Technical efficiency, technological progress and productivity growth of large and medium manufacturing industries in Ethiopia: A data envelopment analysis

The purpose of this study is to assess empirically how the technical efficiency scores for 43 sub-sectors and their determinants over the period 2010 to 2017 show significant variation across the sub-sectors. The study applied a two-step approach for measuring technical efficiency and its determinan...

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Autores principales:	Obsa Teferi Erena, Mesfin Mala Kalko, Sara Adugna Debele
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2021
Materias:	technical efficiency technological progress productivity dea tobit model ethiopian manufacturing sector Finance HG1-9999 Economic theory. Demography HB1-3840
Acceso en línea:	https://doaj.org/article/b4361a0c4ab74ce6aa32dd09cd891cc1
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spelling	oai:doaj.org-article:b4361a0c4ab74ce6aa32dd09cd891cc12021-11-11T14:23:43ZTechnical efficiency, technological progress and productivity growth of large and medium manufacturing industries in Ethiopia: A data envelopment analysis2332-203910.1080/23322039.2021.1997160https://doaj.org/article/b4361a0c4ab74ce6aa32dd09cd891cc12021-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23322039.2021.1997160https://doaj.org/toc/2332-2039The purpose of this study is to assess empirically how the technical efficiency scores for 43 sub-sectors and their determinants over the period 2010 to 2017 show significant variation across the sub-sectors. The study applied a two-step approach for measuring technical efficiency and its determinants. A data envelopment analysis output-orientation (i.e. both CCR & BCC models) is used to estimate technical efficiency scores for 43 sub-sectors over the period 2010 to 2017. Malmquist productivity index (MPI) output orientation is also applied to compute technical efficiency change, technological progress, and productivity change. The estimated technical efficiency score shows significant variation across the sub-sectors. Thus, we used a Tobit regression model to scrutinize what defines the variation in technical efficiency scores using three years of panel data which covers 2015 to 2017. Moreover, the 43 sub-sectors were further grouped into 14 major sub-sectors and classified as public and private to examine whether there is a technical efficiency score discrepancy between the same sub-sectors operating under different ownership. For measuring overall technical efficiency, we used two output variables (i.e., value-added and operating surplus) and two input variables (i.e., total fixed assets and a total number of employees). When reducing the sub-sectors to fourteen major groups, the operating surplus was not included, thus we used value-added and total sales as output variables and total fixed assets, the total number of employees, and cost of raw materials used in the production process as input variables. To shed light on the source of inefficiency, technical efficiency is decomposed into pure technical efficiency and scale efficiency. This study found that the sector had experienced a 37 percent technical efficiency in overall average when the CCR model was used. The study also claims that public owned subsectors are less likely to be efficient than private subsectors. The regression results show the capital expenditure ratio has a significant positive influence on technical efficiency. The Malmquist index result also shows, on average, the sector had registered a 10.5% technological progress and a 13% productivity growth over the period 2010–2017. The findings of the study would have implications for policymakers, government, and firm owners in that it offers an insight into the source of productivity growth in the sector.Obsa Teferi ErenaMesfin Mala KalkoSara Adugna DebeleTaylor & Francis Grouparticletechnical efficiencytechnological progressproductivitydeatobit modelethiopian manufacturing sectorFinanceHG1-9999Economic theory. DemographyHB1-3840ENCogent Economics & Finance, Vol 9, Iss 1 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	technical efficiency technological progress productivity dea tobit model ethiopian manufacturing sector Finance HG1-9999 Economic theory. Demography HB1-3840
spellingShingle	technical efficiency technological progress productivity dea tobit model ethiopian manufacturing sector Finance HG1-9999 Economic theory. Demography HB1-3840 Obsa Teferi Erena Mesfin Mala Kalko Sara Adugna Debele Technical efficiency, technological progress and productivity growth of large and medium manufacturing industries in Ethiopia: A data envelopment analysis
description	The purpose of this study is to assess empirically how the technical efficiency scores for 43 sub-sectors and their determinants over the period 2010 to 2017 show significant variation across the sub-sectors. The study applied a two-step approach for measuring technical efficiency and its determinants. A data envelopment analysis output-orientation (i.e. both CCR & BCC models) is used to estimate technical efficiency scores for 43 sub-sectors over the period 2010 to 2017. Malmquist productivity index (MPI) output orientation is also applied to compute technical efficiency change, technological progress, and productivity change. The estimated technical efficiency score shows significant variation across the sub-sectors. Thus, we used a Tobit regression model to scrutinize what defines the variation in technical efficiency scores using three years of panel data which covers 2015 to 2017. Moreover, the 43 sub-sectors were further grouped into 14 major sub-sectors and classified as public and private to examine whether there is a technical efficiency score discrepancy between the same sub-sectors operating under different ownership. For measuring overall technical efficiency, we used two output variables (i.e., value-added and operating surplus) and two input variables (i.e., total fixed assets and a total number of employees). When reducing the sub-sectors to fourteen major groups, the operating surplus was not included, thus we used value-added and total sales as output variables and total fixed assets, the total number of employees, and cost of raw materials used in the production process as input variables. To shed light on the source of inefficiency, technical efficiency is decomposed into pure technical efficiency and scale efficiency. This study found that the sector had experienced a 37 percent technical efficiency in overall average when the CCR model was used. The study also claims that public owned subsectors are less likely to be efficient than private subsectors. The regression results show the capital expenditure ratio has a significant positive influence on technical efficiency. The Malmquist index result also shows, on average, the sector had registered a 10.5% technological progress and a 13% productivity growth over the period 2010–2017. The findings of the study would have implications for policymakers, government, and firm owners in that it offers an insight into the source of productivity growth in the sector.
format	article
author	Obsa Teferi Erena Mesfin Mala Kalko Sara Adugna Debele
author_facet	Obsa Teferi Erena Mesfin Mala Kalko Sara Adugna Debele
author_sort	Obsa Teferi Erena
title	Technical efficiency, technological progress and productivity growth of large and medium manufacturing industries in Ethiopia: A data envelopment analysis
title_short	Technical efficiency, technological progress and productivity growth of large and medium manufacturing industries in Ethiopia: A data envelopment analysis
title_full	Technical efficiency, technological progress and productivity growth of large and medium manufacturing industries in Ethiopia: A data envelopment analysis
title_fullStr	Technical efficiency, technological progress and productivity growth of large and medium manufacturing industries in Ethiopia: A data envelopment analysis
title_full_unstemmed	Technical efficiency, technological progress and productivity growth of large and medium manufacturing industries in Ethiopia: A data envelopment analysis
title_sort	technical efficiency, technological progress and productivity growth of large and medium manufacturing industries in ethiopia: a data envelopment analysis
publisher	Taylor & Francis Group
publishDate	2021
url	https://doaj.org/article/b4361a0c4ab74ce6aa32dd09cd891cc1
work_keys_str_mv	AT obsateferierena technicalefficiencytechnologicalprogressandproductivitygrowthoflargeandmediummanufacturingindustriesinethiopiaadataenvelopmentanalysis AT mesfinmalakalko technicalefficiencytechnologicalprogressandproductivitygrowthoflargeandmediummanufacturingindustriesinethiopiaadataenvelopmentanalysis AT saraadugnadebele technicalefficiencytechnologicalprogressandproductivitygrowthoflargeandmediummanufacturingindustriesinethiopiaadataenvelopmentanalysis
_version_	1718438977154842624

Technical efficiency, technological progress and productivity growth of large and medium manufacturing industries in Ethiopia: A data envelopment analysis

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