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On the dynamics of agricultural labour input and their impact on productivity and income: an empirical study of Swiss family farms

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  • Hoop, Daniel
  • Mack, Gabriele
  • Mann, Stefan
  • Schmid, Dierk

Abstract

The labour employment trends of 2003 Swiss FADN farms between 2004 and 2009 are studied, differentiating between the use of on- and off-farm family labour, employees, and contracting services accomplished by and for third parties. By means of a correlation and data envelopment analysis, the relationships between changes in labour input, farm size, productivity and income are empirically explored. With the aid of a cluster analysis 7 major strategies to adjust labour input are revealed whereas slightly over half of the farms in the period under consideration leave labour input at a constant level. Although some of the clusters differ substantially in terms of growth in both labour productivity and income, differences in total factor productivity are not significant.

Suggested Citation

  • Hoop, Daniel & Mack, Gabriele & Mann, Stefan & Schmid, Dierk, 2014. "On the dynamics of agricultural labour input and their impact on productivity and income: an empirical study of Swiss family farms," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 3(4), pages 1-11.
    • Handle: RePEc:ags:ijameu:236915
    DOI: 10.22004/ag.econ.236915
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    1. Dierk Schmid & Swetlana Renner & Daniel Hoop, 2023. "Exploring within- and between-effects of the factors influencing off-farm work decisions in Switzerland," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(10), pages 416-425.
    2. Benedikt Kramer & Anke Schorr & Reiner Doluschitz & Markus Lips, 2019. "Short and medium-term impact of dairy barn investment on profitability and herd size in Switzerland," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 65(6), pages 270-277.
    3. Kaliba, Aloyce R. & Mushi, Richard J. & Gongwe, Anne G. & Mazvimavi, Kizito, 2020. "A typology of adopters and nonadopters of improved sorghum seeds in Tanzania: A deep learning neural network approach," World Development, Elsevier, vol. 127(C).

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