{"id":419,"date":"2022-12-27T07:38:41","date_gmt":"2022-12-27T07:38:41","guid":{"rendered":"https:\/\/webresources-uat.com\/nchrp1918\/?page_id=419"},"modified":"2022-12-27T07:38:41","modified_gmt":"2022-12-27T07:38:41","slug":"8-revenue-modeling","status":"publish","type":"page","link":"https:\/\/crp.trb.org\/nchrpwebresource2\/research-and-planning-overview\/8-revenue-modeling\/","title":{"rendered":"(8) Revenue Modeling"},"content":{"rendered":"\n
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RESEARCH AND PLANNING<\/a>  <\/span>|   SETUP<\/a>  |   ONGOING OPERATIONS<\/a>  | TRANSITIONING AND GROWING<\/a><\/div><\/div>\n \n
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Revenue Modeling (8)<\/h1>\n \n

Description:<\/strong><\/h3> \n\n

\n \n A revenue modeling tool allows an agency to compare scenarios, such as doing nothing, increasing rates of existing taxes and fees (such as fuel excise taxes and vehicle-based fees), and enacting new mechanisms such as RUC. Revenue modeling tools help clarify the magnitude and urgency of the revenue outlook in any given jurisdiction. The tools also give decision-makers and lawmakers a clear picture of the stakes and motivations for considering RUC. <\/p> \n\n

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Details:<\/strong><\/h3>\n

Revenue modeling creates a mathematical model built on a software tool, such as a spreadsheet, to forecast costs and revenues for RUC and other vehicle-related charges. The model uses a range of inputs to produce a range of outputs. Inputs may include transportation forecast values, such as vehicle miles traveled and number of vehicles; policy inputs, such as RUC rates and transition strategies; and technical inputs, such as mileage reporting account manager costs and state agency operational costs. Outputs may include yearly breakdowns of total and net RUC revenue, as well as total and net fuel tax revenue. \n<\/p>\n

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Primary Uses:<\/strong><\/h3>\n

Generate policy studies focused on transportation revenue or legislative impact statements. Combine with cost model to create overall financial model for project.<\/p>\n <\/div>\n \n

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Best Practices\/Lessons Learned:<\/strong><\/h3>\n