Technical Efficiency in Agribusiness: A Meta‐Analysis on Ghana

Abstract

The few meta-analyses published on efficiency in agriculture focused on traditional agriculture to the neglect of agribusiness. This article presents a meta-analysis on agribusiness using Ghana as a case. Databases including AgEconsearch, Google scholar, EBSCOHost, EmeraldInsight, and Wiley online Library among others were searched in order to identify published studies relating to the subsectors of agribusiness. The selected loglog fractional regression model revealed that mean technical efficiency (MTE) increased over time with a mean value of 62%. MTEs of geographical sections of Ghana are also similar. Time series models possess higher MTE than panel data MTEs. In line with theory, models without functional forms and distance functions elicited higher MTE than Cobb-Douglas and translog functions. Nontraditional agricultural production showed higher MTE than traditional agriculture. MTEs in the production subsector do not differ from those in the manufacturing subsector. While this indifference suggests that value adding manufacturing subsector is as efficient as the primary production agriculture, and the increasing MTE notwithstanding, efficiency improving measures including training in farm management are required to make up for the mean difference of 38% found. [JEL Classification: Q13]. C 2016 Wiley Periodicals, Inc.

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“…review 34 articles on agricultural efficiency in developing countries. Another MRA on agriculture is provided byOgundari (2014) who investigates the dynamics of African agricultural efficiency levels obtained from 442 frontier studies Djokoto and Gidiglo (2016). and focus on the heterogeneity in efficiency scores from 34 primary papers on Ghanaian agriculture Iliyasu et al (2014).…”

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“…In particular, Table 4 has each of the empirical surveys attributed into one of the ISIC sections and their associated JEL codes. For instance, Hollingsworth (2003), who surveyed 188 published papers on frontier efficiency analysis in hospitals and health (2007) Q12, D24 Coelli, (1995) Q10, C14, D24 Djokoto (2015) Q10, Q18, D24 Djokoto and Gidiglo (2016) Q10, Q13 Djokoto et al (2016) D24, Q12 Färe et al (2013) Q10, C14 Gorton and Davidova (2004) L25 (2018) C13, C80, G20, G21, L25 Altunbaş et al (2001) G21, D21, G23 Ashton and Hardwick (2000) G20, D61, G21 Berger and Humphrey (1992) G20, G21, G22, G23, G24, G28, G29 Berger and Humphrey (1997) G20, G21, G22, G23, G24, G28, G29 Berger et al (1993) G20, G21, G22, G23, G24, G28, G29 Berger (2007) G20, G21, G22, G23, G24, G28, G29 Berger et al (1999) G21, G28, G34, E58, L89 Colwell and Davis (1992) G20, C14, D24 DeYoung et al (2009) G21, G34 Eling and Luhnen (2010) G22, I13, J65 Fethi and Pasiouras (2010) G21 Galagedera (2003) D92, E22, F21, G11, G24, G31, H54, O16, P45, R42, R53 Iršová and Havránek (2010) C13, G21, L25 Jreisat and Paul (2010) E50, G21 Kaffash and Marra (2017) G21, G22, E50, C83 Macoris et al (2016) G20, G21, C67 Paradi and Zhu (2013) E50, G21 von Furstenberg (2008) G21, G20, R30, R12 Worthington (2010) G21, G20…”