"background": "Time-series forecasting is critical for optimising capital investments in industrial process-control systems. A previously published model for evaluating their long-term cost-effectiveness in a West African context required independent validation to assess its generalisability and robustness. ", "purpose and objectives": "This study aimed to replicate and critically evaluate the methodological rigour of the specified forecasting model. The core objective was to test its predictive accuracy and parameter stability using updated, locally sourced data. ", "methodology": "We executed a direct replication using the original autoregressive integrated moving average (ARIMA) specification, formalised as \ᵈ yt = c + =1^{p\ \ᵈ yt-i + =1^q\ -j + \, where yₜ represents the cost-effectiveness index. The model was re-estimated with a new dataset of comparable scale, and its forecasts were compared against held-back observational data. Inference was based on robust standard errors to account for heteroskedasticity. ", "findings": "The replication confirmed the model's directional accuracy for forecasting cost trends but revealed a systematic overestimation of cost-saving magnitudes by approximately 15%. Parameter estimates for the autoregressive components were statistically significant (p < 0. 05) but showed greater variability than originally reported, indicating lower stability in different sampling conditions. ", "conclusion": "The original model provides a structurally sound framework, but its predictive precision is contingent on highly specific input data characteristics, limiting its unmodified transferability to other operational contexts within the region. ", "recommendations": "Future applications should incorporate recalibration using local historical data and consider integrating exogenous economic variables to improve forecast robustness and practical utility for infrastructure planning. ", "key words": "replication study, time-series analysis, cost-benefit analysis, control systems, forecasting, ARIMA, engineering economics", "contribution statement": "This study provides the first independent validation of
Ndiaye et al. (Sun,) studied this question.
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