The Arms Race on American Roads: The Effect of SUV s and Pickup Trucks on Traffic Safety

Transcription

1 The Arm Race on American Road: The Effect of SUV and Pickup Truck on Traffic Safety Michelle J. White Univerity of California, San Diego, and NBER Abtract Driver have been running an arm race on American road by buying increaingly large vehicle uch a SUV and light truck. An important reaon for the popularity of large vehicle i that familie view them a providing better protection to their occupant if a crah occur. But when familie drive large vehicle, they poe an increaed danger to occupant of maller vehicle and to pedetrian, bicyclit and motorcyclit. Thi paper meaure both the internal effect of large vehicle on their own occupant afety and their external effect on other. The reult how that light truck are extremely deadly. For each one million light truck that replace car, between 34 and 93 additional car occupant, pedetrian, bicyclit or motorcyclit are killed per year and the value of the live lot i between $242 and $652 million per year. The afety gain that familie obtain for themelve from driving large vehicle come at a very high cot: for each fatal crah that occupant of large vehicle avoid, at leat 4.3 additional fatal crahe involving other occur by Michelle J. White 1

2 The Arm Race on American Road: The Effect of SUV and Light Truck on Traffic Safety 1 Michelle J. White Driver have been running an arm race on American road, replacing car with port utility vehicle (SUV) and pickup truck and then replacing thee vehicle with even larger SUV and even heavier truck, including the tank-like Hummer. From 1980 to 2000, the proportion of motor vehicle that are SUV or light or heavy truck increaed from.22 to An important reaon for the popularity of large vehicle i that familie view them a providing better protection to their occupant if a crah occur. But becaue SUV and light truck are taller, heavier and more rigid than car, they poe an increaed danger to occupant of car and to pedetrian, bicyclit and motorcyclit. Greater height mean that when SUV or light truck trike car, they hit car occupant upper bodie and head rather than their lower bodie, cauing greater injury. And when SUV and light truck trike pedetrian, bicyclit or motorcyclit, victim are hit in the body and cruhed. In contrat, when car trike pedetrian, bicyclit, or motorcyclit, victim are uually hit in the leg and thrown onto the car hood, which i relatively oft. Alo while car are deigned with crumple zone to aborb the impact of a crah, SUV and light truck are much tiffer. They therefore aborb le of the force of the crah and tranfer more to car. 3 In thi paper, I ue micro-level data on crahe to meaure both the internal effect of light truck and SUV on their own occupant afety when crahe occur and the 1 I am grateful to Emily Tang for reearch aitance and to Eli Berman, Roger Gordon, Howard Gruenpecht, Valerie Ramey, Matthew Neidell, Steve Carroll, Bob Reville, the referee, and participant at the 2003 ALEA Conference for very helpful comment. The Intitute of Civil Jutice at RAND and the NSF Economic Program provided reearch upport. An earlier verion of thi paper appeared a NBER working paper The figure for 1980 i lightly undertated becaue SUV were counted a car in 1980 and a light truck in See U.S. Cenu Bureau, Statitical Abtract of the U.S (Table 1062). 3 See Leonard Evan, Car Size and Safety: Reult from Analyzing U.S. Accident Data (Working paper, General Motor Reearch Laboratorie 1985), National Highway Traffic Safety Adminitration, A Collection of Recent Analye of Vehicle Weight and Safety (DOT HS , May 1991), National Highway Traffic Safety Adminitration, The Effect of Decreae in Vehicle Weight on Injury Crah 2

3 external effect of light truck and SUV on occupant of car, pedetrian, bicyclit and motorcyclit. The internal effect i the increae in afety that light truck/suv provide to their own occupant when crahe occur. The negative external effect i the harm that light truck/suv caue to occupant of car and to pedetrian, bicyclit, and motorcyclit when crahe occur. The reult of the paper how that light truck are extremely deadly. When driver hift from car to light truck or SUV, each crah involving fatalitie of light truck/suv occupant that i prevented come at a cot of at leat 4.3 additional crahe involving death of car occupant, pedetrian, bicyclit or motorcyclit. The reult alo ugget that when behavioral change are taken into account, large vehicle actually endanger their own occupant rather than protecting them. The afety benefit of ubtituting car for light truck and SUV on the road i found to be imilar in magnitude to the benefit of eat belt. Section I of the paper review the literature and ection II provide a imple model of the external effect of light truck. Section III and IV decribe the data and the reult. Section V examine the effect of a policy change in which one million car replace light truck or SUV. Section VI examine why liability rule and other legal intitution fail to internalize the negative external effect of heavy vehicle. Section VII i the concluion. I. BACKGROUND The effect of vehicle ize on traffic afety ha long been controverial, with ome reearcher arguing that larger vehicle increae traffic afety and other arguing the oppoite. The controvery date from the 1970, when Federal government-mandated increae in fuel economy tandard (CAFÉ tandard) led automaker to reduce vehicle weight. Crandall and Graham ued aggregate U.S. data for the 1970 and 1980 to argue that adoption of the CAFÉ tandard and the reulting reduction in vehicle weight caued many additional traffic death and eriou injurie. 4 More recently, Coate and Weight (DOT HS , January 1997), and Keith Bradher, High and Mighty: SUV The World Mot Dangerou Vehicle and How They Got That Way (2002, ch. 9) for dicuion. 4 Robert W. Crandall and John D. Graham, The Effect of Fuel Economy Standard on Automobile Safety, XXXII J. of Law & Econ (1989). 3

4 VanderHoff ued tate level data for everal year in the 1990 to argue that the increae in the proportion of U.S. vehicle that conit of SUV and light truck ha reduced traffic fatalitie. 5 Other reearcher have argued that larger vehicle reduce afety, baed on either crah data or tet in which two vehicle are crahed into each other. Meyer and Gomez- Ibanez 6 dicu evidence from a New York State tudy which found that, when a mall car i involved in a crah with another car that i large rather than mall, occupant of the mall car are 42% more likely to be eriouly injured. Converely when a large car i involved in a crah with another car that i mall rather than large, occupant of the large car are 29% le likely to be eriouly injured. 7 Thee contradictory view ugget that the overall impact of vehicle weight/ize on traffic afety i a mixture of two effect. Firt, if larger vehicle protect their occupant better in crahe, then an increae in the ize of all vehicle would increae traffic afety. But, econd, vehicle fleet are never homogeneou, particularly if pedetrian, bicyclit and motorcyclit are conidered to be ultra-light vehicle. Thi mean that when ome vehicle increae in ize, traffic afety may fall becaue an increaing proportion of crahe involve vehicle that have different ize. To illutrate, uppoe there are two type of vehicle in a fleet mall veru large. Ten crahe per year occur and all crahe involve randomly choen pair of vehicle. Crahe may therefore involve two mall vehicle, two large vehicle, or one mall and 5 See Dougla Coate and Jame VanderHoff, The Truth about Light Truck, Regulation, Spring Becaue the Crandall-Graham and Coate-VanderHoff tudie both ue aggregate data over multiple year period, they encounter the difficulty that change in mandated afety equipment and practice, uch a eatbelt, anti-lock brake, airbag, trengthened door panel, and law requiring ue of eat belt, occurred over the ame period. A a reult, the Coate and VanderHoff tudy may attribute the reduction in fatalitie to the rie in the number of SUV and light truck when it i actually due to afety improvement. Uing micro data on crahe rather than aggregate data ma ke it poible to eparate out thee effect. Alo ee Theodore E. Keeler, Highway Safety, Economic Behavior, and Driving Enforcement, 40 Am. Econ. Rev. 684 (1994). 6 John R. Meyer and Joe A.Gomez-Ibanez, Auto, Tranit and Citie (1981, p. 264) 7 See alo Inurance Intitute for Highway Safety, Statu Report: Crah Compatibility, How Vehicle Type, Weight Affect Outcome (1998), Hand Jokch, Dawn Maie, and Robert Pickier, Vehicle Aggreivity: Fleet Characterization Uing Traffic Colliion Data (Working paper, U.S. Department of Tranportation, HS , 1998), Tom Wenzel and Marc Ro, Are SUV Really Safer than Car? (Working paper, Environmental Energy Technologie Diviion, Lawrence Berkeley National Laboratory, Fall 2002) available at and Ted Gayer, Motor Vehicle Regulation and the Fatality Rik of Sport- Utility Vehicle, Van and Pickup (Working paper, Georgetown Univerity, 2002). 4

5 one large. Suppoe the cot per crah involving a mall and a large vehicle i $50, the cot per crah involving two mall vehicle i $45, and the cot per crah involving two large vehicle i $40. Initially, the fleet conit of all mall vehicle, o that total crah cot are $450/year. But if 10% of mall vehicle are replaced by large vehicle, the cot of crahe rie to $458.50, becaue ome crahe of two mall vehicle are replaced by cotlier crahe of one mall and one large vehicle. The total cot of crahe i maximized when the fleet conit of 60% mall and 40% large vehicle, when it i $466. If the fleet hift entirely to large vehicle, then the total cot of crahe fall to $400, ince all crahe involve two large vehicle. Thi ugget that the effect on afety of an increae in average vehicle ize could either be poitive or negative, depending on fleet compoition and the relative cot of different type of crahe. Thu when mall car were ubtituted for large in repone to government-mandated CAFÉ tandard, crah cot may have rien becaue more crahe involved a mall and large car rather than two large car. Similarly, the ubtitution of SUV and pickup truck for car in recent year may have increaed crah cot becaue more crahe now involve a car and an SUV or pickup, rather than two car. I dicu thee iue further below. 8 There i alo a literature both by economit and engineer on the behavioral repone to change in vehicle characteritic. Sam Peltzman argued that driver repond to the increaed afety that eat belt provide by driving fater. 9 Leonard Evan argued that driver drive more afely in mall car than in large car, preumably to compenate for the greater danger they face. 10 II. THEORY Suppoe a particular driver vehicle may have a two-vehicle crah with a randomly elected other vehicle, including pedetrian, bicyclit or motorcyclit a ultra-mall 8 In the analyi below, I alo conider whether large vehicle are more likely to have ingle vehicle crahe than mall vehicle and whether driving behavior differ ytematically by vehicle ize. 9 Sam Peltzman, The Effect of Automobile Safety Regulation, 83 J. of Pol. Econ. 677 (1975). 10 Leonard Evan, Accident Involvement Rate and Car Size (Working paper, General Motor Reearch Laboratorie, Warren, MI, 1983), and Leonard Evan, upra note 3. 5

6 vehicle. Driver are aumed to chooe the ize of their vehicle. Suppoe a particular driver drive a vehicle of ize and other driver on average drive vehicle of ize S. There are N other driver. The probability of the particular driver having a twovehicle crah with any other driver i denoted p (, S ), which depend on the ize of both the particular driver vehicle and other driver vehicle. Greater ize i aumed to increae the probability of crahe, o that p, > 0. In a crah, occupant of the particular driver vehicle uffer damage of d (, S) and occupant of the other driver p S vehicle uffer damage of D (, S). When either vehicle i larger, it own damage in a two-vehicle crah i maller, but damage to the other vehicle i larger, o that d, < 0 but d, > 0. S D D S In addition to two-vehicle crahe, ingle vehicle crahe may occur in which vehicle go off the road or hit a fixed object uch a a tree or a highway barrier. Suppoe the particular driver probability of a ingle vehicle crah i denoted ρ (). Damage to the vehicle occupant in thi type of crah i denoted δ () driver are denoted Ρ (S) and (S). The ame term for other. Larger vehicle are aumed to have higher probabilitie of ingle-vehicle crahe and higher damage in thee crahe, o that ρ,, Ρ, > 0. Finally, aume that vehicle ize i meaured in unit coting one δ S S dollar each. 11 The ocial cot of vehicle ize i: + NS + Np(, S)( d (, S ) + D(, S)) + ρ ( ) δ ( ) + NΡ( S ) ( S) (1) The ocial cot of vehicle ize include the cot of purchaing larger vehicle plu the expected cot of two-vehicle and ingle-vehicle crahe. Note that driver utility gain from driving larger/taller/more threatening vehicle which the auto indutry refer to a 11 Thi model extend the tandard law and economic model of the choice of care to conider the choice of vehicle ize. See Steven Shavell, Economic Analyi of Accident Law (1987), Michelle J. White, An Empirical Tet of the Comparative and Contributory Negligence Rule in Accident Law, 20 RAND J. of Econ. 308 (1989), and Aaron S. Edlin, Per-Mile Premium for Auto Inurance (National Bureau of Economic Reearch Working Paper 6934, 1999). See Yu -ping Liao and Michelle J. White, No-Fault for Motor Vehicle: An Economic Analyi, 4 Am. Law and Econ. Rev (2002) for a game -theoretic verion of the model that focue on the trategic interaction between the particular driver care level and that of other driver. Note that the number of mile driven i treated a fixed. 6

7 driver reptilian intinct i ignored. 12 Alo, to keep the model imple, the number of mile driven i treated a fixed. The firt order condition defining optimal vehicle ize for the particular driver and other driver are: 1 + N ( pd + p D) + ( ρ δ + ρδ ) + N( pd + p d) = 0; (2) 1 + ( pd S + psd) + ( P S + PS ) + ( pds + psd) = 0 ; (3) In eq. (2), N ( pd + p D) i the marginal harm to other driver involved in two-vehicle crahe when the particular driver drive a larger vehicle the external effect. It mut be poitive ince the particular driver impoe higher damage on other vehicle occupant by driving a larger vehicle. The next et of term, ( ρ δ + ρδ ) + N( pd p d), i the + marginal benefit to the particular driver from driving a larger vehicle the internal effect. Of the four term in the internal effect, three are poitive and only one-- Npd --i negative. The particular driver incur higher expected crah damage in ingle-vehicle crahe and i more likely to be involved in two-vehicle crahe when he drive a larger vehicle, but her damage when he i involved in two-vehicle crahe i maller. Suppoe for the moment that the overall ign of the internal effect i negative, o that the particular driver own crah cot fall when he drive a larger vehicle. (Thi iue i invetigated in the empirical work below.) In order for eq. (2) to hold a an equality, the negative internal effect mut exceed the poitive external effect and the combined value of both effect mut decline in abolute value from greater than one to le than one a rie. Auming that thi condition hold for the particular driver, eq. (2) determine an internal olution for the particular driver optimal vehicle ize, *. However corner olution are likely to occur. If the internal effect i negative overall and large compared to the external effect at all value of, then the optimal vehicle ize i the larget poible vehicle. Alternately if the internal effect i poitive rather than negative overall, then the optimal vehicle ize i the mallet poible vehicle. The ame type of condition hold for other driver optimal vehicle ize. 12 See Bradher, upra note 3, Chapter 6, for dicuion. 7

8 Now conider the particular driver private cot of vehicle ize. Aume for implicity that driver alway bear their own crah damage and are never liable for other driver crah damage. (The effect of alternate liability rule i conidered below.) Then the particular driver expected private cot of vehicle ize i + Npd + ρδ. Treating other driver choice of vehicle ize a fixed, the particular driver chooe her vehicle ize to atify: 1 + ( ρδ + ρ δ ) + N( pd + p d) = 0 (4) Eq. (4) i identical to eq. (2), except that the external effect diappear. Therefore the particular driver chooe her vehicle ize o to equate the internal effect to the marginal cot of ize. Eq. (4) hold a an equality if the overall internal effect i negative and it abolute value decline from greater than one to le than one a rie. Auming that eq. (2) and (4) both have internal olution, the particular driver ha an incentive to chooe an inefficiently large vehicle becaue he ignore the external cot to other driver of her vehicle ize. Since other driver face the ame ditortion, they all drive inefficiently large vehicle. 13 In reality, driver chooe care level in driving a well a chooing vehicle ize, and the model ugget that thee choice are related. Suppoe the particular driver hift to a larger vehicle. A a reult, her expected crah damage may be lower and, a a reult, he may chooe a lower care level in driving. 14 But lower care and larger vehicle ize increae the particular driver external effect on other driver, ince both change raie other driver expected crah damage. In the empirical work, I ue micro-level data on crahe to etimate the internal and external effect of driving larger vehicle. III. DATA 13 Corner olution are alo likely in thi cae. If the internal effect i large and negative at all value of, then the particular driver chooe the larget poible vehicle. In thi ituation there i no negative externality if the optimal vehicle ize i alo the larget poible vehicle. Alternately if the internal effect i poitive overall or negative but mall, there may be no negative externality becaue both the ocial and private firt order condition imply that the bet choice i the mallet poible vehicle. 14 Evan, upra note 3, provide evidence that driver of larger vehicle are more likely to be involved in crahe, which ugget that they ue le care than driver of maller vehicle. 8

9 III. The dataet i a ample of police-reported motor vehicle crahe produced by the National Highway Traffic Safety Adminitration General Etimate Sytem (available at To my knowledge, economit have not previouly analyzed thee data. Detailed information i provided concerning vehicle type of all vehicle involved in each crah, the circumtance of the crah, and the injurie utained by all peron involved in the crah. I divide vehicle into three categorie: car, light truck (including SUV, van, and pickup truck), and heavy truck (including large truck and bue). 15 Five type of crahe are examined eparately: two-vehicle crahe involving at leat one car, two-vehicle crahe involving at leat one light truck, ingle vehicle crahe, crahe involving a vehicle hitting a pedetrian or bicyclit, and crahe involving a vehicle and a motorcycle. 16 The data cover the period IV. SPECIFICATION AND RESULTS The baic pecification i a logit regreion explaining fatalitie or eriou injurie in particular type of crahe (where eriou injurie are defined a diabling or incapacitating). I dicu the reult for each type of crah eparately. A. Fatalitie and eriou injurie in two-vehicle crahe involving car. Define vehicle one (v1) to be the car and vehicle two (v2) to be the other vehicle. If both vehicle are car, then one car i choen randomly to be vehicle one. 18 The dependent variable are a dummy variable that equal one if one or more occupant of vehicle one were killed in the crah and a dummy variable that equal one if one or more occupant of vehicle one were eriouly injured or killed. There are approximately 192,000 two- 15 I follow the government claification of SUV, van and pickup a light truck. The heavy truck category include ingle unit traight truck, combination truck, and medium or heavy motorhome. 16 Crahe involving more than two vehicle (about 6.3% of all crahe) and hit and run crahe are omitted, the latter becaue no information on the driver i available. Crahe involving farm equipment, nowmobile, van-baed chool bue, and hore are alo omitted. 17 Becaue the data cover crahe involving low damage level or poible injury, I ignore iue of ample election bia that were of concern to author uing data on fatal crahe only. See Steven D. Levitt and Jack Porter, Sample Selection in the Etimation of Air Bag and Seat Belt Effectivene, 83 Rev. of Econ. and Stat. 603 (2001), for di cuion. 18 Thi i becaue the GES tend to report the vehicle in which the mot eriou harm occur a vehicle one. 9

10 vehicle crahe involving car in the dataet, including 701 with fatalitie and 9,800 with eriou injurie. The key explanatory variable are two dummy variable for whether vehicle two i a light truck or a heavy truck, where the omitted category i another car. The coefficient of thee variable meaure the change in the probability of fatalitie or eriou injurie in vehicle one when vehicle two i a light or heavy truck rather than another car. Since the hypothei i that occupant of car are more likely to be injured or killed in crahe if the other vehicle i larger, both variable are predicted to have poitive ign. I alo include a et of control variable that capture the circumtance of the crah. Thee include dummy variable for whether the crah occurred in rain, now, or fog (the omitted category i clear weather), whether the crah occurred in darkne, whether the crah occurred in a medium or large city (the omitted category i a mall town or rural area), whether the crah occurred on an intertate highway or a divided highway (the omitted category i a two-way treet), and whether the crah occurred on a weekday. I alo include eparate dummy variable for whether the driver of vehicle one or vehicle two wa male, whether the driver of vehicle one or vehicle two wa under 21 or over 60 year old, and interaction term for whether the driver of either vehicle wa both male and under 21. Dummy variable are alo included for whether the driver of vehicle one or vehicle two wa driving more than ten mile per hour above the peed limit and for whether the driver of vehicle one or vehicle two or both wa driving negligently (thi include driving when drunk or under the influence of drug). Separate variable for the number of occupant in each vehicle and for whether the driver of vehicle one wore a eatbelt are included. For everal of the variable, there are alo additional dummy variable for miing data. Year dummie are included to account for the increaing prevalence of airbag and other afety feature over the period (ue of eatbelt i controlled for directly.) Weight are ued to make the ample repreentative of all crahe. 19 Summary tatitic are hown in table 1, column The dataet doe not include the tate in which the accident occurred, o that tate dummy variable cannot be ued. But the weight are deigned to take care of the problem that different tate reporting ytem include varying proportion of accident of particular type. The weight alo offet the overampling of fatal crahe in the dataet. 10

11 The reult of the logit regreion explaining fatalitie and eriou injurie for occupant of vehicle one are hown in table 1, column 1 and 2. Standard error are in parenthee. Both the light truck and heavy truck dummie have the predicted poitive ign and are trongly tatitically ignificant in both model. Among the other variable, occupant of vehicle one are more likely to be killed or eriouly injured in crahe that occur at night or on weekend, in crahe that occur in citie rather than rural area, in crahe in which either vehicle peed wa more than 10 mile per hour above the limit, in crahe in which the driver of vehicle one wa more than 60 year old or the driver of vehicle two wa male, and when vehicle one contained more occupant. Occupant of vehicle one are le likely to be killed or eriouly injured if the driver of vehicle one wore a eatbelt. But, urpriingly, the dummie for male driver and for young male driver generally have negative rather than poitive ign and the ign of the dummy variable for driving negligently are generally negative. To get a ene of the importance of the v2 variable, table 2, top ection, how the predicted probabilitie of fatalitie and eriou injurie conditional on a crah. 20 When a car i involved in a two-vehicle crah with a light truck, the predicted probability of the car occupant uffering one or more fatalitie i.00161, compared to when the other vehicle i another car. Thu the probability of fatalitie for car occupant fall by 38% when the other vehicle i a car rather than a light truck. For eriou injurie, the reduction i from.0282 to.0228, or 19%. B. Injurie and fatalitie in two-vehicle crahe involving light truck. In thi dataet, vehicle one (v1) i the light truck and vehicle two (v2) i the other vehicle. If both vehicle involved in the crah are light truck, then one i randomly choen to be vehicle one. The key explanatory variable again are dummie for whether vehicle two i a light truck or a heavy truck rather than a car. The predicted ign of the v2 dummie 20 The predicted value are calculated by evaluating the relevant logit regreion to obtain the predicted probability of fatalitie eparately for each obervation, uing the actual value of the explanatory variable. For the predicted probability of fatalitie that i labeled a v2 = light truck in table 2, I take a weighted average over all obervation in which v2 i a light truck. For the predicted probability of fatalitie labeled a v2 = car in table 2, I take a weighted average over the ame et of obervation, but change the value of v2 to be a car. Thi aume that when light truck driver hift to driving car, their demographic characteritic and driving behavior variable remain the ame. All other figure in table 2 are calculated uing the ame procedure, except thoe labeled actual ditribution of vehicle which are dicued below. 11

12 are again poitive, ince occupant of light truck are more likely to be killed or injured in two-vehicle crahe if the other vehicle i larger. The control variable are the ame a in the previou regreion. The reult of the logit regreion are hown in table 3, top panel. Since the reult for the control variable are imilar to thoe for the previou dataet, only the coefficient and tandard error of the v2 dummy variable are given. (Summary tatitic are given in column 3 of table 3, top panel.) Both v2 variable have poitive ign and are trongly tatitically ignificant in both regreion. Table 2, econd panel, indicate that if a light truck i involved in a crah with a car rather than another light truck, the probability of fatalitie among the light truck occupant fall from to , or by 55%, and the probability of eriou injurie among the light truck occupant fall from.0198 to.0154, or by 22%. C. Injurie and fatalitie in crahe involving pedetrian, bicyclit and motorcyclit. The third and fourth dataet conit of crahe involving a vehicle hitting a pedetrian or bicyclit and a vehicle hitting a motorcyclit, repectively. 21 In both dataet, the pedetrian or bicyclit or motorcyclit i vehicle one (v1) and the car or truck i vehicle two (v2). The key explanatory variable again are dummie for whether vehicle two i a light truck or a heavy truck rather than a car. The hypothei i that pedetrian/bicyclit and motorcyclit are more likely to be killed or eriouly injured when they are truck by light or heavy truck rather than car, o that the v2 = light truck and v2 = heavy truck variable are predicted to have poitive ign. The control variable are the ame a in the previou regreion. Both v2 dummy variable are poitive a predicted and trongly tatitically ignificant in all of the regreion (ee table 3, econd and third panel). If a light truck rather than a car hit a pedetrian/bicyclit, the probability of fatalitie rie from.0181 to.0329, or by 45%, and the probability of eriou injurie rie from.205 to.230, or by 11%. Motorcyclit probability of being killed rie from.0241 to.0543, or by 56%, in 21 Skateboarder, kater, and people in wheelchair and baby carriage are included in the pedetrian/bicyclit dataet. 12

13 the ame circumtance, and their probability of being eriouly injured rie from.234 to.316, or by 26%. (See table 2, third and fourth panel.) 22 D. Injurie and fatalitie in ingle vehicle crahe. In the lat dataet, the dependent variable are dummy variable that equal one if one or more occupant of the vehicle involved in the crah were killed or eriouly injured. The key explanatory variable are dummie for whether vehicle one i a light truck or a heavy truck, rather than a car. The hypothei i that, becaue larger vehicle are higher and le table than car, they are more likely to kill or eriouly injure their occupant in ingle vehicle crahe. The control variable are imilar to thoe in the previou regreion, but there are no variable for vehicle two. The coefficient of the light truck and heavy truck dummie from the logit regreion are given in table 3, bottom panel. The v1 = light truck coefficient are poitive and tatitically ignificant in both regreion, but urpriingly--the v1 = heavy truck coefficient are negative and tatitically ignificant in both. Thu people involved in ingle vehicle crahe are more likely to be killed or eriouly injured if they are driving a light truck rather than a car, but le likely to be killed or eriouly injured when they are driving a heavy truck rather than a car. 23 Table 2, bottom panel, indicate that if a light truck rather than a car i involved in a ingle-vehicle crah, the probability of fatalitie rie from to.00824, or by 14%, and the probability of eriou injurie rie from.0604 to.0637, or by 5%. V. EXTERNAL VERSUS INTERNAL EFFECTS OF LARGE VEHICLES Now conider a policy change that caue one million light truck to be replaced by car. The policy could be a pecial tax on ga guzzler, a tax on purchae or regitration of SUV and pickup, or any of a variety of other meaure (ee the dicuion below). I focu on replacing light rather than heavy truck with car, ince mot SUV and pickup truck are ued for non-buine purpoe and therefore could be replaced by car without lo of economic efficiency. Becaue the average number of car and light truck on 22 A dummy variable i included in the motorcycle crah regreion for whether motorcyclit wore helmet. Surpriingly, it i not tatitically ignificant in either regreion. 13

14 U.S. road during the period of the dataet were 132 million and 53 million, repectively, thi change i marginal in the ene that it involve expanding the tock of car by le than 1% and reducing the tock of light truck by le than 2%. 24 I do the calculation in two way. Firt I aume that when light truck driver hift to car, their driving behavior remain the ame and o their probability of being involved in crahe remain that of light truck driver. Thi i realitic if driver tend to ort acro vehicle type depending on their driving behavior, i.e., reckle driver chooe light truck and careful driver chooe car. Second I aume that when light truck driver hift to car, their driving behavior change to that of car driver and their probability of being involved in crahe become that of car driver. Thi i realitic if driving behavior depend mainly on the type of vehicle driven. (One factor upporting the behavior change aumption i that, becaue driver of light truck it higher relative to the ground than driver of car, they perceive a given peed to be lower and therefore they drive fater--regardle of their individual driving habit.) 25 The two aumption referred to a no-behavior-change and behavior-change --are treated a lower and upper bound etimate of the effect of the policy change. Table 4 how the annual probability of crahe by type of crah and type of vehicle during the period of our data. Relative to car, light truck are much more likely to be involved in two-vehicle and ingle-vehicle crahe, but are equally likely a car to be involved in crahe involving pedetrian/bicycle and motorcycle. Table 5 how the reult of the policy change for fatal crahe. Each external and internal effect i hown on a eparate row and the reult under the no-behavioral-change and behavioral-change aumption are hown in eparate column. Examine the no-behavior-change aumption firt. The firt external effect i the reduction in the number of two-vehicle crahe involving fatalitie of car occupant following the policy change. From table 2, the reduction in the probability of car 23 Thi reult may reflect the fact that driver of heavy truck are profeionally trained. 24 The car tock figure i the average number of regitered car in the U.S. over the ample period. The light truck figure i computed by adding up all U.S. ale of light truck between 1990 and the relevant year and then averaging over the ample year. Data are taken from U.S. Cenu Bureau, upra note 2 (table 1010 and 1062). 25 At an extreme, paenger in an airplane flying at high altitude perceive their peed a cloe to zero. See Curti Rit, Roll Over, Newton: The Deign of Sport Utility Vehicle i Enough to Make the Father of Phyic Turn in Hi Grave, 22 Dicover 44 (April 2001). 14

15 occupant being killed in two-vehicle crahe when v2 i a car rather than a light truck i = From table 4, the probability of a light truck being involved in a two-vehicle crah i.0398 per year and thi figure i aumed to remain the ame after the policy change. Multiplying thee figure together and multiplying the reult by 1,000,000, we find that 24 fewer fatal crahe would occur if the policy change were adopted. 26 The next two external effect are the impact of the policy change on crahe involving vehicle hitting pedetrian/bicyclit and motorcyclit. Following the ame procedure, the policy change reduce the number of fatal crahe involving pedetrian/bicyclit and motorcyclit by 10 and 5 per year, repectively. Combining all three external effect, the policy change would reduce the number of fatal crahe involving occupant of car, pedetrian, bicyclit and motorcyclit by 40 per year. VI. Now turn to the internal effect of the policy change. Becaue of the change, one million ertwhile light truck driver become car driver and experience car occupant rather than light truck occupant probabilitie of being killed or injured in ingle- or twovehicle crahe. Conider ingle-vehicle crahe firt. Becaue light truck are more dangerou than car in ingle vehicle crahe, the policy reduce the number of inglevehicle crahe involving fatalitie by (.0103)( )(1,000,000) or by 12 per year. Now conider two-vehicle crahe. I firt ue the logit regreion for the light truck dataet to predict the average probability of fatalitie when a light truck i involved in a two-vehicle crah with a randomly-elected other vehicle, which i (See the figure for actual ditribution of vehicle in table 2.) Then I ue the logit regreion for the car dataet to predict the average probability of fatalitie when a car i involved in a two-vehicle crah with a randomly-elected other vehicle, which i The difference between thee two figure i the increae in the probability of a two-vehicle crah being fatal when driver hift from driving light truck to driving car. Multiplying thi difference by the probability of light truck being involved in two-vehicle crahe 26 The firt external effect correpond to the term pd in eq. (4) above. The damage meaure d i the probability of fatalitie conditional on a crah occurring, o that d i the change in the probability of fatalitie when car have two-vehicle crahe with other car rather than light truck. p i the probability of a light truck having a two -vehicle crah. Becaue the policy change involve one million light truck driver hifting to car, pd i multiplied by 1,000,000. The other external effect and the firt internal effect are computed uing the ame procedure. All calculation ue the ample weight. 15

16 and by1,000,000, the reult i that the policy change increae the number of fatal crahe by 21 per year. Combining the two internal effect, they imply that when one million light truck driver hift to car, they and other occupant of their vehicle experience 9 additional crahe involving fatalitie per year. Turning to the overall reult, one triking implication i that when driver chooe light truck rather than car, the ratio of external to internal effect i 40/9 = 4.3. Thi mean that for each fatal crah involving occupant of their own vehicle that driver avoid by chooing light truck, more than 4 additional fatal crahe occur involving car occupant, pedetrian, bicyclit and motorcyclit. In other word, afety gain for thoe driving light truck come at an extremely high cot to other. The right hand ide of table 5 how the effect of the policy change under the behavior-change aumption. Specifically I aume that when driver hift from light truck to car, their crah probabilitie change from thoe of light truck driver to thoe of car driver. For the firt external effect, thi mean that the change in the number of crahe involving fatalitie become [( )(.0398) + ( )(.00161)](1,000,000) = Thi figure i nearly twice a large a the figure of -24 in the no-behavior-change cae. Other figure in the right-hand column of table 5 are calculated uing the analogou procedure. Both the external and internal effect of the policy change are more favorable in the behavior-change cae, i.e., more fatal crahe involving both occupant of the driver own vehicle and occupant of other vehicle, pedetrian, bicyclit, and motorcyclit are avoided. An important difference between the two et of reult i that the overall internal effect change ign: from 9 additional fatal crahe to 23 fewer fatal crahe. Thi i becaue in the behavior-change cae, driver who witch from light truck to car become afer, ince the reduction in the number of ingle vehicle crahe more than offet the extra danger of being involved in a two-vehicle crah with a larger vehicle. 27 The firt external effect in the behavior-change cae correpond to pd + pd in eq. (4) above. The firt term i the ame a in the no-behavior-change calculation. In the econd term, p i the change in the probability of two-vehicle crahe when driver hift from light truck to car and d i the initial damage level, or the probability of fatalitie when car are involved in two-vehicle crahe with light truck. The reult i multiplied by one million. 16

17 Thi reult implie that driving a light truck rather than a car provide no afety gain for the light truck occupant they would be afer driving car. Overall, the number of fatal crahe avoided a a reult of the policy change nearly triple in the behavior-change cae: from 30 to 81 per year. Becaue both the internal and the external effect of the policy change are beneficial in the behavior change cae, the ratio of external cot to internal benefit i infinite. To value the benefit of the policy change, I ue the fact that each fatal crah involve an average of 1.15 death and I take the average value of a life to be $7 million. 28 Thi mean that value of the policy change i 30*1.15*($7 million) = $242 million per year in the no-behavior-change cae and 81*1.15*($7 million) = $652 million per year in the behavior-change cae. Taking the midpoint of thi range, the value of the policy change i $447 per year for each vehicle whoe type change from light truck to car. Now turn to the reult in table 6 for eriou injury crahe. In the no-behaviorchange cae, the policy change avoid 246 crahe involving eriou injurie of car occupant, pedetrian, bicyclit and motorcyclit, but it caue 328 additional eriou injury crahe of ertwhile light truck occupant. Thu the overall reult of the policy change i an increae of 82 eriou injury crahe and the ratio of external benefit to internal cot i only.75. But in the behavior-change cae, the policy change caue 611 fewer eriou injury crahe to occur per year. How do the benefit of reducing the number of light truck compare to the benefit of other policy change involving driving? Crandall and Graham 29 etimated that the CAFÉ tandard of the 1970 caued about 300 additional death to occur in traffic crahe per year. In comparion, the policy change analyzed here would ave between 34 and 93 live each year even though it only involve ubtituting one million car for light truck. Levitt and Porter 30 found that eat belt ave 11,000 live per year at a total yearly cot of $513 million and air bag ave 2,250 live per year at a total yearly cot of $4 billion. If we value each life aved at $7 million, ubtract the cot of eat belt/air bag from their benefit, and convert the reult to a per vehicle bai, then the net value of 28 W. Kip Vicui and Joeph E. Aldy, The Value of a Statitical Life: A Critical Review of Market Etimate Throughout the World, 27 J. of Rik and Uncertainty 5 (2003). 29 Supra note Supra note

18 eat belt per vehicle per year i $413 and the net value of air bag per vehicle per year i $64. The eat belt figure i imilar in magnitude to the value of replacing light truck with car, which we calculated to be $447 per vehicle per year at the midpoint of our upper and lower bound etimate. 31 Overall, the policy change analyzed here generate enormou gain and, becaue car are cheaper than light truck, it cot are negative. VI. THE FAILURE OF LIABILITY RULES, INSURANCE, AND TRAFFIC RULES Thi paper how that driver deciion to drive light truck rather than car have extremely large negative external effect and may alo have negative internal effect. Thi ection conider whether any of the exiting legal intitution including tort liability, traffic rule, and requirement that vehicle owner purchae liability inurance-- internalize thee negative effect. Conider tort liability rule firt. Tort liability make injurer liable for victim damage under certain circumtance and therefore give driver an incentive to ue additional care in order to reduce the probability and everity of crahe. In theory, liability for damage hould fall more heavily on owner of light truck than car and thi hould both dicourage driver from purchaing light truck and encourage them to ue additional care if they do purchae thee vehicle. But in practice, tort liability ha only weak incentive effect. One problem i that liability for damage in the traffic context i generally baed on negligence, o that driver are only liable if their care level fall below the negligence tandard. An optimal negligence tandard would require that light truck driver take more care than car driver, ince the cot of care i the ame for both type of vehicle but light truck caue greater damage. A related problem i that negligence rule encourage a higher-than-optimal level of driving activity, becaue driver ecape liability for damage in crahe a long a their care level in driving exceed the negligence tandard. Driver therefore have an incentive to hift from car to light truck becaue 31 Note that the figure for the net value per vehicle of eat belt and air bag are for all vehicle, while the figure for the value of ubtituting car for light truck i a marginal value. If additional car were ubtituted for light truck, then the marginal value would eventually fall a the vehicle fleet became motly 18

19 they do not bear the cot of the additional crahe they caue, a long a their driving meet the negligence tandard. The firt problem could be olved and the econd could be mitigated by raiing the negligence tandard for light truck driver above that for car driver. For example, lower peed limit could et for light truck than car, imilar to the lower peed limit that are ometime poted for heavy truck on freeway. But the tort ytem in fact applie the ame tandard of care to driver of light truck a driver of car. Another problem with the tort liability ytem i that many tate in the U.S. ue nofault ytem, rather than negligence rule, to determine liability in motor vehicle crahe. 32 In tate with no-fault, the liability ytem doe not penalize driver of large/heavy vehicle at all for cauing higher damage. In fact, driver of car are at a diadvantage under no-fault, ince they uffer more damage in crahe and bear thee cot themelve. Now conider traffic rule, which impoe monetary fine, required attendance at traffic chool, licene upenion, or other penaltie on driver who violate traffic rule. Traffic rule uffer from the ame hortcoming a liability rule, ince the ame tandard of driving behavior and the ame penaltie are impoed on driver of both light truck and car. They therefore do not dicourage driver from hifting to light truck. Finally conider liability inurance. Mot tate require vehicle owner to purchae liability inurance, o that the inurer rather than the driver pay compenation for damage to victim in crahe when the inured driver i liable. Becaue many driver are judgment-proof, requiring that driver purchae liability inurance increae the probability that crah victim will actually be able to collect when they are legally entitled to do o. Alo, inured driver have an incentive to take care in driving even though their inurance companie pay damage, becaue inurance companie charge higher premium when their expected liability i higher. Thee factor ugget that owner of light truck hould pay higher liability inurance premium than owner of car, both becaue they are involved in more crahe and becaue their vehicle do more car. In thee calculation, the tock of vehicle in 1997 i aumed to be 185 million, the figure ued to contruct the crah probabilitie in table A of 1995, fifteen tate in the U.S. ued ome verion of no-fault for traffic crahe. See Liao and White, upra note 11, for an analyi of no-fault liability rule in the motor vehicle accident context. 19

20 damage when crahe occur. But again the reality i different. Becaue the negligence and no-fault liability ytem often allow driver to ecape liability for damage they caue, owner of light truck do not necearily pay higher inurance premium. Another factor that affect inurance rate i that mot tate require driver to purchae only a mall amount of liability coverage. Five tate do not require driver to purchae liability inurance at all, one tate require driver to purchae only $10,000 of coverage, and the mot common minimum coverage requirement i only $25, Since the damage in fatal and eriou injury crahe i far higher, thi mean that driver rarely pay for all of the damage their vehicle caue in high damage crahe. Limited coverage requirement reduce inurance companie incentive to et higher premium for larger vehicle, becaue the higher damage that thee vehicle caue often exceed the coverage limit. Another problem i that up to 30 percent of driver in ome tate are uninured. When driver purchae liability inurance, they typically buy additional coverage for their own damage if they are involved in a crah with an uninured driver. The cot of uninured driver coverage i higher for driver of car than driver of light truck and thi factor tend to raie the relative cot of liability inurance for car. 34 Thee conideration ugget that the negative external effect of large vehicle are not internalized by exiting liability rule, traffic rule or liability inurance. Would any of the reform that have been propoed recently be effective in internalizing the negative external effect of heavy vehicle? One recently propoed reform, called pay-at-thepump involve bundling liability inurance with gaoline purchae, o that all driver would pay a fixed amount per gallon of gaoline for liability inurance. 35 The pay-at-thepump propoal ha the advantage of forcing all driver to purchae liability inurance and 33 The tate that do not require owner of vehicle to purchae liability inurance are NH, TN, SC, VA and WI. The dollar figure are the required amount of inurance coverage for bodily injury to a ingle peron injured in a crah (higher limit apply if there are multiple victim in a ingle crah). Thee figure are taken from 34 Inurance companie follow widely differing practice concerning pricing of liability inurance by type of vehicle. State Farm and GE Auto Inurance charge owner of pickup, SUV and large van le for liability coverage, but Alltate and the Progreive Inurance Group charge owner of thee vehicle more. See Joeph B. Treater, Leading Auto Inurer to Cut Rate for Driver of the Bigget Vehicle, New York Time, Nov. 28, 2000, Joeph B. Treater and Keith Bradher, 2 Inurer Raiing Liability Coverage on Bigger Vehicle, New York Time, Dec. 2, 2000, and Car Inurance for Le, 67 Conumer Report 19, October Bradher, upra note 3, chapter 10, argue that inurance companie are loath to raie rate on SUV owner becaue they are more affluent and politically well-connected than owner of car. 35 See Edlin, upra note 11, for dicuion. 20

21 it alo charge owner of SUV and light truck more for liability inurance per mile of driving than owner of car, ince the former get lower ga mileage. The reult preented here ugget that the propoal would be beneficial becaue it would align the cot of inurance more cloely with external afety effect. Another recently propoed reform involve impoing trict liability on manufacture of SUV and pickup truck but not car--for the external harm they caue in crahe. 36 Other reform that would improve incentive include raiing minimum required level of liability coverage and replacing no-fault with fault-baed liability ytem. Other policie that could be ued to dicourage people from buying light truck and SUV include pecial excie taxe on the purchae of thee vehicle, higher regitration fee and tighter ga mileage tandard for thee vehicle, freeway toll baed on vehicle ize, and higher gaoline taxe generally. All of thee policie are in ue in Europe, where fewer light truck are een. VII. CONCLUSION U.S. traffic death totaled 42,815 in 2002, the highet figure ince Although widepread ue of eat belt, campaign againt drunk driving, and adoption of afety equipment uch a airbag and anti-lock brake caued traffic death to fall in the 1970 and 1980, the number of traffic death remained contant during the 1990 and ha been riing ince Thi i at leat in part due to the increaing heterogeneity of the U.S. vehicle fleet. A of 2001 there were 77 million light truck on the road compared to 134 million car, o that a large fraction of crahe involve light truck hitting maller vehicle, pedetrian, bicyclit, or motorcyclit. The reult of thi tudy how that light truck are extremely deadly. For each 1 million light truck that replace car, between 34 and 93 additional car occupant, pedetrian, bicyclit or motorcyclit are killed each year in traffic crahe, depending on whether driving behavior i aumed to remain contant or change. The value of the lot live alone i between $242 and $652 per year for each light truck that replace a car. One reaon that driver purchae light truck i that they think they and their familie will be afer in crahe. But for each 36 See Howard Latin and Bobby Kaola, Bad Deign, Lethal Product: The Duty to Protect Other Motorit Againt SUV Colliion Rik, 82 Boton U.L.Rev (2002) for dicuion. 21