Effects of a Driver Cellphone Ban on Overall, Handheld, and Hands-Free Cellphone Use While Driving: New Evidence from Canada.

HEALTH ECONOMICS Health Econ. 24: 1452–1467 (2015) Published online 11 September 2014 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/hec.3098

EFFECTS OF A DRIVER CELLPHONE BAN ON OVERALL, HANDHELD, AND HANDS-FREE CELLPHONE USE WHILE DRIVING: NEW EVIDENCE FROM CANADA CHRISTOPHER S. CARPENTERa,* and HAI V. NGUYENb a

b

Department of Economics, Vanderbilt University, Nashville, TN, USA Program in Health Services and Systems Research, Duke-NUS Graduate Medical School Singapore, Singapore

ABSTRACT We provide new evidence on the effects of increasingly common driver cellphone bans on self-reported overall, handheld, and hands-free cellphone use while driving by studying Ontario, Canada, which instituted a 3-month education campaign in November 2009 followed by a binding driver cellphone ban in February 2010. Using residents of Alberta as a control group in a difference-in-differences framework, we find visual and regression-based evidence that Ontario’s cellphone ban significantly reduced overall and handheld cellphone use. We also find that the policies significantly increased hands-free cellphone use. The reductions in overall and handheld use are driven exclusively by women, whereas the increases in hands-free use are much larger for men. Our results provide the first direct evidence that cellphone bans have the unintended effect of inducing substitution to hands-free devices. Copyright © 2014 John Wiley & Sons, Ltd. Received 9 May 2013; Revised 1 May 2014; Accepted 17 July 2014 KEY WORDS:

cellphone; ban; quasi-experiment

1. INTRODUCTION Over the past decade, several jurisdictions throughout the United States, Canada, and elsewhere have adopted bans on handheld cellphone use while driving, and several others are contemplating similar legislation. These policies were spurred in part by several studies in psychology that documented increased traffic accident risks of cellphone use in particular and distracted driving in general. For example, Redelmeier and Tibshirani (1997) found that cellphone use while driving quadruples the risk of collision. Research on the effects of cellphone bans has generally found that they reduce handheld cellphone use while driving in the short term (see, for example, Foss et al., 2009 and Goodwin et al., 2012).1 Regarding accidents and fatalities, however, studies have found mixed results: An early study found that cellphone bans were effective at reducing fatalities (Kolko, 2009), whereas more recent studies found no relationship between driver cellphone bans and traffic accidents (Bhargava and Pathania, 2013; Cheng, 2014; Burger et al., 2011). Notably, North American bans on cellphone use while driving target only handheld cellphone devices and do not restrict hands-free cellphone use while driving. This is primarily because it is much more difficult for authorities to observe hands-free device use while driving, and thus enforcement would be challenging. Moreover, there is popular perception that hands-free cellphone use while driving is substantially safer than *Correspondence to: Christopher Carpenter, Department of Economics, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235-1819, USA. E-mail: [email protected] 1

We do not study here texting effects on driving behavior or the effects of public policies to ban texting while driving. For a recent study on this topic, see Abouk and Adams (2013).

Copyright © 2014 John Wiley & Sons, Ltd.

EFFECTS OF A CELLPHONE BAN ON HANDHELD AND HANDS-FREE CELLPHONE USE

1453

handheld cellphone use while driving: A 2011 survey of residents of Alberta, Canada, found that 68.4% agreed either somewhat or strongly that hands-free devices are safer to use while driving than handheld devices (Nurullah et al., 2013). But if hands-free cellphone use while driving is independently risky, then policymakers may be concerned if driver cellphone bans induce people to substitute from handheld cellphone use while driving to hands-free cellphone use while driving. To our knowledge, no previous study has studied the effects of driver cellphone bans on the use of hands-free cellphone devices while driving. We fill this gap in the literature by studying the effects of a driver cellphone ban adopted in Ontario, Canada that was implemented in two phases: a province-wide education and information campaign followed by a binding and fully enforced ban. Specifically, we study how Ontario’s policy affected reported use of cellphones while driving, and our unique contribution is that we separately observe (through respondent self-reports) both handheld and hands-free cellphone use while driving. We make use of large-scale survey data from the Canadian Community Health Surveys. To account for unobserved factors that might influence these behaviors, we use residents of Alberta—which did not adopt a ban until after our sample period—as a control group, and we show that outcomes in Alberta and Ontario trended very similarly prior to implementation of Ontario’s policy. To preview, we find in standard difference-in-differences models that Ontario’s ban on cellphone use while driving significantly reduced the likelihood of any cellphone use while driving by 4.5 percentage points, or about 8% relative to the pre-reform average of any cellphone use while driving in Ontario. We also estimate that the law significantly increased the likelihood an individual reports never or rarely using a handheld cellphone while driving by 5.2 percentage points, or about 7%. Both of these effects should serve to improve public health and safety. However, we find that both the education campaign and the binding cellphone ban also significantly increased the likelihood an individual reports hands-free cellphone use while driving either ‘sometimes’ or ‘often’ by 5.6 and 6 percentage points, respectively. Relative to pre-policy levels in Ontario, these are approximately 40% effects. Ordered probit models confirm that these effects are driven primarily by large increases in reporting never using a handheld cellphone while driving and large decreases in reporting never using a hands-free cellphone while driving. Overall, our results are the first to document important and direct substitution effects of increasingly common driver cellphone bans and may help provide context for interpreting the mixed results in prior research on the effects of cellphone bans on traffic accidents and fatalities. The paper proceeds as follows: Section 2 describes the institutional details behind Ontario’s cellphone ban and provides a literature review. Section 3 describes the data and empirical approach. Section 4 presents the main results, and Section 5 offers a discussion and concludes.

2. BACKGROUND AND LITERATURE REVIEW 2.1. Institutional background Bans on the use of cellphones while driving were first introduced in Canada in 2003 in the province of Newfoundland and Labrador and have since been adopted by all other provinces.2 Table I provides a timeline and description of the provincial bans in Canada which share a number of common features. First, drivers are forbidden to use handheld devices to talk, text, or email while behind the wheel or to use portable video games or DVD players.3 The use of hands-free units is, however, permitted. While legislators argued that hands-free 2 3

A handful of other countries and US states adopted similar policies in the late 1990s and early 2000s (e.g., Japan in 1999, New York State in 2001, and others). Abouk and Adams (2013) studied the effects of laws prohibiting text messaging while driving in the United States and found that these policies reduced fatal accidents, but only in the first few months after the ban. In the USA, bans on texting while driving were generally adopted separately from bans on cellphone use while driving. Our survey data do not ask individuals about texting while driving.


Health Econ. 24: 1452–1467 (2015) DOI: 10.1002/hec

1454

C. S. CARPENTER AND H. V. NGUYEN

Table I. Timeline of bans on cellphone use while driving across Canada Province

Date law in effect/tickets issued

Grace/education period

Newfoundland

April 2003

Nova Scotia

April 2008

19 December 2002 to 30 March 2003 n/a

Quebec Prince Edward Island Saskatchewan

July 2008 January 2010

1 April to 1 July 2008 n/a

January 2010

n/a

Ontario

February 2010

1 November 2009 to 30 January 2010

British Columbia Manitoba

February 2010

1–30 January 2010

$167

6 demerit points (and $1000) if causing injury or death due to distracted driving 3

July 2010

$ 200

None

New Brunswick Alberta

June 2011 September 2011

September 2009 to June 2010 n/a n/a

$172.50 $172

None None

Penalties

Demerit points

$45 to $180

4

$50 for first offense, $100 for second offense, $200 for third offense $115 to $154 $250 to $400 $280 (plus a victims’ surcharge of $60) $155 to $500

None

4 3 4

use is also dangerous, there is much less support for banning hands-free cellphone use.4 Second, the penalties for violating the policy are fines ranging from $45 to $500, depending on the province. A handful of provinces also add demerit points to a person’s driver’s license. Third, emergency phone calls are exempted. Fourth, several provinces—including Ontario—allow for a period of education before officially enforcing the laws. Ontario’s ban was adopted on 26 October 2009. A 3-month education period ran from 1 November 2009 to 30 January 2010, after which time, the ban was in full force. Fines range from $155 to $500, and there are generally no demerit points unless the driver was involved in distracted driving that causes death. Enforcement was strong: In the first month after the ban came into force, the Ontario Provincial Police gave 470 tickets to people caught violating the new distracted driving law. In addition, 468 warnings were issued on a discretionary basis. Through February 2011, around 46 000 tickets have been issued to drivers who have been caught violating Ontario’s cellphone ban (CBC News, 2011). 2.2. Literature review: handheld cellphone use, hands-free cellphone use, and driving ability A very large body of research has documented that cellphone use while driving impairs driving ability and increases crash risk. These studies have been carried out by psychologists, public health scholars, and medical researchers and generally take one of three forms: crash-based studies, controlled laboratory studies, and physical observation studies (WHO, 2011). The results from this body of work clearly demonstrate that cellphone use while driving impairs driving ability and increases crash risk. One of the most heavily cited studies is the study of Redelmeier and Tibshirani (1997) who use a case-crossover design to study a sample of Ontario, Canada, residents involved in traffic collisions with property damage. The research team matched cellphone records to the timing of the collision on the accident day and on the days surrounding the collision. They found that cellphone use was associated with a fourfold increase in crash risk. 4

For example, an August 2001 poll of residents of Newfoundland and Labrador revealed that 55% of respondents felt any cellphone use while driving should be banned, whereas 39% felt that hands-free cellphone use is acceptable (Government of Newfoundland and Labrador, 2002).




1455

Studies examining specific driving deficits that lead to the increased crash risk generally take place in the psychology literature and use controlled laboratory experiments with computer-based driving simulators and eye-tracking software to examine the effects of various distractions (including cellphones, radios, and in-car conversations) on outcomes related to driving ability. Physical observation studies are also common and use a sample of drivers, who have consented to have their behaviors studied, and introduce various hazards into a more naturalistic driving setting. This literature is far too large to review here, but we note that cellphone use while driving has been shown in these studies to be associated with poor speed maintenance, increased mental workload, failure to detect traffic signals, and increased braking response time in response to road hazards (Strayer and Johnston, 2001; Alm and Nilsson, 1995; Charlton, 2009, and Consiglio et al., 2003). There is substantially less consensus on the question of whether handheld cellphone use while driving is differentially risky compared with hands-free cellphone use while driving. On the one hand, handheld cellphone use requires more manual manipulation than hands-free cellphone use. On the other hand, phone conversations on both devices require cognitive attention, and if cognitive deficits are the primary contributors to crashes, then one might not see the differences between the two modes. Moreover, if people systematically overcompensate with riskier driving in response to the perceived safety of hands-free cellphone use, one might observe that handheld cellphone use while driving is actually safer than hands-free cellphone use while driving. For the few studies that have separately examined hands-free cellphone use from handheld cellphone use, the results are mixed. Redelmeier and Tibshirani’s (1997) crash-based study, for example, found no statistically significant difference in crash risk between phone units that allowed the hands to be free compared with handheld units, and the actual study estimates suggested heightened risk for hands-free technology compared with handheld cellphone use. Moreover, a meta-analysis of studies in the psychology literature (Caird et al., 2008) and a review of the transportation safety literature (Ishigami and Klein, 2009) both indicate that hands-free cellphone use while driving is as dangerous as handheld cellphone use while driving. Other research, however, finds that hands-free cellphone use while driving is less risky than handheld cellphone use while driving. Olson et al. (2009) studied outcomes among drivers of commercial vehicles and found that reaching for or dialing a cellphone was associated with heightened risk of a safety-critical event, but talking on a cellphone was not. Moreover, they found that using a hands-free device had a significant protective effect at reducing such risks. A recent study of the National Highway Traffic Safety Administration (NHTSA) using non-commercial drivers who consented to naturalistic observations found that talking on a cellphone—regardless of whether it was handheld or hands-free—was not associated with increased risk of a safety-critical event (Fitch et al., 2013). Like the Olson et al. (2009) findings, however, they found that visual–manual subtasks associated with cellphone use (such as locating, dialing, or pushing a button to begin/end use) significantly increased the risk of a safety-critical event. Fitch et al. (2013) acknowledged that hands-free devices generally do require some manual manipulation for tasks such as device pairing, although perhaps less than that for handheld cellphone devices. A summary of the existing evidence led the World Health Organization to write in 2011 that ‘evidence suggests that hands-free phones are not safer to use than handheld phones in terms of driving performance’ (WHO, 2011), whereas NHTSA’s current policy statement on distracted driving notes that ‘handheld devices may be slightly worse [with respect to crash-risk], but hands-free devices are not risk-free’ (NHTSA, 2014). Thus, more research is needed to address the critical question of relative riskiness of handheld versus handsfree cellphone use while driving. 2.3. Literature review: effects of bans on cellphone use while driving Several economics studies have used variation in the adoption of driver cellphone bans in the United States to examine effects on traffic accidents and fatalities. Unlike most of the psychology and public health studies described earlier, these studies generally analyze existing data on crashes and fatalities and use a treatment/ control strategy based on the timing of when various places adopted driver cellphone bans. Kolko (2009) finds that early adopters of these laws in the United States saw reductions in fatalities in bad weather and wet road Copyright © 2014 John Wiley & Sons, Ltd.


1456


conditions after the laws took effect. Multiple recent studies, however, have found that these bans have little effect at reducing traffic accidents and fatalities. Bhargava and Pathania (2013) evaluate the effects of recent legislative bans on handheld cellphone use on fatal crashes using region-month panel data on fatal crashes in the United States from 1989 to 2007. They find no evidence that these bans significantly reduced fatal crashes, and this same basic null finding is corroborated by Cheng (2014). Burger et al. (2011) evaluate a July 2008 California ban on handheld cellphone use while driving on traffic accidents on freeways in the state. They employ high-frequency data and a regression discontinuity design (using date as the running variable and the ban enactment date as the discontinuity) to control for unobserved time-varying effects that could be correlated with the ban. They also find no evidence that the ban on handheld cellphone use led to a reduction in traffic accidents. One possible explanation for the null findings on cellphone bans and fatalities is that cellphone use while driving is accompanied by other behavior modifications (e.g., reduced speed, increased following distance, and heightened awareness by other drivers) that help compensate for the well-documented increased riskiness of cellphone use while driving. Additional analysis in Bhargava and Pathania (2013) is most consistent with this hypothesis: They use a regression discontinuity strategy to directly evaluate the effects of cellphone use on accident risk using the sharp change in the price of cellphone minutes during ‘nights and weekends’ in the early 2000s. Despite discontinuous changes in cellphone use at the relevant time of day when cellphone minutes became much cheaper, they find no associated discontinuity in crash risk at the same threshold. Other important hypotheses that could plausibly contribute to the finding of inconsistent effects of cellphone bans on accidents and fatalities are that (1) the policies do not significantly reduce handheld cellphone use while driving and/or (2) they induce individuals to switch from handheld cellphone use to hands-free cellphone use while driving, which may be independently risky (or at a minimum is unlikely to be completely risk-free, as reviewed earlier). As to the first hypothesis, some prior work has focused on how handheld cellphone use while driving responds to cellphone bans. Cheng (2014) uses national data on observed cellphone use and shows that the state cellphone bans in the USA significantly reduce handheld cellphone use. Several single-site studies in the public health literature also examine how cellphone bans affect cellphone use by using actual observations of drivers at intersections. These studies generally find that handheld cellphone use does, in fact, decline immediately after implementation of a ban (see, for example, Foss et al., 2009; Goodwin et al., 2012; McCartt and Geary, 2004; McCartt et al., 2003; McCartt et al., 2006). As to the second hypothesis, we are aware of no existing published studies on the possibility of substitution to hands-free cellphone use while driving. One government report relying on physical observations of drivers suggests the possibility of substitution to hands-free devices in London after penalties were increased for handheld cellphone use while driving (Narine et al., 2010). That report did not incorporate any control group, however, so any observed differences may have simply reflected secular trends. Studies that rely on physical observations of drivers suffer from some key limitations. First, and most importantly for our study, such studies cannot account for substitution toward hands-free cellphone use, because this is by construction not observable (or, at a minimum, it is far less observable than handheld cellphone use).5 Indeed, this is a key reason why the cellphone bans do not generally include restrictions on hands-free cellphone devices. Second, studies using physical observations can generally say very little about whether and to what extent compliance and/or substitution vary by observable demographic characteristics, which may be important for crafting effective policy. While trained observers are likely to correctly measure gender, other characteristics such as age, race/ethnicity, and (certainly) education are far less likely to be measured well. Third, physical observations of drivers generally take place at intersections, and driver behavior at intersections may be different from behavior elsewhere (e.g., on major highways). Finally, the public health studies are generally small in scale and thus have questionable representativeness and generalizability to other settings.

5

The Narine et al. (2010) study did not explain how they measured use of hands-free cellphone devices using physical observations.




1457

In summary, there is an incredibly large literature in psychology and public health clearly showing that cellphone use while driving impairs driving ability and heightens crash risk. There is less of a consensus as to whether hands-free technology reduces (or increases) such deficits, although there is broad agreement that hands-free devices are not completely risk-free. There is also now a substantial literature in economics and public health on the effects of driver cellphone bans on handheld cellphone use, accidents, and fatalities. That literature clearly finds near-term reductions in handheld cellphone use following ban adoption but does not consistently find reductions in traffic accidents or fatalities. Researchers have suggested substitution to hands-free devices as a possible explanation for the lack of fatality effects, and indeed survey evidence suggests individuals perceive hands-free use as much safer than handheld use. Ours is the first study to directly examine the effects of a driver cellphone ban on hands-free cellphone use while driving in a difference-in-differences framework.

3. DATA DESCRIPTION AND EMPIRICAL APPROACH We examine self-reported cellphone use while driving using data from the 2009 and 2010 Canadian Community Health Surveys (CCHS).6 The CCHS asked separate questions about handheld and hands-free cellphone use in topical modules in 2009 and 2010; our analysis uses data from Alberta and Ontario in each of these years.7 Individuals are asked the following question about their handheld cellphone use: ‘Excluding hands-free use, how often do you use a cellphone while you are driving a motor vehicle?’ Regarding hands-free cellphone use, individuals are asked: ‘How often do you use a hands-free when talking on the cellphone while you are driving a motor vehicle?’ The responses to these questions are coded as 1 (often), 2 (sometimes), 3 (rarely), and 4 (never). On the basis of these two questions, we construct three binary variables: ever uses cellphone while driving is equal to one if the individual reported ever using a cellphone while driving a motor vehicle, regardless of whether it was handheld or hands-free; never or rarely uses handheld is equal to one if the individual responded ‘never’ or ‘rarely’ to the question about how often she uses a handheld cellphone while driving (and zero otherwise); and often or sometimes uses hands-free is equal to one if the individual responded she ‘often’ or ‘sometimes’ uses a hands-free device for talking on a cellphone while driving (and zero otherwise). We also use the frequency responses directly in ordered probit models, described later. Our main difference-in-differences (DD) model uses data from residents of Alberta and Ontario from 2009 and 2010 and takes the following form: Y ipt ¼ α þ β1 X ipt þ β2 ðONTARIOEDUCATION PERIODÞpt þ β3 ðONTARIOBAN IN FULL FORCEÞpt þβ4 ðONTARIOÞp þ β5 M t þ εipt

(1)

where Yipt are the dichotomous outcomes for individual i in province p in month t described immediately. These models are estimated by ordinary least squares.8 For the categorical frequency of use outcomes, we estimate ordered probit models. X is a vector of individual demographic characteristics and includes an indicator for being male, age and its square, education (dummies for bachelor’s or more, some college, and high school, with less than high school degree as the excluded category), marital status (dummies for married and never married, with widowed/divorced/separated as the excluded category), an indicator for residing in an urban area, household size, immigrant status, number of children aged 0–5 years in the family, number of children aged

6

Canada does not maintain a fatal accident reporting system in the same way the United States does, so we cannot directly evaluate the effect of Ontario’s cellphone ban on traffic fatalities. 7 In the CCHS, provinces can choose which topical modules to administer; we focus on Ontario and Alberta, which both administered the topical module including the cellphone use questions in 2009 and 2010 (but not in 2011). Notably, earlier waves of the CCHS also included questions about cellphone use but did not distinguish between handheld and hands-free use. 8 Results using probit models for the dichotomous outcomes produced similar results. Copyright © 2014 John Wiley & Sons, Ltd.


1458


6–11 years in the family, and languages spoken (English, French, both English and French, with other languages as the excluded category). ONTARIO is an indicator variable equal to one for individuals in Ontario, the treatment province. This variable controls for all time invariant characteristics of the treatment province compared with the control province (Alberta). EDUCATION PERIOD is an indicator variable equal to one for observations in both provinces between 1 November 2009 and 31 January 2010.9 BAN IN FULL FORCE is an indicator variable equal to one for observations in both provinces from 1 February 2010 onward. M is a vector of month dummies (23-month dummies included) that account for secular changes or shocks in outcomes that are common to individuals in both the treatment and control provinces. The coefficients of interest are β2 and β3 on the interaction terms between the ONTARIO indicator and the EDUCATION PERIOD and BAN IN FULL FORCE indicators, respectively. These coefficients capture the relative effects of the cellphone education campaign and subsequent binding law on outcomes for residents of Ontario compared with the associated change in outcomes for people in Alberta where there was no such education policy or cellphone ban. The key identifying assumption in this simple DD model is that there were no other shocks to outcomes over this period for Ontario residents relative to Alberta residents coincident with the timing of the education period and fully enforced ban.10 Regressions are weighted to be population representative, and the main sample is all respondents aged 14 years and older with valid responses to the relevant cellphone use questions. An important challenge in our two-province setting with one treatment group is how to correctly describe the precision of our estimates in the presence of correlated errors. Unfortunately, we are not aware of a well-accepted way in the literature to deal with this problem in our particular setting. For example, we cannot implement the Cameron et al. (2008) wild bootstrap procedure because we have too few clusters, and the methods of Conley and Taber (2011) for inference with a small number of policy changes similarly require a large number of control groups. Instead, we adopt an approach in the spirit of Baker et al. (2008) who study a similar province-specific reform and cluster our standard errors at the province-month level. Clustering instead at the province level produced standard errors that were consistently an order of magnitude smaller than those clustered at the provincemonth level and are available upon request. When discussing statistical significance, we only refer to specific estimates in the context of the larger (more conservative) standard errors.

4. RESULTS 4.1. Descriptive statistics Table II presents descriptive statistics of the key demographic variables used in this analysis for the CCHS sample. We present demographic characteristics (e.g., age, race, education, and marital status), as well as the key cellphone use outcomes. There are substantial baseline differences in cellphone use while driving across the two provinces under study: 65% of Alberta residents report using a cellphone while driving, whereas only 49% of Ontario residents report using a cellphone while driving over the sample period. Ontario has a higher proportion of residents who report never using handheld cellphones while driving than Alberta (63% versus 40%), whereas the proportion of residents who report never using a hands-free cellphone device while driving is more comparable across the two provinces (72% in Ontario and 78% in Alberta). In terms of demographics, Ontario has a higher proportion of immigrants than Alberta (29% versus 18%). Other than this, these two samples are broadly similar in most observed characteristics, meaning that the observed characteristics in the CCHS data cannot account for the large baseline differences in behaviors relating to cellphone use while driving between the two provinces. 9

The confidential version of the CCHS provides us information on exact date of interview. We regressed the outcomes on the province specific trends using data for the pre-policy period and found no statistically significant difference between Ontario and Alberta in its pre-policy trends.

10



1459


Table II. Descriptive statistics, CCHS 2009–2010, 14+ Variable

Ontario: 2009–2010

Alberta: 2009–2010

Ever uses cellphone device while driving (handheld or hands-free) Never uses handheld cellphone device while driving Rarely uses handheld cellphone device while driving Sometimes uses handheld cellphone device while driving Often uses handheld cellphone device while driving Never uses hands-free cellphone device while driving Rarely uses hands-free cellphone device while driving Sometimes uses hands-free cellphone device while driving Often uses hands-free cellphone device while driving

0.488 (0.500) 0.633 (0.482) 0.196 (0.397) 0.108 (0.311) 0.062 (0.242) 0.720 (0.449) 0.077 (0.267) 0.075 (0.264) 0.127 (0.333)

0.648 (0.478) 0.402 (0.490) 0.283 (0.451) 0.196 (0.397) 0.119 (0.324) 0.778 (0.415) 0.076 (0.265) 0.065 (0.247) 0.08 (0.272)

Age Immigrant Household size Male Urban

45 (16.7) 0.294 (0.455) 3.01 (1.392) 0.523 (0.499) 0.829 (0.376)

43 (16.6) 0.177 (0.382) 2.922 (1.41) 0.533 (0.499) 0.877 (0.328)

Less than high school degree High school degree Some college Bachelor’s degree or more

0.117 (0.321) 0.17 (0.376) 0.079 (0.269) 0.634 (0.481)

0.132 (0.339) 0.177 (0.381) 0.090 (0.289) 0.601 (0.490)

Married Widowed/divorced/separated Never married

0.663 (0.472) 0.108 (0.311) 0.228 (0.419)

0.655 (0.475) 0.106 (0.308) 0.238 (0.426)

32 056

9555

N Author calculations from CCHS. Weighted means. Standard deviations in parentheses.

4.2. Graphical evidence In Figure 1 we show month-by-month trends in the proportion of individuals who report ever using a cellphone while driving. Several features are notable. First, as noted earlier, the proportion of individuals who report ever using a cellphone while driving is substantially lower in Ontario than in Alberta. Second, the trends in this outcome prior to the cellphone policy are roughly similar across the two provinces. Third, there is visual evidence of a decrease in the proportion of individuals in Ontario who report ever using a cellphone device while driving that appears toward the end of the education period and persists through the period the full ban is in effect. In Alberta, in contrast, the proportion of respondents who report ever using a cellphone while driving remains approximately stable over the sample period.

Figure 1. Trends in cellphone use while driving, outcome is ever uses cellphone while driving (handheld or hands-free), Ontario and Alberta, CCHS 2009–2010 Copyright © 2014 John Wiley & Sons, Ltd.


1460


Figures 2 and 3 present the corresponding graphs for the outcomes that separately reflect handheld cellphone use and hands-free cellphone use, respectively. Specifically, Figure 2 shows the proportion of residents in each province who report never or rarely using a handheld cellphone while driving, whereas Figure 3 shows the proportion of residents in each province who report sometimes or often using a hands-free cellphone while driving. Both figures reveal broadly the same patterns as indicated in Figure 1 and additionally suggest that Ontario’s driver cellphone ban induced reductions in handheld cellphone use while driving but also induced increases in hands-free cellphone use while driving. Notably, the level differences across the two provinces remain substantial for the outcome in Figure 2 (never or rarely using handheld cellphone while driving) but are much closer for the outcome in Figure 3 (sometimes or often using hands-free cellphone while driving). 4.3. Regression results We present the baseline difference-in-differences results in Table III for the three main dichotomous outcomes reflecting extensive margin effects: an indicator for ever using a handheld or hands-free cellphone while driving

.3

Feb2010

.2

Oct2009

10

Alberta

D ec

Ju n1 0

Ontario

09 D ec

Ju n0 9

.1 Ja n0 9

Proportion of often or sometimes using hands-free

Figure 2. Trends in handheld cellphone use while driving, outcome is never or rarely uses handheld cellphone while driving, Ontario and Alberta, CCHS 2009–2010

Figure 3. Trends in hands-free cellphone use while driving, outcome is often or sometimes uses hands-free cellphone while driving, Ontario and Alberta, CCHS 2009–2010 Copyright © 2014 John Wiley & Sons, Ltd.


1461


Table III. Effects of Ontario’s education campaign and cellphone ban on cellphone use while driving: extensive margin; regression-adjusted; DD models, OLS CCHS 14+, 2009–2010

Average of outcome in Ontario before the policy (January to October 2009) Regression-adjusted DD model ONTARIO * EDUCATION PERIOD ONTARIO * BAN IN FULL FORCE 2 Adjusted R N

(1)

(2)

(3)

Ever uses cellphone while driving (handheld or hands-free)

Never or rarely uses handheld cellphone while driving

Often or sometimes uses hands-free cellphone while driving

0.539

0.0378 (0.0411) *** 0.0453 (0.0129) 0.173 40 948

0.768

0.147

0.0269 (0.0301) *** 0.0522 (0.0165) 0.100 40 964

0.0561 (0.0097) *** 0.0597 (0.0137) 0.077 40 957

***

Each column shows the results from a separate DD linear probability model. All models include province and month fixed effects, as well as controls for age and its square, household size, sex (male; female is the excluded category); urban; education (less than high school, some college, college degree or more; less than high school is the excluded category), and marital status (married, never married; widowed/divorced/separated is the excluded category), immigrant status, number of children aged 0–5 years, number of children aged 6–11 years, language spoken (English, French, both English and French, other languages are the excluded category). Standard errors throughout are clustered at the province–month level and estimates are weighted. Significance levels *** ** * p < 0.01; p < 0.05; p < 0.1. are

(column 1); an indicator for never or rarely using a handheld cellphone while driving (column 2); and an indicator for often or sometimes using a hands-free cellphone device while driving (column 3). The top panel reports the average of the relevant outcomes for respondents in Ontario during the period January 2009 through October 2009 which was prior to implementation of Ontario’s education policy and official ban. In the middle panel, we report the coefficients on the relevant interaction terms (between ONTARIO and EDUCATION PERIOD and between ONTARIO and BAN IN FULL FORCE) for each outcome from the baseline difference-in-differences model. The models control for all the covariates described earlier including demographic characteristics and month fixed effects. Thus, the printed estimates are the difference-in-differences estimates of β2 and β3 in Eqn (1). The results in column 1 of Table III indicate that Ontario’s fully enforced cellphone ban significantly reduced the likelihood of ever using a cellphone while driving by about 4.5 percentage points relative to the associated change in Alberta. The estimate for the education period indicates a 3.8 percentage point reduction in any cellphone use while driving, but it is not statistically significant. Relative to the pre-reform prevalence of ever using a cellphone while driving of 54% in Ontario, the full ban effect represents an 8.3% reduction. Column 2 shows that Ontario’s fully enforced ban significantly increased the likelihood an individual reports never or rarely using a handheld cellphone while driving by 5.2 percentage points, or about a 6.8% effect. The estimated coefficient for the education period in column 2 is also positive but is not statistically significant.11 Finally, column 3 shows that Ontario’s education period and fully enforced ban both significantly increased the likelihood an individual reports sometimes or often using a hands-free cellphone while driving by 5.6 and 6 percentage points, respectively. These effects are very large relative to the pre-reform average for this outcome in Ontario: Only 14.7% of respondents in Ontario reported often or sometimes using a handsfree cellphone device while driving prior to the provincial reforms; thus, the results in column 3 of Table III represent effect sizes of about 38% and 40.6%, respectively.12 Taken together, the finding in column 1 of 11 12

Appendix I reports an expanded set of coefficient estimates from this model. It is worth noting that the large baseline differences in the cellphone use behaviors while driving between the two provinces mean that the estimated percentage point changes translate to different percent changes depending on what is used as the relevant base comparison. For example, since Ontario’s rate of cellphone use while driving in the pre-reform period was substantially lower than Alberta’s, the estimated 4.5 percentage point reduction in overall cellphone use while driving represents a smaller percent effect relative to the baseline rate in Alberta. Relatedly, because the baseline rate of hands-free cellphone devices while driving in Alberta is lower than in Ontario, the estimated percent increase due to Ontario’s policies—which is around 40% when measured against Ontario’s baseline rate—is even larger when measured as a proportion of Alberta’s baseline rate.



1462


Table III indicates that Ontario’s policies induced overall reductions in cellphone use while driving, but the findings in column 3 further indicate that there was substantial substitution from handheld to hands-free cellphone use while driving. Table IV presents results for each level of the categorical outcomes separately for handheld cellphone use while driving (column 1) and hands-free cellphone use while driving (column 2). These models are estimated using ordered probit, and we present predicted changes for each level of the outcome (often, sometimes, rarely, and never). The results for these intensive margin outcomes in Table IV show that Ontario’s education campaign and fully enforced cellphone ban reduced handheld cellphone use while driving primarily by significantly increasing the likelihood individuals report never using a handheld cellphone while driving. Column 1 of Table IV also shows monotonically increasing reductions in the likelihood of reporting often, sometimes, or rarely using a handheld cellphone while driving for both the education campaign and the fully enforced ban. In column 2 we show the predicted changes for each level of the outcome for hands-free cellphone use while driving. These results mirror those for handheld cellphone use while driving in column 1 and indicate that Ontario’s education period and fully enforced ban led to large and significant reductions in the likelihood of reporting never using a hands-free cellphone device while driving. The results in column 2 of Table IV also show that the majority of the estimated substitution effect on Table III is driven by a large increase in reporting the use of hands-free cellphone use while driving ‘often’ (compared with ‘sometimes’). This is consistent with fairly complete substitution. Finally, in Table V we estimate policy effects for different demographic groups for the extensive margin outcomes reported in Table III. Prior research does not provide a strong evidence base for what to expect regarding demographic differences in the effects of driver cellphone bans; the fatality literature has failed to find consistent effects and the research using physical observations of driver cellphone use behaviors has generally not reported differences by demographics, presumably because such characteristics are either difficult or impossible to physically observe (e.g., age and education). One exception is Cheng (2014) who

Table IV. Effects of Ontario’s education campaign and cellphone ban on handheld and hands-free cellphone use while driving: intensive margin; ordered probit models CCHS 14+, 2009–2010 (1)

(2)

Handheld cellphone use while driving

Hands-free cellphone use while driving

Regression-adjusted DD model Often = 4 ONTARIO * EDUCATION PERIOD ONTARIO * BAN IN FULL FORCE

0.031 (0.013) *** 0.054 (0.006)

**

0.029 (0.011) *** 0.042 (0.009)

Sometimes = 3 ONTARIO * EDUCATION PERIOD ONTARIO * BAN IN FULL FORCE

0.029 (0.012) *** 0.050 (0.005)

**

0.011 (0.004) *** 0.016 (0.004)

Rarely = 2 ONTARIO * EDUCATION PERIOD ONTARIO * BAN IN FULL FORCE

0.021 (0.008) *** 0.036 (0.004)

**

0.008 (0.003) *** 0.012 (0.003)

Never = 1 ONTARIO * EDUCATION PERIOD ONTARIO * BAN IN FULL FORCE

0.082 (0.033) *** 0.140 (0.014)

**

0.049 (0.018) *** 0.070 (0.015)

***

***

***

***

Each column shows the results from a separate ordered probit model. Four-point scale for ordered handheld and hands-free variables: 1 (never), 2 (rarely), 3 (sometimes), and 4 (often). All models include province and month fixed effects, as well as controls for: age and its square, household size, sex (male; female is the excluded category); urban; education (less than high school, some college, college degree or more; less than high school is the excluded category), and marital status (married, never married; widowed/divorced/separated is the excluded category), immigrant status, number of children aged 0–5 years, number of children aged 6–11 years, language spoken (English, French, both English and French, other languages are the excluded category). Standard errors throughout are clustered at the province*** ** * month level and estimates are weighted. Significance levels are p < 0.01; p < 0.05; p < 0.1. Copyright © 2014 John Wiley & Sons, Ltd.


1463


Table V. Effects of Ontario’s education campaign and cellphone ban on handheld and hands-free cellphone use while driving, by subgroup; regression-adjusted DD models OLS, CCHS 14+, 2009–2010 (1)

(2)

(3)

Ever uses cellphone while driving (handheld or hands-free)

Men Women 14–24 year olds 25–50 year olds 51+ year olds Urban Rural Some college or less Bachelor’s or more

(4)

(5)

Never or rarely uses handheld cellphone while driving

Coefficient on ONTARIO * EDUCATION PERIOD

Coefficient on ONTARIO * BAN IN FULL FORCE

Coefficient on ONTARIO * EDUCATION PERIOD


0.0212 (0.027) 0.0597 (0.0614) 0.034 (0.0753) * 0.0438 (0.0244) 0.0706 (0.0552) 0.0359 (0.0364) 0.0242 (0.0663) 0.0467 (0.048)

0.0138 (0.015) *** 0.0767 (0.0178) 0.051 (0.0341) *** 0.0677 (0.0195) 0.00197 (0.023) *** 0.0388 (0.0144) ** 0.0657 (0.0291) 0.0333 (0.0207)

0.00783 (0.0213) 0.0675 (0.0462) 0.0654 (0.0422) 0.0182 (0.0249) 0.0405 (0.0446) 0.0138 (0.0253) 0.0963 (0.076) *** 0.0605 (0.0205)

0.0223 (0.0216) *** 0.0837 (0.0208) 0.0464 (0.0467) *** 0.0770 (0.0264) 0.0169 (0.023) *** 0.0487 (0.0163) * 0.0645 (0.0328) * 0.0459 (0.0237)

***

0.103 (0.0373)

***

0.0596 (0.0171)

**

0.0905 (0.044)

***

0.0580 (0.019)

Sample size

(6)

Often or sometimes uses handsfree cellphone while driving

N


Coefficient on ONTARIO * EDUCATION PERIOD 0.0790 (0.0172) ** 0.0359 (0.0147) *** 0.0904 (0.0218) *** 0.0791 (0.0197) 0.0149 (0.0243) *** 0.0623 (0.00818) * 0.0445 (0.0231) *** 0.105 (0.0221)

0.0793 (0.0215) *** 0.0374 (0.0117) 0.0586 (0.0349) *** 0.0739 (0.0192) ** 0.0478 (0.021) *** 0.0632 (0.015) * 0.0557 (0.0308) *** 0.0591 (0.0187)

19 438

0.0159 (0.0163)

0.0504 (0.0177)

***

24 122

***

***

21 526 4808 16 223 19 933 30 840 10 124 16 842

See notes in Table III.

reports that the effects of driver cellphone bans on handheld cellphone use in the United States did not differ between youths and adults. In the context of the outcomes we study, there are several possible hypotheses regarding demographic differences.13 Regarding age, for example, it is possible that younger and middle-age drivers will be more comfortable with the hands-free technology than older drivers, so we may expect less substitution by the older respondents. We are also able to examine results by urban/rural residence location; it is possible that enforcement is lower in rural areas since in these areas people are more likely to be traveling on roads that are not heavily trafficked. If so, one might expect less direct compliance with (and thus less need for) substitution behavior in response to the driver cellphone ban in rural areas. Finally, we are able to examine differences by respondent education, and there are several possible hypotheses here. One is that education may proxy for income; given that hands-free technology requires a purchase in addition to the original cellphone device, this may give more latitude for substitution behavior among high-educated people. More educated people may also better be able to process the education campaign messages about the dangers of cellphone use while driving; this could induce larger reductions in their self-reported handheld cellphone use while driving, but it may also unintentionally induce larger increases in hands-free cellphone use while driving.14 Of course, it could also be that different groups of people are simply more law abiding than others. 13 14

As discussed later, it is also possible that reporting bias varies with observable characteristics, so these additional analyses should be interpreted with caution. This is a limitation of the outcomes we study. As discussed later, we were not able to obtain information on the content of the messages during the education period, and this may have important implications. For example, messages such as ‘Don’t use a handheld cellphone while driving’ may induce different behavioral responses than a message such as ‘Distracted driving is dangerous’.



1464


The format of Table V is as follows. Each row represents a different demographic group. Columns 1 and 2 report results for ever using a cellphone while driving (corresponding to column 1 of Table III); columns 3 and 4 report results for ‘never’ or ‘rarely’ using a handheld cellphone while driving (corresponding to column 2 of Table III), and columns 5 and 6 report results for ‘often’ or ‘sometimes’ using a hands-free cellphone device while driving (corresponding to column 3 of Table III). The odd-numbered columns report estimates for the education period whereas the even-numbered columns report estimates for the fully enforced ban. We begin by examining effects of the education policy and full ban by gender in the top two rows. We find that women exhibit much larger reductions in both overall and handheld cellphone use while driving in response to the policy interventions than men. Men, in contrast, exhibit larger substitution toward hands-free cellphone use while driving than women. Taken together, these patterns suggest that the policies were particularly effective at achieving their intended effects on women, while among men the policies mainly work by inducing substitution to hands-free cellphone devices while driving. These results are consistent with women being more law abiding than men. Regarding age, we find that the full-force ban had the largest effect at reducing overall and handheld cellphone use while driving among those aged 25–50 years; in fact, for adults aged 51 years and older, we find no significant effects of the fully enforced ban at reducing handheld cellphone use while driving. Regarding hands-free cellphone use while driving, we also find the largest evidence of substitution among those aged 25–50 years, although we find extremely large and statistically significant substitution to hands-free cellphone use while driving for the younger group during the education period. We also find statistically significant substitution toward hands-free use for the older group in the full-force ban period, which is inconsistent with the hypothesis that their hands-free use would be deterred by inexperience with the technology. The next two panels of Table V show the effects of the policies by rural/urban location. These results reveal relatively similar patterns of both reductions in handheld cellphone use while driving and increases in hands-free cellphone use while driving for both groups. Finally, the bottom two panels of Table V show results by education group. We estimate that Ontario’s policies significantly reduced overall cellphone use while driving only for the high education sample. In fact, we estimate a particularly large reduction (10.3 percentage points) in overall cellphone use while driving for higheducated people during the education period, although we also estimate a substantial reduction (6 percentage points) in overall cellphone use for this same sample during the fully enforced ban. This pattern is roughly replicated for handheld cellphone use while driving, although for this outcome we do estimate a marginally significant reduction for the less-educated sample during the full ban period as well. Surprisingly, we also estimate that the less-educated people are estimated to have significantly increased their handheld cellphone use while driving in the education period.15 For both groups we estimate significant substitution toward hands-free cellphone devices while driving during the full ban period, and for the less-educated sample we find that this effect is also observed to a very large extent during the education campaign. These patterns are consistent with propensity to abide with the law being positively related to education.

5. DISCUSSION AND CONCLUSION The results in Tables III–V suggest that Ontario’s cellphone ban significantly reduced both overall and handheld cellphone use while driving but also significantly increased hands-free cellphone use while driving. As such, our results confirm that increasingly common bans on handheld cellphone use while driving are having their intended effects at reducing the targeted behavior while at the same time we document the first evidence

15

Because we cannot empirically distinguish an education campaign effect from a pure announcement effect, this significant increase in the use of handheld cellphones while driving among the less-educated sample could be ‘real’ if people are responding to the known future illegality of the behavior by engaging in it in the very short run (e.g., a ‘last hurrah’ effect). Of course, this is the only sample for which we find such an effect, so it could also be a statistical anomaly.




1465

of unintended offsetting behavior in this context (Peltzman, 1975; Carpenter and Stehr, 2011). This last finding that individuals substitute toward hands-free cellphone devices in response to a ban on driver cellphone use may help explain the mixed results in the economics literature on the effects of handheld cellphone bans on traffic accidents and fatalities if in fact hands-free cellphone use while driving is independently risky, a question that has not yet been settled. Our findings are not without limitations. First, all of our outcomes are self-reported, and desirability bias is a concern. That is, even in the absence of any true behavior change, it could be that the increased stigma against cellphone use while driving reflected in Ontario’s policy may have changed people’s reports of their behavior without changing actual behavior. In this case, one would expect to observe reductions in cellphone use while driving as we do in Table III. Although we are unfortunately not aware of any public health research that has compared objective measures (e.g., physical observations) with self-reports of cellphone use while driving (and again this would be very difficult with use of hands-free devices, as they are by construction much more difficult to observe), we note that our results indicating offsetting behavior of increasing hands-free cellphone use while driving are broadly inconsistent with desirability bias. This is because while it is plausible that Ontario’s ban increased stigma against cellphone use while driving, it is much less plausible that the social attitudes underlying the ban concurrently encouraged hands-free use. Moreover, the large gender differences in the estimated effects on handheld and hands-free cellphone use while driving would also be difficult to rationalize with a simple desirability bias story, as it would have to be the case that women (but not men) systematically reported less handheld cellphone use while at the same time men (but less so women) systematically reported more hands-free cellphone use. We agree, however, that more research is needed on this question that uses more objectively measured outcomes. Second, we are unable to cleanly identify the ‘education period’ effects as truly reflecting causal effects of an Ontario-specific educational campaign, in part because we do not know the content or extent of public information efforts. Importantly, we cannot empirically distinguish education period effects from anticipation effects: It could be that there is no causal effect of the education campaign per se and that all the relative differences in outcomes during the education period simply reflect anticipatory behavior. We can say, however, that the education campaign appears to have had particularly large effects in the direction the policymakers intended (i.e., less overall and handheld cellphone use while driving with no concurrent increase in hands-free cellphone use while driving) among the highly educated sample, so this may be interpreted as evidence consistent with an important role for the education campaign. Third, the overall welfare effects of our results are not unambiguous. This is because—as discussed earlier— the literature on the relative riskiness of handheld versus hands-free cellphone use while driving is not completely settled. Research evaluating the effects of bans on hands-free cellphone use while driving might help shed light on this question, but the lack of sufficient policy adoption variation is a serious constraint. Of course, the fact that the likelihood of reporting any cellphone use while driving significantly declined in Ontario during the full-ban period should unambiguously improve public health and safety, although it is not clear how much consumer surplus was reduced.16 Despite these challenges, our results contribute to a broader and timely literature on the effects of increasingly common driver cellphone bans. In so doing, our results highlight one possibility why prior studies relating these bans to accidents and fatalities may have reached mixed results. These results also highlight the important role of large-scale survey evidence in complementing physical observations of driver behavior that are more common in the traffic safety and public health literatures. From a policy perspective, our results suggest that lawmakers should more directly target the specific set of risky behaviors at play: distracted driving in general, not handheld cellphone use in particular. Educational campaigns that disabuse people of the notion that hands-free cellphone use is a risk-free alternative to handheld cellphone use may also be recommended. 16

It is also possible that the regulation increases welfare of individuals who want to reduce handheld cellphone use while driving in the absence of regulation but fail to do so because of their time inconsistency (e.g., Gruber and Koszegi, 2004 and Gruber and Mullainathan, 2005).



1466


APPENDIX I Table AI. Effects of Ontario’s education campaign and cellphone ban on never or rarely use handheld cellphone while driving; regression-adjusted DD models OLS CCHS 14+, 2009–2010; expanded set of coefficient estimates (1) Never or rarely uses handheld cellphone while driving Ontario * Education period Ontario * Ban in full force Age Age squared Male Urban High school Some college Bachelor’s or more Married Single Household size Immigrant Kids under 6 years Kids 6–11 years English French Both English and French 2 Adjusted R N

0.0269 (0.0301) *** 0.0522 (0.0165) 0.000550 (0.00125) *** 4.99e05 (1.23e05) *** 0.0829 (0.00684) 0.00492 (0.00687) *** 0.0591 (0.0132) *** 0.0448 (0.0155) *** 0.0641 (0.0135) *** 0.0292 (0.0107) *** 0.0563 (0.0153) 0.00554 (0.00354) * 0.0148 (0.00864) 0.00270 (0.00736) 0.00171 (0.00804) ** 0.0244 (0.0114) ** 0.0485 (0.0187) 0.00976 (0.0128) 0.100 40 964

Models correspond to column 2 in Table III. All models include month and province fixed effects. Standard errors (in parentheses) are clus*** ** * tered at the province–month level and estimates are weighted. Significance levels are p < 0.01; p < 0.05; p < 0.1.

CONFLICT OF INTEREST No IRB approval was needed (secondary analysis of already collected data). The manuscript contains original unpublished work and is not being submitted for publication elsewhere at the same time. There are no conflicts of interest to disclose.

ACKNOWLEDGEMENT While the research and analysis are based on data from Statistics Canada, the opinions expressed do not represent the views of Statistics Canada.

REFERENCES

Abouk R, Adams S. 2013. Texting bans and fatal accidents on roadways: do they work? Or do drivers just react to announcements of bans? American Economic Journal: Applied Economics 5(2): 179–99. Alm H, Nilsson L. 1995. The effects of a mobile telephone task on driver behavior in a car following situation. Accident Analysis and Prevention 27(5): 707–715. Baker M, Gruber J, Milligan K. 2008. Universal childcare, maternal labor supply and family well-being, unpublished working paper. Bhargava S, Pathania V. 2013. Driving under the (cellular) influence. American Economic Journal: Economic Policy 5(3): 92–125. Burger N, Kaffine D, Yu B. 2011. Did California’s hand-held cell phone ban reduce accidents?, Working paper. Copyright © 2014 John Wiley & Sons, Ltd.



1467

CBC News. 2011. Hundreds charged in cellphone driving blitz, newspaper report posted February 23, 2011. Available at: http://www.cbc.ca/news/canada/toronto/story/2011/02/23/toronto-dstracted-driving-blitz528.html Caird J, Willness C, Steel P, Scialfa C. 2008. Meta-analysis of the effects of cell phones on driver performance. Accident Analysis and Prevention 40: 1282–1293. Cameron AC, Gelbach J, Miller D. 2008. Bootstrap-based improvements for inference with clustered errors. Review of Economics and Statistics 90: 414–427. Carpenter C, Stehr M. 2011. Intended and unintended consequences of youth bicycle helmet laws. Journal of Law and Economics 54(2): 305–324. Charlton SG. 2009. Driving while conversing: cell phones that distract and passengers who react. Accident Analysis and Prevention 41(1): 160–173. Cheng C. 2014. Do cell phone bans change driver behavior, unpublished working paper. Conley T, Taber C. 2011. Inference with “Difference in Differences” with a small number of policy changes. Review of Economics and Statistics 93(1): 113–125. Consiglio W, Driscoll P, Witte M, Berg WP. 2003. Effect of cellular telephone conversations and other potential interference on reaction time in a braking response. Accident Analysis and Prevention 35(4): 495–500. Fitch GM, Soccolich SA, Guo F, McClafferty J, Fang Y, Olson RL, Perez MA, Hanowski RJ, Hankey JM, Dingus TA. 2013. The impact of hand-held and hands-free cell phone use on driving performance and safety-critical event risk. Report No. DOT HS 811 757. Washington, DC: National Highway Traffic Safety Administration. Foss RD, Goodwin A, McCartt AT, Hellinga LA. 2009. Short-term effects of a teenage driver cell phone restriction. Accident Analysis and Prevention 41: 419–424. Goodwin AH, O’Brien N, Foss RD. 2012. Effect of North Carolina’s restriction on teenage driver cell phone use two years after implementation. Accident Analysis and Prevention 48: 363–367. Government of Newfoundland and Labrador – Canada. 2002. Bill passed to limit cellphone use by drivers, news release reported on December 20, 2002. Available at: http://www.releases.gov.nl.ca/releases/2002/gsl/1220n03.htm Gruber J, Koszegi B. 2004. Tax incidence when individuals are time-inconsistent: the case of cigarette excise taxes. Journal of Public Economics 88(9-10): 1959–1987. Gruber J, Mullainathan S. 2005. Do cigarette taxes make smokers happier. Advances in Economic Analysis & Policy 5(1): Article 4, 1–43. Ishigami Y, Klein RM. 2009. Is a hands-free phone safer than a handheld phone? Journal of Safety Research 40: 157–164. Kolko J. 2009. The effects of mobile phone and hands-free laws on traffic fatalities. The B.E. Journal of Economic Analysis and Policy 9(1), Article 10, 1–26. McCartt A, Braver E, Geary L. 2003. Drivers’ use of hand-held cell phones before and after New York State’s cell phone law. Preventive Medicine 36: 629–635. McCartt A, Geary L. 2004. Longer term effects of New York State’s law on drivers’ hand-held cell phone use. Injury Prevention 10: 11–15. McCartt A, Hellinga L, Geary L. 2006. Effects of Washington, D.C., law on drivers’ hand-held cell phone use. Traffic Injury Prevention 7: 1–6. Narine S, Walter L, Charman S. 2010. Mobile phone and seat belt usage rates in London 2009. Wokingham, Transport Research Laboratory Ltd, 2010 (TRL Project Report 418). National Highway Traffic Safety Administration (NHTSA). 2014. Policy statement on distracted driving. Available at: http://www.nhtsa.gov/Driving+Safety/Distracted+Driving+at+Distraction.gov/ci.Policy+Statement+and+Compiled +FAQs+on+Distracted+Driving.print. Accessed April 21, 2014. Nurullah A S, Thomas J, Vakilian F. 2013. The prevalence of cell phone use while driving in a Canadian province. Transportation Research Part F 19: 52–62. Olson RL, Hanowski RJ, Hickman JS, Bocanegra J. 2009. Driver distraction in commercial vehicle operations. Report available at: http://www.distraction.gov/download/research-pdf/Driver-Distraction-Commercial-Vehicle-Operations. pdf. Accessed April 20, 2014. Peltzman S. 1975. The effects of automobile safety regulation. Journal of Political Economy 83(4): 677–726. Redelmeier D, Tibshirani R. 1997. Association between cellular telephone calls and motor vehicle collisions. New England Journal of Medicine 336(7): 453–458. Strayer D, Johnston W. 2001. Driven to distraction: dual-task studies of simulated driving and conversing on a cellular telephone. Psychological Science 12(6): 462–466. World Health Organization. 2011. Mobile phone use: a growing problem of driver distraction. Report available at: http:// www.who.int/violence_injury_prevention/publications/road_traffic/en/index.html. Accessed April 20, 2014.



Driver cellphone and texting bans in the United States: evidence of effectiveness.

Cellphone-based devices for bioanalytical sciences.

FPscope: a field-portable high-resolution microscope using a cellphone lens.

Correlates of Marijuana Drugged Driving and Openness to Driving While High: Evidence from Colorado and Washington.

State all-driver distracted driving laws and high school students' texting while driving behavior.

Phone use while driving: results from an observational survey.

The effects of texting on driving performance in a driving simulator: the influence of driver age.

Cellphone-based detection platform for rbST biomarker analysis in milk extracts using a microsphere fluorescence immunoassay.

Cellphone-Based Hand-Held Microplate Reader for Point-of-Care Testing of Enzyme-Linked Immunosorbent Assays.

Hand-held cell phone use while driving legislation and observed driver behavior among population sub-groups in the United States.

Canada removes ban on physician-assisted suicide.

Simulated driving performance under alcohol: Effects on driver-risk versus driver-skill.

Texting while driving: is speech-based text entry less risky than handheld text entry?

Association between riding with an impaired driver and driving while impaired.

Effects of fog, driver experience and gender on driving behavior on S-curved road segments.

Driving performance and driver discomfort in an elevated and standard driving position during a driving simulation.

Co-rumination via cellphone moderates the association of perceived interpersonal stress and psychosocial well-being in emerging adults.

Attitudes of Greek Drivers with Focus on Mobile Phone Use While Driving.

Intended and unintended effects of restrictions on the sale of cigarillos to youth: evidence from Canada.

Driving while drinking: performance impairments resulting from social drinking.

Correction to Scientific Evidence Supports a Ban on Microbeads.

A Systematic Review of Intervening to Prevent Driving While Intoxicated: The Problem of Driving While Intoxicated (DWI).

Driver workload during differing driving maneuvers.

Objective assessment of the effects of texting while driving: a simulator study.