Why Governments Are Terrible at Forecasting Revenue

Episode 31 of Government Spending with Fexingo explores why governments consistently miss their revenue forecasts — and not by accident. Lucas and Luna dig into the specific mechanics of how the U.S. Congressional Budget Office and state revenue estimators use 'static scoring' that ignores how tax changes actually affect behavior. They walk through the 2017 Tax Cuts and Jobs Act as a case study: the CBO predicted a $1.5 trillion revenue loss over ten years, but actual corporate tax receipts fell less than half that projection in the first three years. They also examine why states like California chronically overestimate income tax revenue from capital gains, and why Colorado's cannabis tax revenue fell 30 percent short of forecasts. The hosts explain the key flaw: revenue estimators assume tax bases are inert, but people and businesses restructure their affairs the moment a new tax law passes. The episode unpacks 'dynamic scoring,' why the Treasury Department's own models often contradict the CBO, and why the gap between forecast and reality matters for borrowing costs. If you've ever wondered why budget debates hinge on dueling revenue projections, this episode shows you the hidden assumptions. #RevenueForecasting #StaticScoring #DynamicScoring #CBO #TaxCutsAndJobsAct #CorporateTax #StateBudgets #CaliforniaRevenue #ColoradoCannabisTax #CapitalGains #TreasuryDepartment #TaxElasticity #BehavioralResponse #BudgetPolitics #Economics #GovernmentSpending #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo