(lead (Pb), CO, CO2 and particulates such as PM10, PM2.5) and specific health variables (incidence of bronchitis, hospital admissions, emergency room visits etc.). The specific parameters of the dose function for air pollution have been reasonably well studied (for example, Mayeres et al (1996), WHO (1999), Ostro et al (2004), Pope et al (1995, 2002 and 2009), as well as the EU project ExternE). The final estimate of the social cost of pollution would be a product of the DALY and average GDP per capita (for a given period).<sup>2</sup>

# **Congestion**

There is also a large literature on congestion. Recent studies include Roobuste et al (2001), Mizutani et al (2011) with their common focus on estimating the social costs of traffic congestion. Measuring these costs is often done in in three steps. The first is to estimate the daily time lost due to traffic congestion. Time loss is specified as a function of traffic volume and road length and speed. The second is to calculate the annual time loss – or opportunity cost - due to traffic congestion. Finally, the monetary value of traffic congestion is calculated. Time loss caused by congestion relies on a measure of the value of time. For example, detailed studies have calculated the value of time for each vehicle type, as vehicle types serve as proxies for different groups of people and hence different opportunity costs (see INFRAS/IWW 2004). Additional costs of vehicular use can include accidents and noise. Again, for simplicity, studies tend to rely on unit costs for specific modes of transport. In short, measurement of congestion costs boils down to: (a) loss of time and its value; and (b) excess energy use due to recurrent and nonrecurrent delays.

# **Intermodal choice**

Fuel subsidies can affect not only aggregate demand but can also have implications for the modal mix, often with complex feedbacks. For example, Forkenbrock (1999, 2001) has estimated the external costs of intercity truck freight and railway transportation looking at pollution, traffic accidents and noise, as well as climate change.<sup>3</sup> Another recent study done for Barcelona, finds that the external costs of cars and motorcycles are 9 euro cents per km trip; almost seven times larger than the external costs of public transport, estimated at 1.3 euro cents per km trip. Although that study does not estimate the indirect cost of freight (railway vs. road), the same logic could be applied in calculating those numbers as well (Robuste _et al.,_ 2001).

A significant proportion of the literature is devoted to studying the determinants of modal choice (mainly for passenger transport). Among the main factors are socio-demographic commonly measured by age, gender, occupation, education, income, household composition and car availability (De Witt _et al._ , 2013). The most robust relationship is between income and car ownership. More rudimentary models only consider income as the only determinant of car ownership (Schaefer, 2000, for instance etc.). Similarly, a paper on Jordan (Al-Ghandor _et al._ ,

> 2 This seems to be the dominant method. See, for instance, Doumani (2011) in the case of Cairo, Mizutani _et al._ (2011) in the case of Japan. Monzon and Guerrero (2004) for the case of Madrid use a simpler method of valuing the cost of pollution as the sum of deaths due to pollution (times GDP per capita) and total excess hospital costs due to increased hospital admissions as a result of increased pollution.

> 3 The unit costs for air pollution, climate change and noise are all taken from INFRAS/IWW study (1994) and its subsequent updates.

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