Title: A Projection of Motor Fuel Tax Revenue and Analysis of Alternative Revenue Sources in Georgia
Abstract:Motor fuel tax revenue currently supplies the majority of funding for transportation agencies at the state and federal level. Georgia uses excise and sales taxes to generate revenue for the Georgia De...Motor fuel tax revenue currently supplies the majority of funding for transportation agencies at the state and federal level. Georgia uses excise and sales taxes to generate revenue for the Georgia Department of Transportation (GDOT). Inflation and increases in vehicle fuel efficiency have reduced the effectiveness of these taxes in recent years. These changes have resulted in drivers purchasing less fuel and generating less fuel tax revenue, which weakens GDOT’s ability to maintain Georgia’s transportation assets. This thesis uses literature from regional and state agencies, academic reports, and databases to identify factors that affect motor fuel tax revenue and then creates a model to predict Georgia’s fuel tax receipts in 2020 and 2030. It also discusses and evaluates other transportation funding mechanisms that could replace or supplement the fuels tax and recommends how best to implement these strategies. In Georgia, fuel tax revenue is based on fuel consumption, which is directly affected by vehicle miles traveled (VMT) and fuel efficiency, and fuel price. Several forces influence VMT and fuel efficiency including demographic factors such as population density and persons per household, economic factors such as, income distribution and gross domestic product (GDP), and technological factors such as alternative vehicle development. The model incorporates these factors and their interactions by segmenting vehicles into four classes: personal vehicles, single-unit trucks, combination trucks, and transit vehicles, and then creating unique forecasting frameworks for each segment. The model first calculates 2009 VMT and revenue to compare these projections with known values to validate the model’s logic and create a baseline for projecting future revenue. Then, the 2009 model’s conceptual framework and additional variables are used to project future fuel tax revenue. The model calculates revenue from personal vehicles using a proportional categorical method that uses income as its main explanatory variable as well as user-prompted variables in post-processing. Freight revenue is calculated using historical VMT-GDP relationships in combination with other user-prompted inputs. Because of the model’s input-output nature, users can create a virtually limitless array of revenue projection scenarios for 2020 and 2030. To show a probable range of these outputs, conservative and aggressive scenario outputs are presented and discussed for each year. These revenue outputs are compared against the 2009 values on an absolute, per-capita, and per-mile basis. The results indicate that real revenue will increase from 2009 to 2020 but actually decline between 2020 and 2030 due to fuel economy improvements and widespread use of alternatively fueled vehicles. To counteract these potential revenue declines, this document discusses methods of increasing fuel tax revenue, including increasing the current fuels tax and/or linking it to inflation, VMT-fees, widespread tolling, and regional transportation sales taxes. Each of these mechanisms has advantages and drawbacks, depending on an agency’s overall set of objectives. After evaluating each method, the author recommend s first evaluating Georgia’s upcoming regional transportation sales tax, and then aiming to implement a VMT-fee by 2020 by conducting extensive trials and public involvement. Regardless of what specific steps Georgia’s leaders take, change will be needed to maintain Georgia’s infrastructure and its economic competitiveness.Read More
Publication Year: 2012
Publication Date: 2012-04-06
Language: en
Type: dissertation
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Title: $A Projection of Motor Fuel Tax Revenue and Analysis of Alternative Revenue Sources in Georgia
Abstract: Motor fuel tax revenue currently supplies the majority of funding for transportation agencies at the state and federal level. Georgia uses excise and sales taxes to generate revenue for the Georgia Department of Transportation (GDOT). Inflation and increases in vehicle fuel efficiency have reduced the effectiveness of these taxes in recent years. These changes have resulted in drivers purchasing less fuel and generating less fuel tax revenue, which weakens GDOT’s ability to maintain Georgia’s transportation assets. This thesis uses literature from regional and state agencies, academic reports, and databases to identify factors that affect motor fuel tax revenue and then creates a model to predict Georgia’s fuel tax receipts in 2020 and 2030. It also discusses and evaluates other transportation funding mechanisms that could replace or supplement the fuels tax and recommends how best to implement these strategies. In Georgia, fuel tax revenue is based on fuel consumption, which is directly affected by vehicle miles traveled (VMT) and fuel efficiency, and fuel price. Several forces influence VMT and fuel efficiency including demographic factors such as population density and persons per household, economic factors such as, income distribution and gross domestic product (GDP), and technological factors such as alternative vehicle development. The model incorporates these factors and their interactions by segmenting vehicles into four classes: personal vehicles, single-unit trucks, combination trucks, and transit vehicles, and then creating unique forecasting frameworks for each segment. The model first calculates 2009 VMT and revenue to compare these projections with known values to validate the model’s logic and create a baseline for projecting future revenue. Then, the 2009 model’s conceptual framework and additional variables are used to project future fuel tax revenue. The model calculates revenue from personal vehicles using a proportional categorical method that uses income as its main explanatory variable as well as user-prompted variables in post-processing. Freight revenue is calculated using historical VMT-GDP relationships in combination with other user-prompted inputs. Because of the model’s input-output nature, users can create a virtually limitless array of revenue projection scenarios for 2020 and 2030. To show a probable range of these outputs, conservative and aggressive scenario outputs are presented and discussed for each year. These revenue outputs are compared against the 2009 values on an absolute, per-capita, and per-mile basis. The results indicate that real revenue will increase from 2009 to 2020 but actually decline between 2020 and 2030 due to fuel economy improvements and widespread use of alternatively fueled vehicles. To counteract these potential revenue declines, this document discusses methods of increasing fuel tax revenue, including increasing the current fuels tax and/or linking it to inflation, VMT-fees, widespread tolling, and regional transportation sales taxes. Each of these mechanisms has advantages and drawbacks, depending on an agency’s overall set of objectives. After evaluating each method, the author recommend s first evaluating Georgia’s upcoming regional transportation sales tax, and then aiming to implement a VMT-fee by 2020 by conducting extensive trials and public involvement. Regardless of what specific steps Georgia’s leaders take, change will be needed to maintain Georgia’s infrastructure and its economic competitiveness.