Show Me The Way To Go Home: An Empirical Investigation of Ride Sharing and Alcohol Related Motor Vehicle Homicide
Brad N Greenwood Sunil Wattal
Fox School of Business
Temple University
Abstract
In this work, we investigate how the entry of the driving service Uber influences the rate of alcohol related motor vehicle homicides. While significant debate has surrounded the entry of driving services like Uber and Lyft, limited rigorous empirical work has been devoted to uncovering the social benefits of such services (or the mechanism which drives these benefits). Using a difference in difference approach to exploit a natural experiment, the entry of Uber into markets in California between 2009 and 2013, findings suggest a significant drop in the rate of homicides during that time. Furthermore, results suggest that not all services offered by Uber have the same effect, insofar as the effect for the Uber Black car service is intermittent and manifests only in selective locations. These results underscore the coupling of increased availability with cost savings which are necessary to exploit the public welfare gains offered by the sharing economy. Practical and theoretical implications are discussed within.
Key Words: Uber, drunk driving, vehicular homicide, difference in difference, natural experiment, platforms
Introduction
The introduction of ridesharing platforms such as Uber and Lyft has sparked a host of policy debates over the last half decade. Detractors of such programs not only argue that the entry of these firms puts the public at significant risk through their limited liability corporate structure[1], but that patrons are equally at risk[2] and these firms upset the delicate balance of service providers[3]. Countervailing these perceptions, both scholars and policy makers have argued that such services resolve market failures by providing customers with a much needed service that circumnavigates the bureaucratic processes of licensed livery (Rempel 2014). However, limited empirical evidence exists to establish the social benefits (or lack thereof) of these platforms. To the extent that Uber has entered more than 53 countries and 200 cities worldwide, and many are debating legislation to allow or bar these platforms, and a robust estimate of any social benefits that these services provide could factor heavily in the legislative debates.
One social benefit consistently associated with these platforms, and presently being debated in the media, is the potential for reducing the instances of drunk driving (Badger 2014). As existing regulatory structures for traditional vehicle for hire services, viz. taxicabs, are designed to retard the number of licensed vehicles on the road in order to manufacture excess demand (Sternberg 1996), the absence of a sufficient number of taxis may result in citizens operating motor vehicles under the influence of alcohol (Grove 2013). Inasmuch as the result of these public welfare losses are often born by taxpayers, such as the cost of prosecuting and incarcerating individuals convicted of DUI, the effective management of the number of and type of vehicle for hire services poses a significant challenge for policy makers.
Preliminary analysis conducted by Uber and several industry analysts suggest that introduction of Uber and other ride sharing services has a negative influence on DUI arrests[4]. However, these studies have been questioned on several grounds: including involvement of Uber in the data analysis, methodological rigor (i.e. single city estimations), and the presence of confounding factors such as changes in city’s population, bar scene, and tougher enforcement.
Moreover, a limited understanding of the mechanisms by which such services influence the rate of DUIs exists. On one hand, it is plausible that the decrease in DUI is simply the result of availability of vehicles for hire and that patrons are willing to pay a price premium for such services. Insofar as it is often difficult to hire a taxi, based on time, location, or even the race of the patron (Meeks 2010), it is plausible that the presence of the platform mitigates these market inefficiencies by soliciting the driver electronically, thereby significantly reducing search costs (Parker and Van Alstyne 2005) and creating excess utility for the consumer. On the other hand, it is equally plausible that the effect is a result of both availability and cost. Drawing from rational choice theory (Clarke and Cornish 1985, Cornish and Clarke 2014) it is conceivable that individuals who make the decision to drive under the influence do so based on the costs associated with conviction, the cost of searching for and hiring a taxi, and the probability of being stopped by the police and/or striking another driver. This broad question: what is the impact of Uber’s introduction on alcohol related motor vehicle homicides in the local area and by what mechanisms, forms the core of the research investigated in this paper.
Empirically, we exploit a natural experiment, the introduction of the ride sharing service Uber into cities in the State of California between 2009 and 2014, to investigate the effect. Leveraging this econometric setup offers us several advantages. First, to the extent that the entrance of Uber is staggered temporally and geographically, we execute a difference in difference estimation to establish the effect. Second, Uber offers multiple services in each of the treated areas with varying price points (note that these services also enter at varying times and orders). On one hand, UberBlack, a town car service, offers transportation with a significant markup over taxicabs (~20% - ~30% price premium). On the other, the UberX service is a personalized driving service which offers significant discounts over taxis (~20% - ~30% price reductions). To the degree that each of these services identifies a different mechanism being at play (availability v. availability and price point), we are able to cleanly identify the dominant mechanisms at play. We test these using hand collected data from the California Highway Patrol (CHP) safety and crash dataset and a custom webscraper which indicates when each service entered a geographic area in California.
Results indicate that while the entry of UberX strongly and negatively affects the number of motor vehicle homicides which occur in townships, limited evidence exists to support previous claims that this occurs with the Uber Black car service as well (indicating that prior claims about the efficacy of Uber may have been overstated (Badger 2014)). Further, results indicate that the time for such effects to manifest vary is significant (upwards of 9 – 15 months). These results are robust to a variety of estimations (e.g. OLS, Poisson, and Quasi-Maximum Likelihood count models) and operationalizations. Finally, findings suggest an absence of a heterogeneous pre-treatment homicide trend in treated locations, indicating that the primary assumptions of the difference in difference model are not violated (Angrist and Pischke 2008, Bertrand et al. 2002). Further, results suggest no effect of Uber when surge pricing is likely in effect, thereby underscoring the importance of cost considerations. Economically, results indicate that the entrance of Uber X results in a 3.6% – 5.6% decrease in the rate of motor vehicle homicides per quarter in the state of California. With more than 1000 deaths[5] occurring in California due to alcohol related car crashes every year, this represents a substantial opportunity to improve public welfare and save lives.
Theoretically, these results add interesting nuance to extant understanding of the sharing economy. To the extent that researchers have proposed the sharing economy as a viable alternative to established market firms in many markets, e.g. AirBnB (Edelman and Luca 2014) and crowdsourcing for the funding of nascent ventures (Burtch et al. 2013), our results highlight the importance of cost considerations in resolving such market failures. While it is plausible that increased access to services, regardless of cost, would allow consumers to price point differentiate based on their own preferences, a preference of consumers towards established services as costs increase is suggested. Further, to the degree that results underscore the beneficial effects of ridesharing services, inasmuch as considerable public welfare loss in the form of motor vehicle homicide is avoided, this work informs the ongoing policy debate regarding ridesharing services. Finally, this work contributes to the small, but growing stream, of literature discussing the societal impacts of electronic platforms (Burtch et al. 2013, Chan and Ghose 2014, Greenwood and Agarwal 2013). To the degree that platforms have been found both enhance and diminish public welfare, our work contributes by drawing a richer picture of the public welfare implications of platform introduction.
References
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[1] http://www.nytimes.com/2014/10/19/upshot/when-uber-lyft-and-airbnb-meet-the-real-world.html?abt=0002&abg=0
[2] http://www.sfexaminer.com/sanfrancisco/uber-driver-suspected-of-attacking-passenger-in-sf-raises-safety-concerns/Content?oid=2907619
[3] http://www.nytimes.com/2014/09/30/business/uniteds-deal-with-uber-raises-concerns.html
[4] http://blog.uber.com/duiratesdecline
[5] http://apps.dmv.ca.gov/about/profile/rd/r_d_report/Section_5/S5-243.pdf