Revenue forecasting in the mining industries: A data-driven approach

Robust forecasting of mining sector revenues is key to effective budgeting (and broader fiscal management) in many resource-rich countries. However, this is challenging in practice, given commodity market volatility, the extended lags (and often opaque processes) between resource discoveries and fiscal yields, and the heterogeneity of taxable entities within the sector. Such issues are exacerbated by capacity deficits: quantitative sector assessment frameworks are seldom employed or maintained by revenue authorities. In contrast, commercial mining entities typically have well-developed tools for analysing future cash flows and profitability. This paper identifies considerable scope to strengthen public revenue forecasts by drawing more heavily on industry best practices and data sources, including through bottom-up analysis of the tax base and a more rigorous approach to modelling key uncertainty drivers.