How to Forecast Corporate Income Tax Revenues

Corporate income tax (CIT) collections are among the most difficult revenues to forecast—even with adequate staffing, comprehensive data, and a stable tax design. In practice, forecasting units typically operate under less ideal conditions. As institutional constraints take time to ease, this Note sets out a practical toolkit of methods to strengthen forecasting capacity across a wide range of country contexts. It outlines techniques that provide unbiased forecasts even when the impact of past reforms is only partially known, introduces approaches to account for ongoing and prospective policy changes to leverage time-series approaches, and highlights the potential efficiency gains achievable through structural modeling. A simple empirical assessment of forecasting specifications shows that parsimonious regression models, when backed by sufficient data, can improve prediction accuracy, even though the benchmark of assuming CIT revenues grow in line with GDP remains difficult to beat.