IS ORGANIC AGRICULTURE MORE SCALE EFFICIENT THAN CONVENTIONAL AGRICULTURE? THE CASE OF COCOA CULTIVATION IN GHANA
Justice Djokoto (),
Victor Owusu and
Dadson Awunyo-Vitor ()
Review of Agricultural and Applied Economics (RAAE), 2020, vol. 23, issue 2
Abstract:
Research background: Despite the growing social recognition of the positive role played by organic farming in the conservation of natural resources and the reduction or elimination of the negative externalities of modern agriculture, the economic competitiveness of organic versus conventional agriculture is a contentious issue. Studies on scale efficiency in the agricultural economics literature, in general, did not address the differences in production practices such as organic and conventional production. Purpose of the article: We estimated scale efficiency of organic and conventional production, tested for differences between organic and conventional agriculture scale efficiency, and explored the sources of inefficiencies. Methods: This was accomplished using cross-sectional data on 658 organic and conventional cocoa farmers, for the 2012/13 production season in the Eastern Region of Ghana. The analysis accounted for selection bias and recognised the fractional property of the scale efficiency measure. Findings & Value added: Organic agriculture is less scale efficient than conventional agriculture. Whilst we recommend that both producer groups improve scale efficiency, organic producers require greater work to do to make up for the almost 50% scale inefficiency. We also found farmer-based organisations to significantly influence scale efficiency. This calls for the need to strengthen farmer-based organisations to increase participation, among other reasons. We departed from the existing scale efficiency literature in a three of ways. We accounted for selection-bias using propensity score matching in the organic and conventional samples in analysing scale efficiency, modelled scale inefficiency using fractional regression and empirically selected the appropriate link function using a battery of tests. Finally, we accounted for an important policy variable; farmer-based organisation. We employed propensity score matching that accounted from observable biases. Further research may consider other methods that account for both observed and unobserved variations.
Keywords: Crop Production/Industries; Farm Management; Production Economics; Productivity Analysis (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://ageconsearch.umn.edu/record/308407/files/RAAE_2_2020_Djokoto_et_al.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ags:roaaec:308407
DOI: 10.22004/ag.econ.308407
Access Statistics for this article
More articles in Review of Agricultural and Applied Economics (RAAE) from Faculty of Economics and Management, Slovak Agricultural University in Nitra Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().