Binary logistic regression analysis on determinants of capacity utilization in medium and large manufacturing industries in Ethiopia

Zemene Yohannes (), Amare Matebu () and Fekade Asrat ()

Asian Development Policy Review, 2023, vol. 11, issue 1, 1-11

Abstract: Most manufacturing industries in Ethiopia are not operating at full capacity. The manufacturing industry is one of the main determinants of the economic growth of a country; therefore, the reasons why they are not operating at full capacity have to be assessed. The aim of this study is to assess determinant factors associated with Ethiopia’s large and medium manufacturing industries (henceforth referred to as LMMIs in this study) not working at full capacity based on 2020 LMMI survey data. In this study, 3,067 large and medium manufacturing industries were examined. Among these industries, 78.71% were not working at their full capacity, while the remaining 21.29% were. Binary logistic methods were used to analyze the data. Study results found that the region, the number of months the establishment operated during the study period, the workplace of the manufacturing company, the effect of Covid-19, and the current most serious problem facing the establishment were statistically significant predictors for working at full capacity. LMMI intervention programs, including regional work, increasing the number of working months in the year, workplace, the effect of unexpected external influences (e.g., COVID-19) and major problems among LMMIs, should be put in place to increase the production to full capacity.

Keywords: Full capacity; Likelihood ratio test; LMMI; Logistic regressions; Goodness of fit test; Marginal effect. (search for similar items in EconPapers)
Date: 2023
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