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Policy Analytics shows county a forecasting tool to model LIT scenarios using census and revenue data
Summary
Policy Analytics demonstrated a dynamic LIT forecasting model that combines Census/American Community Survey and Department of Revenue collection data to project unit-level revenue under alternative rate and distribution scenarios; advisors asked units to provide local data for refined outputs.
Sam RB of Policy Analytics presented a forecasting model built to project unit-level LIT revenues under hypothetical rate scenarios and distribution methodologies. He said the model uses American Community Survey and Census Bureau population data (presenter cited both 2020 and 2023 data for different distribution purposes) plus recent Department of Revenue collection data to estimate adjusted gross income by municipality and to simulate outcomes such as a 0.4% EMS LIT or municipal opt-outs.
Sam described how the tool can run live scenarios in meetings, letting stakeholders see how different weighting methodologies (for example population vs. square mileage for fire/EMS) and municipal opt-in/opt-out choices affect taxed adjusted gross income and unit receipts. He emphasized the model's outputs depend on accurate, unit-level data and encouraged each municipal fiscal officer and special unit to deliver requested financials for the next scenario run.
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