2020•Cogent Economics & FinanceOpen access

Sectoral and spatio-temporal differentiation in technical efficiency: A meta-regression

Justice Gameli Djokoto, Ferguson Korbla Gidiglo, Francis Yao Srofenyoh, Kofi Aaron A-O. Agyei-Henaku, Akua A. Afrane Arthur, Charlotte Badu-Prah

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Abstract

In the literature, existing meta-regressions on efficiency have focused on specific sectors in a country or multiple country and on specific economic activity. None of the available efficiency meta-regressions covers multiple sectors of an economy. We contribute to the literature by investigating the technical efficiency differentiation within a multi-sectoral environment. Using data from 152 publications yielding 223 observations from diverse sources and applying meta-regression analysis, we investigated the heterogeneity in mean technical efficiency (MTE), assessed the temporal and spatial drivers of estimated technical efficiency for Ghana. We found heterogeneity in the estimated MTE. The selected cauchit functional form of the fractional regression model showed sectoral and spatial variables drive heterogeneity in MTE. There was a seeming technical efficiency regression with average MTE of 0.676 that requires greater effort in the management of production than has been the case previously in order to close the output gap.

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In the literature, existing meta-regressions on efficiency have focused on specific sectors in a country or multiple country and on specific economic activity. None of the available efficiency meta-regressions covers multiple sectors of an economy. We contribute to the literature by investigating the technical efficiency differentiation within a multi-sectoral environment. Using data from 152 publications yielding 223 observations from diverse sources and applying meta-regression analysis, we investigated the heterogeneity in mean technical efficiency (MTE), assessed the temporal and spatial drivers of estimated technical efficiency for Ghana. We found heterogeneity in the estimated MTE. The selected cauchit functional form of the fractional regression model showed sectoral and spatial variables drive heterogeneity in MTE. There was a seeming technical efficiency regression with average MTE of 0.676 that requires greater effort in the management of production than has been the case previously in order to close the output gap.

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Available abstract

In the literature, existing meta-regressions on efficiency have focused on specific sectors in a country or multiple country and on specific economic activity. None of the available efficiency meta-regressions covers multiple sectors of an economy. We contribute to the literature by investigating the technical efficiency differentiation within a multi-sectoral environment. Using data from 152 publications yielding 223 observations from diverse sources and applying meta-regression analysis, we investigated the heterogeneity in mean technical efficiency (MTE), assessed the temporal and spatial drivers of estimated technical efficiency for Ghana. We found heterogeneity in the estimated MTE. The selected cauchit functional form of the fractional regression model showed sectoral and spatial variables drive heterogeneity in MTE. There was a seeming technical efficiency regression with average MTE of 0.676 that requires greater effort in the management of production than has been the case previously in order to close the output gap.

Key concepts: Meta-regression, Econometrics, Regression, Economics, Regression analysis, Statistics, Meta-analysis, Mathematics

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