"background": "The adoption of advanced manufacturing systems in developing economies is critical for industrial growth, yet robust methodological frameworks for evaluating their uptake and impact are lacking. Existing studies often rely on cross-sectional surveys, which fail to account for temporal trends and confounding factors, limiting causal inference. ", "purpose and objectives": "This study aims to develop and apply a rigorous econometric framework to evaluate the adoption rates of modern manufacturing systems within the country's industrial sector. The primary objective is to quantify the causal effect of targeted policy interventions on technology adoption. ", "methodology": "A quasi-experimental difference-in-differences (DiD) model was employed, using panel data from manufacturing plants. The core specification is Y{it = \0 + \1 (\) + \ + \ +, where Y₈ₓ is the adoption status. Inference is based on cluster-robust standard errors at the plant level. ", "findings": "Plants exposed to the intervention showed a statistically significant increase in adoption probability of 18. 7 percentage points (95% CI: 12. 4, 25. 0) compared to the control group. The effect was more pronounced in medium-scale enterprises than in large conglomerates. ", "conclusion": "The DiD approach provides a valid and powerful methodological tool for evaluating manufacturing system adoption, revealing a strong positive causal link between the studied interventions and technology uptake. ", "recommendations": "Policy design should incorporate quasi-experimental evaluation methods from inception. Future industrial support programmes should be tailored to address the specific barriers faced by different scales of enterprise. ", "key words": "difference-in-differences, manufacturing systems, technology adoption, econometric evaluation, industrial policy", "contribution statement": "This paper provides the first application of a difference-in-differences model to isolate the causal effect of industrial policy on manufacturing systems adoption in this context, introducing a
Chinweike Okonkwo (Mon,) studied this question.
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