Forecasting and Analysing Corporate Tax Revenues in Sweden Using Bayesian VAR Models

Corporate tax revenue forecasts are important for governmental agencies, but are complicated to achieve with high precision and generally also difficult to connect to governments’ macroeconomic forecasts. This paper proposes a solution to these problems by decomposing corporate tax revenues and connecting the components to different determinants using Bayesian VAR models. Applied to Sweden, we find that most of the variation in forecasting errors of net operating surplus and net business income are attributable to shocks in factors identified in the literature, and that the forecasting performance is improved by conditioning on the macroeconomic development.