{ "background": "The modernisation of industrial machinery fleets is critical for economic development, yet robust methodologies for quantifying the adoption rates of advanced systems in emerging economies are lacking. Existing approaches often fail to isolate the causal effect of intervention programmes from broader temporal trends.", "purpose and objectives": "This study aims to develop and validate a quasi-experimental econometric model to accurately measure the causal impact of a national industrial modernisation initiative on the adoption rates of advanced machinery systems within the country.", "methodology": "A difference-in-differences (DiD) model was employed, using panel data from manufacturing firms. The treatment group participated in a targeted capital allowance scheme, while the control group did not. The core model is specified as $Y{it} = \\alpha + \\beta (Treati \\times Postt) + \\gammai + \\deltat + \\epsilon{it}$, where robust standard errors were clustered at the firm level. Data were collected via structured surveys and verified through on-site audits.", "findings": "The DiD estimator revealed a statistically significant positive effect of the scheme on adoption rates. Firms in the treatment group exhibited a 17.5 percentage point increase in the adoption of computer-numerical-control machinery compared to the control group (95% CI: 12.1 to 22.9). The parallel trends assumption was validated using pre-intervention data.", "conclusion": "The proposed DiD model provides a rigorous methodological framework for evaluating industrial technology adoption, successfully isolating the programme's effect from confounding factors. It confirms the efficacy of targeted fiscal incentives in accelerating capital investment in machinery fleets.", "recommendations": "Policymakers should integrate quasi-experimental evaluation designs into the planning of industrial programmes. Future research should apply this model to longitudinal data to assess long-term sustainability and productivity impacts.", "key words": "difference-in-differences, industrial modernisation, machinery fleets, adoption rate, causal inference, econometric evaluation", "contribution statement": "