivers affecting the farm performance, the presence of different technologies should be taken into account. We assume that the technology used by crop farms is not the same for all producers and therefore we use latent class model to identify technological classes at first. Class definition is based on multidimensional classification and determination of indices given by the values of individual components. The principal components analysis is applied to estimate significant and robust weights for the index components. FADN (Farm Accountancy Data Network) database, Czech crop farms data from 2005 to 2017 were used and three groups of technology classes of farms were identified with a determinant influence of the structure index and localisation. The other indices characterise sustainability, innovation, technology, diversification, and individual characteristics. Three distinct classes of crop farms were found, one major class and two minor classes. Family driven farms are usually smaller farms in terms of acreage. Highly sustainable crop farms are most likely located in lower altitudes and not in less-favoured areas. Innovative farms are also likely to be more productive. The results indicate that agricultural production farms with a more sustainable way of farming are most likely to be more productive.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

40101 - Agriculture

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Agricultural Economics

ISSN

0139-570X

e-ISSN

1805-9295

Svazek periodika

66

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

10

Strana od-do

297-306

Kód UT WoS článku

000551034000001

EID výsledku v databázi Scopus

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