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Complementing distance based charges with discounted registration fees in the reform of road user charges: the impact for motorists and government revenue

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Abstract

The call for a congestion charge is getting louder and more frequent in many countries as major metropolitan areas experience increasing levels of road congestion. This is often accompanied by a recognition that governments need to find new sources of revenue to maintain existing road networks and to invest in new transport infrastructure. Although reform of road pricing is almost certain to occur at some time in the future in a number of countries, a key challenge is in selling the idea to the community of road users as well as a whole raft of interest groups that influence the views of society and politicians. Simply announcing a need for a congestion charge (often misleadingly called a tax) does little to progress the reform agenda. What is required is a carefully structured demonstration of what might be done to progressively introduce adjustments in road user charges that are seen as reducing the costs to motorists while ensuring no loss of revenue to government. In this paper we show, in the context of Sydney (Australia), that this can be achieved by the reform of registration fees in the presence of a distance-based charging regime that can deliver financial gains to motorists, with prospects of revenue growth to the State Treasury.

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Notes

  1. Politicians in countries we are familiar with are heavily influenced by the flow of revenues to government, and Treasuries frequently remind their Minister about this. So from a political perspective, this is paramount.

  2. We also investigated all day distance-based charging, and while there may be some merits for this, including the view that the perception of an all day charge might look better as it is less at (3) cents per km, on balance we believe that it will be more difficult to sell this as the first step, and so we have focussed on peak period only distance-based charging.

  3. The appeal of a registration fee reduction is that it is transparent and more clearly linked to the reform of road pricing, in a way that makes it easier to gain buy into a road pricing reform package. A 50 % reduction in the registration fee is likely to be perceived much more as a good deal compared to the same amount being sold as a concession on income tax which will amount to a very small percentage. Prospect theory highlights this through perceptual conditioning.

  4. Some individuals may be (slightly) worse off financially even though most will be better off. Some form of a compensation package may have merit in such circumstances, with monies coming from the additional revenue gain beyond the revenue neutral outcome for Treasury. See also Levinson (2010).

  5. Based on data from the Sydney annual Household Travel Survey and http://www.rta.nsw.gov.au/publicationsstatisticsforms/downloads/travelspeeds_sydney_metro_area.html. During school holidays, traffic lightens by about 7–10 % outside school drop off hours, yet the influence that this has on traffic flow is immense. (See http://www.privatefleet.com.au/congestion/). The National Road and Motorists Association (NRMA) of Australia uses a rule of thumb that when traffic on congested roads falls by 5 %, speeds increase about 50 % (though this might only mean an average speed increase from 20 to 30 km/h). See http://smh.drive.com.au/roads-and-traffic/how-do-you-spell-the-end-of-the-school-holidays-gridlock-20120715-224ag.html. We calculated a 4.77 % drop in traffic volumes during school holidays in Sydney in 2005 on all the major arterial roads, freeways and tollroads (sourced from http://www.rta.nsw.gov.au/trafficinformation/downloads/aadtdata_dl1.html).

  6. The HTS consists of a face-to-face interview survey carried out every day from July to June of each financial year. This collection method ensures high data quality and maximises response rates. A simple travel diary is used by each householder to record the details of all travel undertaken for their nominated 24-h period. An interviewer then interviews each householder to collect the details of each trip. The interviewer records the mode of travel, trip purpose, start and end location, and time of departure and arrival. Vehicle occupancy, toll roads used and parking are recorded for private vehicle trips and fare type and cost for public transport trips. The HTS sampling method was designed for BTS by the Statistical Consultancy section of the Australian Bureau of Statistics (ABS) such that the relative standard error (RSE) decreases and the statistical reliability increases as more waves of data are pooled.

  7. We have data at the postcode level which is at a greater level of spatial disaggregation; and while it is useful for studying sources of systematic variation that influence total kilometres travelled per driver, there are sample reliability concerns for the analysis undertaken herein. We use SSDs, but undertake some additional scenario analysis to assess the range of annual kilometres of drivers from each SSD.

  8. There may be implications for residents of Gosford–Wyong who commute to the other Sydney SSDs; however this can, in future analysis, be included if required.

  9. It is often suggested that the same outcome for motorists can be achieved by simply reducing the registration fee, and increasing fuel taxes. We do not support this view, given that fuel excise is a sum per litre of fuel that is essentially independent of the specific kilometres of travel. The idea of specific kilometres (and its link to locations and times of the day) is focussed on relating travel to sources and magnitudes of externalities such as traffic congestion and emissions (Hensher and Bliemer 2012), and it has been well established that energy based taxes fail to deal adequately with traffic congestion problems (Greene 2011). We do, however, acknowledge that there is a link between variations in fuel consumed per kilometre and specific kilometres, but not enough to influence the evidence presented in this paper.

  10. We recognise that these elasticities are drawn from a study that focussed on fuel price changes, and that we are using these estimates in the absence of elasticities that are specific to a DBC or a registration fee. However we would suggest that the range reported and assessed is a good starting position until we have evidence for specific costs.

  11. In Sydney, all tolled roads are cashless with electronic tags (ETAGS). ETAGS tend to make payment seamless and change the perception of toll payments since the driver is not having to be reminded in the same way as having to find cash and stop. This tends to reduce the price sensitivity and brings it closer to the fuel cost response.

  12. There is no account taken for changes in travel time.

  13. The peak is defined as 6.31–9.30 am and 3.01–6 pm Monday–Friday.

  14. When we introduced an all day DBC, we would also get a change in off-peak kilometres, but that scenario is not considered in this paper.

  15. We recognise that this will likely be smaller when trips moving to off-peak periods are considered. It is of course true, that if motorists have similar total outlays before and after but travel less km, then the average cost per km travelled must increase. This means, as a referee has pointed out, that the decrease in costs to motorists is essentially a function of the decrease in kilometres driven. When taking account of fuel costs, if the peak kilometres all move to the off peak then the cost outcome is more or less unchanged (noting marginally lower fuel costs under less congested condition in the off peak). We have not introduced the possibility of some kilometres being moved to the off peak or switching to public transport, and nor have we accounted for the public transport fare or any possible loss of value associated with trips eliminated.

  16. This will need very careful consideration. It should be fair as well. If high peak km drivers get a lot of compensation, they pay much less per km than people that drive below average kilometres. So this would more or less mean that the first km are charged at a higher rate, while the rate diminishes. Does this have the desired effect? In the end, high peak km drivers may have less and less incentive to decrease their kilometres driven.

  17. Based on the expected volume of installations.

  18. It is important to note that we are focussing on the Sydney metropolitan area as if it were a closed system. There will be a need to consider the entire state of NSW, and to recognise that the DBC may be lower if it is defined to capture all externalities as well as cost the road damage. Since congestion is not an issue in regional and rural NSW, a lower DBC may have to be considered. If, in addition, government would want a common registration fee structure throughout the State, then we would have to recalculate the financial implications on Treasury of a lower DBC for rural and regional residents. Visitors to specific locations in NSW would also be subject to the pricing reforms, with the same payment paths open to them that are currently offered on tollroads in Sydney (i.e., a phone number to call to pay within 24 h or acquire an ETAG and open an account).

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Acknowledgments

This study is supported by the Australian Research Council Discovery Program Grant DP110100454 titled “Assessment of the commuter’s willingness to pay a congestion charge under alternative pricing regimes and revenue disbursement plans”. We are indebted to the NSW Bureau of Transport Statistics (BTS) for providing the data required to undertake the empirical calculations. We thank Tim Raimond, Annette Hay and Charlie Lin of BTS for all their support. Richard Ellison of ITLS assisted in developing some of the macros for the scenario analysis. Discussions with Michiel Bliemer, as well as his detailed comments on earlier drafts, are appreciated as are suggestions by Martin Richards and three referees.

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Hensher, D.A., Mulley, C. Complementing distance based charges with discounted registration fees in the reform of road user charges: the impact for motorists and government revenue. Transportation 41, 697–715 (2014). https://doi.org/10.1007/s11116-013-9473-6

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