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Chapter 4 | Congestion charging and community attitudes

that pay the congestion charge) tend to be the higher income earners. The public

transport users (possibly the lower income earners) would benefit from the extra

funding source for public transport (Hsu et al. 2004, p. 7).

c. California

Usage patterns on the 91 Express Lanes in California also indicate that higher income

earners are frequent users, although the pattern is slightly more complex, as outlined

by Sullivan:

Income correlates positively with use frequency; being female, middle-aged, and

highly educated also correlates with greater use. Nevertheless, many frequent users

are low income, and many high-income commuters are infrequent users or non-users

(Sullivan 2003, p. 40).

An important message from the research to date is that it may not be valid to assume

that a high value of time (as manifested in WTP tolls for a less congested trip) is

correlated with high income. As Verhoef and Small warned in the context of 91

Express Lanes (SR91) in California, ‘the correlation between value of time and income

is actually far from perfect’:

One of the most striking findings from actual experience on SR91 is that most people

who use the express lanes do so intermittently, and the mix of incomes using the

express and the free lanes on any given day overlaps considerably (Verhoef and Small

1999, p. 2).

This may reflect users’ desire for fast, congestion-free journeys at specific times and

for specific purposes. That is, optimal tolled lanes provide users with a choice where,

on occasion, they may be prepared to pay for faster travel times.

Conclusions on regressivity

Lee (2003) noted that ‘those travelling on urban highways at the peak period in the

peak direction are substantially more affluent than the population as a whole, and

those who choose to pay the toll are more affluent still’ (Lee 2003). From this, Lee

concluded that the distributional impact of congestion charging appears to be mildly

regressive, but not regressive enough to be a significant obstacle to introducing the

charges.

Lee went on to point out that the regressivity of raising revenue from congestion

charging needs to be compared to alternative forms of revenue-raising. Put another

way, even if congestion charging were regressive, this would need to be compared

to the alternate way of raising the revenue, such as ‘fuel excise taxes, sales taxes,

and local property taxes’. These taxes, Lee observed, are also mildly regressive under

typical conditions. Lee concludes that ‘congestion pricing is probably a progressive

policy from the standpoint of redistributional equity, and no worse than mildly

regressive’ (Transportation Research Board 2005, p. 50).

In summary, equity is a complex issue and to determine the distributional impact of

congestion charging would require case-by-case analysis.

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