Research on public perceptions of highway and transit spending, local option sales taxes, autonomous vehicle impacts on government finances, and commercial vehicle enforcement benefits.
Who Thinks America Spends Too Much on Highways and Mass Transit?
Devajyoti Deka, Rutgers, The State University of New JerseyShow Abstract
Da Fei, Rutgers, The State University of New Jersey
An increasing gap between transportation revenue and expenditure at all levels of governance in recent years has been highly concerning to transportation officials and researchers in the United States. Despite decreasing revenue through taxes, sharply increasing cost of transportation projects, and increasing transportation cost for average households, a small but significant proportion of Americans perceive public spending on highways and mass transit as too much. With pooled national data from 21 General Social Surveys in the years between 1984 and 2016, this study examines the characteristics of Americans who perceive highway and mass transit spending as too much. Generalized mixed logit models are used to examine how demographic and socioeconomic characteristics, geographic location within the country, ideologies, political party affiliations, and religious beliefs affect the perception of highway and mass transit spending. The results reveal that fiscal conservatism has the strongest effect on the perception that too much money is spent on transportation. People with a high level of education are less likely to perceive both highway and transit spending as too much, whereas people with a low level of education have the opposite perception. Young people are less likely to perceive transit spending as too much, but more likely to perceive highway spending as too much. Increasing level of education appears to be the key to garnering support for transportation funding.
Voting for Transport: Analyzing Voter Support for Local Option Sales Taxes for Transportation
Anne Brown, Univeristy of OregonShow Abstract View Presentation
Jaimee Lederman, University of California, Los Angeles
Brian Taylor, University of California, Los Angeles
Martin Wachs, University of California, Los Angeles
Local and regional governments in the U.S. rely increasingly on local option sales taxes (LOSTs) to fund transportation capital investments and operations. Despite the rising reliance on LOST revenues for transportation, most research on the factors that influence voter support for LOSTs consists of case studies. This article presents a more comprehensive, multi-jurisdictional analysis. Data from 76 LOST measures put on county ballots between 1976 and 2016 in California were used to examine factors associated with voter support of LOSTs. Regression models were estimated and companion case studies conducted to examine a broad spectrum of potential explanatory variables ranging from macroeconomic and political context, to voter characteristics, to the spatial distribution of proposed projects. Findings reveal that modal funding splits are the primary predictors of voter support at the county level, while LOSTs that raise taxes—as opposed to extending or renewing existing taxes—are less popular with voters. Countywide support for a measure, however, obscures sharp variations in where and who supports LOST measures at a local level. At the local level, political party affiliation is the strongest predictor of voter support for LOSTs and voters living adjacent to proposed projects tend to be more supportive of LOSTs. Overall, findings suggest that people largely vote in their self-interest (and for nearby projects), favor the taxation status quo, and are influenced by party affiliation. If LOSTs grow increasingly commonplace, the configuration, scale, and operation of transportation systems may be increasingly explained by patterns of voter behavior.
Quantifying the Potential Impact of Autonomous Vehicle Adoption on Government Finances
Jacob Terry, University of WaterlooShow Abstract View Presentation
Chris Bachmann, University of Waterloo
There is some understanding that autonomous vehicles will disrupt public sector policies and the existing transportation industry, but this disruption is often loosely defined and tends to ignore how it would affect governments financially. The primary objective of this paper is to quantify the short-term impact of introducing autonomous vehicles on government finances. The analysis focuses on eight Canadian governments, encompassing four government tiers. Public discourse and academic literature are used to generate nine predicted changes (forecast variables) in future adoption scenarios. Using the predicted rate of autonomous vehicle adoption, the remaining variables are converted into financial changes by combining them with government financial records, infrastructure inventory datasets, and project cost estimates. The results suggest that while revenue impacts are fairly minimal, and mostly impact Canadian provinces, the cost of implementing the expected vehicle-to-infrastructure communication upgrades could be expensive for governments with smaller populations, especially municipalities. The revenue analysis indicates the biggest shift is likely to be a loss in gas tax, which affects federal and provincial revenues, yet this share is relatively small compared to the size of these governments’ budgets. The expense analysis suggests that although provinces have extensive road networks, the cost of upgrading all of their highways may not be unreasonable compared to their yearly revenue intake. On the other hand, municipalities would require substantial new funds to be able to make the same upgrades.
Estimating the Benefits of Automated Commercial Vehicle Enforcement
Grayson L Forlines, University of KentuckyShow Abstract View Presentation
Andrew Martin, Kentucky Transportation Cabinet
Valerie J Keathley, Kentucky Transportation Center
Jerry Kissick, Kentucky Transportation Center
Jennifer Walton, Kentucky Transportation Cabinet
Automated enforcement of commercial vehicle regulations is one potential method through which states can generate revenue and improve safety compliance by more efficiently directing the attention of law enforcement and state DOT officials to non-compliant carriers and identifying carriers who may be evading taxes. This paper estimates the potential benefits of remote enforcement of weight-distance tax regulations using data from camera-equipped Kentucky Automated Truck Screening (KATS) systems and PrePass weigh stations in Kentucky and links these data sources with administrative tax returns and Kentucky State Police citation data. We estimate that remote enforcement and identification of tax evaders could generate up to $10.4 million annually in revenue. Implementation of KATS weigh stations increases monthly impounds by approximately $5,000 per station, or about 160 percent. Overall, our results indicate that remote enforcement can assist state DOTs and law enforcement agencies targeting non-compliant carriers and may be an effective tax enforcement tool for states.