A GM (1,1)-ARIMA-MPI-based forecasting model for waterway maintenance funding requirements

Currently, inland waterway maintenance funds in China rely mainly on fiscal appropriations, supplemented by lockage fees and power-generation revenues. To forecast future funding needs scientifically, we propose a GM(1,1)-ARIMA-MPI hybrid model that integrates the grey prediction model GM(1,1), the autoregressive integrated moving-average (ARIMA) model and the manufacturing progress index (MPI) method. The model projects that CNY 50.05 billion will be required during the 15th Five-Year period and CNY 53.90 billion during the 16th Five-Year period. The results indicate that the model can reliably estimate future waterway maintenance funding requirements; the projected amounts can feed into inland water-transport planning, while the policy recommendations help broaden financing channels and improve the scientific allocation of public funds.