Systematic review and meta-regression analysis of technical efficiency in dairy farms

Systematic review and meta-regression analysis of technical efficiency in dairy farms Purpose – The purpose of this paper is to complement and extend previous literature reviews on Technical Efficiency (TE) in dairy farms, analysing the effects of different methodologies and study-specific characteristics on Mean TE (MTE). Design/methodology/approach – The researchers independently conducted a systematic review of more than 400 abstracts and 85 full-text papers. Original keywords were applied to seven key electronic databases. Results from a meta-regression analysis of 85 published papers totalling 443 TE distributions in dairy farms worldwide are discussed. Findings – The variation in the MTE indexes reported in the literature can be explained by the methodology of estimations (method of estimation, functional form of frontier models, model dimensionality), the farms geographical location and farm size. Additionally, the results suggest that, given the state of technology prevailing in each country at the time that the studies on TE were conducted, dairy farmers in the sample could increase milk output by 20.9 per cent (level of inefficiency), on average, if they produce on their frontiers. Originality/value – This study makes two important contributions: first, it updates and compares previous works on frontier estimation of TE in dairy farms; and second, it adds two dimensions of dairy farms, size (herd and land area) and economic development, to the known differentials of TE measurement. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Productivity and Performance Management Emerald Publishing

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1741-0401
DOI
10.1108/IJPPM-02-2015-0027
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to complement and extend previous literature reviews on Technical Efficiency (TE) in dairy farms, analysing the effects of different methodologies and study-specific characteristics on Mean TE (MTE). Design/methodology/approach – The researchers independently conducted a systematic review of more than 400 abstracts and 85 full-text papers. Original keywords were applied to seven key electronic databases. Results from a meta-regression analysis of 85 published papers totalling 443 TE distributions in dairy farms worldwide are discussed. Findings – The variation in the MTE indexes reported in the literature can be explained by the methodology of estimations (method of estimation, functional form of frontier models, model dimensionality), the farms geographical location and farm size. Additionally, the results suggest that, given the state of technology prevailing in each country at the time that the studies on TE were conducted, dairy farmers in the sample could increase milk output by 20.9 per cent (level of inefficiency), on average, if they produce on their frontiers. Originality/value – This study makes two important contributions: first, it updates and compares previous works on frontier estimation of TE in dairy farms; and second, it adds two dimensions of dairy farms, size (herd and land area) and economic development, to the known differentials of TE measurement.

Journal

International Journal of Productivity and Performance ManagementEmerald Publishing

Published: Mar 7, 2016

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