Abstract

The study analysed the effciency of the metal manufacturing sector in Zimbabwe. The background to this study is the decimation of the sector given its contribution to vital economic indicators like employment, Gross Domestic Product (GDP) and export. A non-parametric methodology, Data Enveloping Analysis (DEA) was used to measure effciency in the metal sector and estimating the drivers and barriers to effciency using STATA econometric software. Data on metal manufacturing inputs; cost of raw material (CM), energy (E), water and sewages (WS) and cost of services (S) were transformed into multiple outputs; sales (SLS), value added (VA) and gross value of production (GVP). Using an input oriented constant returns to scale (CRS) model, in the Metals sub-sector of the manufacturing sector, 38% of the Decision Making Unit (DMUs) are effcient and 62% are ineffcient. At least 52% of the DMUs are operating above the average effciency of 68%, whereas 48% of the DMUs are struggling below the average effciency level. Under an input oriented variable returns to scale (VRS) model, in the Metals sub-sector of the manufacturing sector, 57% of the DMUs are effcient and 43% are ineffcient. At least 62% of the DMUs are operating above the average effciency of 86%, whereas 38% of the DMUs are struggling below the average effciency level. The study's literature confrms that small to medium metal manufacturing frms have increased, which are mainly informal and thus pose a threat to government when it comes to instituting effciency policies.

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