Academic journal article Economic Inquiry

Do Cell Phone Bans Change Driver Behavior?

Academic journal article Economic Inquiry

Do Cell Phone Bans Change Driver Behavior?

Article excerpt


In recent years, there has been increasing concern over distracted driving due to cell phone use. This stems from the substantial recent increase in cell phone usage while driving, as well as a body of research and official statistics suggesting that this behavior may lead to distraction and traffic accidents. One survey reports that over 60% of drivers regularly send text messages while driving, and that 66% of drivers report answering calls while driving (Tison, Chaudhary, and Cosgrove 2011). A growing body of research including naturalistic studies and studies of simulated driving tasks provides evidence that cell phone usage does affect driver behavior by, for example, slowing drivers' reaction time or taking drivers' eyes away from the roadway more often (Hosking, Young, and Regan 2009; Just, Keller, and Cynkar 2008; Olson et al. 2009). While it is difficult to know for sure whether and how much driver cell phone use increases accidents and casualties, official estimates from the National

Highway Traffic Safety Administration (2009) are that 995 people lost their lives in motor vehicle crashes in the United States in 2009 due to the use of cell phones while driving.

In response, states have started to pass cell phone bans--texting bans and handheld bans--that prohibit drivers from using cell phones behind the wheel. Texting bans prohibit drivers from sending or reading text messages on cell phones; handheld bans prohibit all drivers from engaging in phone calls, either talking or listening, on handheld cell phones when operating motor vehicles. These bans impose significant penalties for violations, including fines (ranging from $20 to $500 in adopting states), license suspension, and even jail time. Therefore, by raising the expected cost of using cell phones while driving, one might expect the bans to reduce traffic accidents by reducing drivers' cell phone use.

Most of the existing literature consists of single-state studies that examine the impact of cell phone bans in early adopting states. Handheld bans have been shown to induce drivers to use cell phones less often in Connecticut (Cosgrove, Chaudhary, and Roberts 2010), New York (McCartt, Braver, and Geary 2003; McCartt and Geary 2004), and Washington, DC (McCartt and Hellinga 2007; McCartt, Hellinga, and Geary 2006). In addition, several studies find evidence that cell phone bans reduce accidents in New York (Jacobson et al. 2012; Nikolaev et al. 2010; Sampaio 2010). Two studies from the Highway Loss Data Institute (2009, 2010) evaluate the ban effects on collision claim frequencies: the 2009 study finds handheld bans increase collision claim frequencies in Connecticut and New York but not in California and the District of Columbia; the 2010 report finds that texting bans increase collision claim frequencies in California, Louisiana, and Minnesota, but not in Washington.

However, a lingering concern with single-state studies is the reliability of statistical inference. First, while cluster-robust standard errors are reliable when the number of clusters is large, they are not when there are only a few clusters (Cameron, Gelbach, and Miller 2008), which applies to single-state studies that typically use a few neighboring states as control groups. (1) Secondly, some single-state studies do not cluster standard errors at the recommended (higher) state level to account for possible within-state cross-county correlation when using county-level data, as suggested by Cameron and Miller (forthcoming). Moreover, some other studies do not cluster to account for within-state correlation at all (Bertrand, Duflo, and Mullainathan 2004), which has been pointed out by Abouk and Adams (2013).

By adopting a multistate design and addressing the inference concerns that single-state studies have, recent studies published in economic journals show that cell phone bans have no meaningful effect on traffic accidents. …

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