The effects of road pricing on driver behavior and air pollution

Abstract

Exploiting the natural experiment created by an unanticipated court injunction, we evaluate driver responses to road pricing. We find evidence of intertemporal substitution toward unpriced times and spatial substitution toward unpriced roads. The effect on traffic volume varies with public transit availability. Net of these responses, Milan’s pricing policy reduces air pollution substantially, generating large welfare gains. In addition, we use long-run policy changes to estimate price elasticities.

Introduction

Growing air pollution, congestion, and accident externalities from vehicle traffic have produced increasing interest in policy remedies. Beijing and Mexico City bar vehicles from their roads on some days based on their license plate numbers (Davis, 2008, Viard and Fu, 2014, Wang et al., 2014). Many German cities have created Low Emissions Zones (Wolff, 2014), which prohibit dirtier vehicles within their borders. Stockholm, London, and Milan charge fees to enter congested downtown areas. In the US, the Department of Transportation is currently sponsoring a large number of road pricing experiments, including San Francisco’s Golden Gate Bridge, Interstate 95 near Miami, SR520 near Seattle, and Interstate 35W near Minneapolis (DeCorla-Souza, 2004, Xie, 2013). Economists have raised concerns over non-price policies because behavioral responses can be so large that net policy benefits may be zero, or even negative (Davis, 2008, Gallego et al., 2013). Theory suggests that road pricing might be more efficient (Vickrey, 1963, Arnott et al., 1993), but this prediction depends on driver responses. On which margins do drivers respond to road pricing, and how large are such responses?

Confounding factors typically make traffic policies difficult to evaluate. Drivers know the policy start date well in advance and may begin to adjust their behavior beforehand, which attenuates estimated effects. Municipalities typically increase public transit service at the same time they implement road pricing or a driving restriction. This makes it impossible to estimate the effect of the policy in isolation. For example, Eliasson et al. (2009) point out that Stockholm expanded bus service at the same time it implemented a congestion charge. Because the buses used for the expansion were older and dirtier, the reduction in emissions within the charge area was muted. Milan first implemented a congestion charge concurrent with, “traffic calming measures, new bus lanes, increased bus frequency, increases in parking restrictions and fees, and medium-term policies such as park-and-ride facilities and underground network extensions” (Rotaris et al., 2010).

To address these identification challenges, we exploit a natural experiment: in late July 2012, an Italian court unexpectedly suspended Milan’s road pricing policy, called “Area C.” The city reinstated pricing eight weeks later. Using unique traffic data at 15-min resolution, our study examines behavioral responses to Milan’s policy, which requires drivers entering the city center to pay €5 on weekdays 7:30AM–7:30PM. Drivers respond to pricing in two ways: (1) shifting trips to the unpriced period, just before 7:30AM or after 7:30PM; and (2) driving around the boundary of the priced area.

Net of these behavioral responses, we find the Area C policy reduces vehicle entries into the priced area by 14.5 percent and air pollution by 6 to 17 percent. The latter effect is large, particularly given that the priced region is just five percent of Milan’s land area and the city has an unusually clean vehicle fleet. Using a well-identified US estimate of willingness to pay from Bayer et al. (2009) and scaling for income in Milan, we calculate that this pollution reduction increases welfare by approximately $3 billion annually. Routes without public transit experience large traffic changes from pricing, while those with public transit experience much smaller changes. We provide evidence that this surprising result may arise from residential sorting: residents who live near public transit may strongly prefer public transit. In addition, we use changes in Milan’s pricing policy across the 2008–2011 and 2012 periods to estimate elasticities: city-center entries by charged vehicles decrease .3 percent in response to a one percent price increase.

This study contributes to the empirical literature on second-best road pricing policies (Small et al., 2005, Small and Verhoef, 2007, Xie, 2013). Closely related to our analysis are Olszewski and Xie (2005), which analyzes the cordon charge and expressway pricing in Singapore, Santos and Fraser, 2006, Santos, 2008 on the London cordon charge, and Eliasson et al. (2009) on the Stockholm cordon charge. These studies find cordon charges do reduce traffic within the priced area. Also related are Foreman, 2013, Small and Gomez-Ibanez, 1998, which find evidence of intertemporal substitution in response to time-varying tolls. Our work complements the theoretical literature on second-best road pricing (Lévy-Lambert, 1968, Marchand, 1968, Verhoef et al., 1996), particularly the literature on cordon charges (Mun et al., 2003, Verhoef, 2005). Finally, we contribute to the literature on environmental effects of traffic policies. Many such studies have found no evidence of air quality improvements (Transport for London, 2005, Transport for London, 2008, Invernizzi et al., 2011). Authors commonly attribute this to driver substitution behaviors or exploitation of policy loopholes (Davis, 2008, Gallego et al., 2013). In important work, Wolff (2014) finds that German Low Emissions Zones reduce the concentration of particles with a diameter of 10 microns or less (PM10) by approximately 9 percent; this study is particularly significant given efforts by European cities to meet stringent air quality standards.

Our study is unique in obtaining unconfounded causal estimates of behavioral responses to road pricing and net road pricing effectiveness. This is the first analysis to examine removal, rather than imposition, of a traffic policy. Other studies have used indirect measures of traffic (such as gasoline sales or vehicle registrations) or hourly vehicle counts, but to the best of our knowledge ours is the first to combine direct, high-resolution measures of traffic volume with air pollution data. Finally, our finding that the net effect of pricing varies with public transit availability is novel. It contributes to the literature on public transit and air quality (Friedman et al., 2001) and adds a new dimension to the literature on traffic policies.

The remainder of the paper proceeds as follows. Section 2 provides policy background and describes the natural experiment. Section 3 covers data, Section 4 describes our estimating equations, and Section 5 discusses results. Section 6 concludes.