How Does Tort Reform Affect Auto Insurance Costs?

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1 WORKING PAPER How Does Tort Reform Affect Auto Insurance Costs? Paul Heaton RAND Institute for Civil Justice WR-1012-ICJ July 2013 RAND working papers are intended to share researchers latest findings and to solicit informal peer review. They have been approved for circulation by the Institute for Civil Justice but have not been formally edited or peer reviewed. Unless otherwise indicated, working papers can be quoted and cited without permission of the author, provided the source is clearly referred to as a working paper. RAND s publications do not necessarily reflect the opinions of its research clients and sponsors. RAND is a registered trademark.

2 How Does Tort Reform Affect Auto Insurance Costs? Paul Heaton RAND July 2013 Abstract: Although proponents of tort reform argue that it will benefit consumers through lowered insurance premiums and increased insurance availability, to date there is limited empirical evidence linking tort reform to consumer outlays. Using data from the Consumer Expenditure Survey and a differences-in-differences research design, this paper examines whether any of several common state-level tort reforms affect consumer costs for auto insurance. Expenditures on auto insurance fall by 12% following no-fault repeal and 6% following relaxation of collateral source restrictions, but are not measurably affected by bad faith reform, reforms to joint-and-several liability, or noneconomic damage caps. None of the reforms generate measurable increases in auto insurance take-up. There is little variation in the impact of the reforms across income, education, and age groups, but no-fault repeal and collateral source reform do disproportionately benefit consumers with lower cost policies. Author I wish to thank Eric Helland and seminar participants at RAND who provided useful comments on the manuscript. This research was funded by the RAND Institute for Civil Justice (ICJ). The content of this work is solely the responsibility of the author and does not necessarily reflect the views of the ICJ or its supporters.

3 I. Introduction Tort reform continues to be a controversial topic, with proponents arguing that reform has the potential to save U.S. consumers and businesses millions or even billions of dollars annually even while opponents contend that reform harms consumers. 1 Despite, or perhaps because of this continued uncertainty regarding the effects of various types of reform, tort reform continues to be an area of active legislative and judicial interest. Data from the American Tort Reform Association, a pro-defendant group, indicates that 86 different laws relating to tort reform were passed by state legislatures between 2008 and However, state supreme courts, including those of Oklahoma 2, Missouri 3, Arkansas 4 have also recently struck down tort reform initiatives. The considerable variation both across states and within states over time in the policy environment related to tort access has raised questions regarding the impact of different tort rules on business, consumers, and the legal system. Although scholars have demonstrated considerable interest in measuring the effects of tort reform across a range of outcomes 5, there has been limited work linking tort reform and auto insurance, despite the fact that auto insurance is one of the most widely held consumer insurance products, with consumer expenditures on liability premiums topping $100 billion in 2011 (Insurance Information Institute 2013). Earlier work that looked at effects of reform generally examined liability lines other than auto (Hunter and Doroshow 2002; Viscusi, Zeckhauser, Born, & Blackmon 1993). Much of the scholarly debate over tort reform in recent years has focused on outcomes related to the health care system, including patient safety (Currie and Macleod 2008), physician supply (Helland and Showalter 2006; Matsa 2007; Hyman, Silver, Black, & Paik 2012; Klick and Stratmann 2007), malpractice premiums (Grace and Leverty 2012), treatment cost (Kessler and McClellan 1996, 2002; Sloan and Shadle 2009) and consumer health insurance premiums (Avraham, Dafny, & Schanzenbach 1 Compare, for example Crain, Crain, McQuilan, & Abramyan (2009) and Hinton and McKnight (2011) to Hunter and Doroshow (2002) and Eisenbrey (2006). 2 Douglas v. Cox Retirement Properties, Inc., 2013 OK 37 (Okla. 2013) 3 Watts v. Cox Medical Centers, 376 S.W.3d 633 (Mo. 2012) 4 Broussard v. St. Edward Mercy Health System, 386 S.W.3d 385 (2012) 5 Eisenberg (2012) provides a review of some of the literature in this area. 1

4 2012; Morrisey, Kilgore, & Nelson 2008). Other recent work attempts to assess the effects of the tort law environment on general economic performance (Cross 2011; Shepherd 2013). Those studies that consider auto insurance typically focus on outcomes other than expenditures or premiums or only take into account individual reforms in individual states. 6 Carvell, Currie, and MacLeod (2012), for example, examine how tort reform affects automobile accident deaths, finding evidence that no-fault repeal increases auto accident deaths while other reforms do not, but they do not consider how such effects might impact insurance costs. 7 Similarly, Browne and Schmit (2008) demonstrate an association between the tort environment of a state and the likelihood that auto crash victims consult an attorney and file suit, but they do not connect these differences in litigation behavior to premiums. Single reform studies include Hawken, Carroll, and Abrahamse (2001), Browne, Pryor, and Puelz (2004), Insurance Resource Council (2011) and Asmat and Tennyson (2013) who examine insurer bad faith; and Anderson, Heaton, and Carroll (2010), who demonstrate that repeal of no-fault lowered average automobile premiums in three states. In this paper, I use data from the Consumer Expenditure Survey and a differences-in-differences (DD) research design to examine whether various forms of tort reform affect consumer expenditures on auto insurance. In addition to looking at a wider range of reforms and states than previous work, an important contribution of the present paper is to demonstrate whether tort reform lowers costs borne by consumers, which is generally a key rationale for reform cited by policymakers. 8 Of the five types of reform examined in the paper caps on non-economic damages, no-fault repeal, reform of joint and several liability, collateral source reform, and introduction of a tort for insurer bad faith only no-fault repeal and collateral source repeal are robustly associated with reductions in consumer insurance costs. 6 One exception is Crain et al. (2009), which looks at a range of reforms across states. This study is relatively weak methodologically, however, because it includes data from only two years and includes only a limited set of statelevel controls and no state fixed effects, so the effect of reform is largely identified cross-sectionally. 7 Loughran (2001) provides an alternative of the impacts of no-fault reform on accidents. Rubin and Shepherd (2007) look at tort reform and accidental deaths, but specifically exclude vehicle accidents. 8 Because auto insurance is compulsory in almost every state, policy debates surrounding auto insurance typically use the term costs synonymously with expenditures rather than prices, a usage pattern that I follow in this paper. 2

5 No-fault repeal reduces consumer costs in subsequent years by 12%, while collateral source reform reduces costs by 6%. I also show that the effects of these reforms are experienced widely throughout the consumer population, reducing costs for consumers from different age groups and educational, income, and racial/ethnic backgrounds. Analyses using quantile regression suggest that no-fault reform and collateral source reform disproportionately benefit consumers who purchase lower cost auto policies. Section II of the paper introduces the data used for the analysis and describes the reforms I analyze. Section III presents the empirical methods. Section IV describes the results, including my analysis of insurance availability, an examination of the effects of reform on different population subgroups, and a series of robustness checks that confirm the paper s main findings. Section V concludes. II. Data and Background on Tort Reforms My primary data are drawn from the Consumer Expenditure Survey microdata files (CEX) collected by the U.S. Census Bureau on behalf of the Bureau of Labor Statistics. The CEX provides the most comprehensive data available on consumer expenditures on a variety of goods and services in the U.S. Quarterly expenditures of a rotating panel of roughly 7,000 households are captured via an interview component, which is supplemented with data from purchase diaries that catalog all purchases made by an additional 7,000 respondents over two pre-determined time windows each year. Although the CEX is a national survey of consumers, to preserve respondent confidentiality, the state of residence is suppressed or recoded for some respondents. Because the tort laws of interest are set at the state level, I limit the sample to individuals for whom non-recoded state residence information is available. 9 9 The treatment of some states changed as the CEX sampling scheme evolved over time for example, between 1998 and 1999 there was a substantial reduction in the number of respondents living in California for whom residence information was suppressed. To account for such changes in the sampling scheme, I include separate state-level sample indicators as additional controls. In the above example, rather than having a single California indicator as a control, I use a two indicators, one for Californians from 1998 and earlier, and one for Californians from 1999 and later. 3

6 My empirical analysis examines household expenditures for auto insurance over time and across consumers residing in states with different tort environments. My primary source for information about the tort environment is the database of state tort laws produced by Avraham (2011). This database captures the state tort environment with respect to joint and several liability, non-economic damages, and collateral source availability, incorporating information from both enacted legislation and relevant case law. These tort reforms are coded with explicit reference to their applicability in auto torts. These data are supplemented with information from Anderson et al. (2010), who provide a catalog of no-fault laws, and data on bad faith laws taken from Asmat and Tennyson (2013). I consider five types of tort reform: caps on non-economic damages, repeal of mandatory no-fault auto insurance, reform of joint and several liability, collateral source reform, and allowance of first-party bad faith torts. 10 There is a theoretical basis for thinking that each of these reforms might affect auto claim costs, and the policy environment with respect to each of these areas has changed in multiple states during the study period, either due to new legislation or state Supreme Court decisions that invalidate existing statutes. Caps on non-economic damages limit the amount of pain and suffering damages that are available to plaintiffs, with limits typically in the hundreds of thousands of dollars. While non-economic damage payments comprise a substantial fraction of overall insurance claim payments in auto injury cases (Anderson et al. 2010), cases with general damages that are high enough to breach a typical damage cap are relatively uncommon 11, suggesting that these reforms may be limited in their ability to affect premiums unless they exert upstream effects on settlement amounts of the willingness of attorneys to pursue cases. 10 Some studies of tort reform also examine punitive damage caps, but such caps are arguably less relevant in auto personal injury cases because punitive damages are awarded in only around 1% of auto cases that have awards (Moller 1996). 11 For example, claim-level data form the IRC suggest that implementing a $200K damage cap in states without a cap in 2007 would have reduced direct expenditures on general damages in these states by only about 4% (author s calculations from IRC 2008). 4

7 Under the doctrine of joint-and-several liability (JSL), in cases involving multiple tortfeasors, an injured party is able to recover the full amount of losses from any one of the tortfeasors, regardless of that person s share of responsibility for the loss. JSL could affect the distribution of costs in the auto context by, for example, allowing injured party in a multi-car accident to seek full recovery from the responsible party with the highest insurance limits or greatest ability to pay. Although traditionally most states recognized JSL, reform efforts in several states sought to limit the applicability of JSL, by, for example, narrowing the types of cases in which JSL could be applied or limiting JSL to defendants deemed to be more than 50% at fault. To the extent that such reform efforts reduce payouts made by tortfeasors in auto cases, it seems possible that such reforms might reduce auto premiums. The collateral source rule limits the introduction of evidence that a plaintiff has already been paid for injuries by an outside party, or consideration of such payments in the determination of damages. Proponents of the rule argue that it provides potential tortfeasors the strongest incentives to prevent injuries, because they must bear the full costs of any injury-causing activity, while opponents argue that the rule allows plaintiffs to obtain double recovery for the same injuries. Several states have enacted reform statutes that explicitly require collateral payments to be deducted from final awards in certain classes of personal injury cases, although significant policy variation has also arisen due to the frequent invalidations of such statutes by state Supreme Courts. Given that many auto injury victims have private health insurance that may cover some of the costs of their medical treatment following an injury, collateral source reforms might reduce auto insurers costs by reducing their need to provide compensation for injuries that have already been paid for by health insurers. No-fault auto insurance regimes gained popularity in the 1970s as a means of providing swifter and more certain compensation to auto crash victims. As adopted in several states, no-fault couples mandatory first-party insurance that covers medical costs and wage loss following an auto injury regardless of who was at fault with a limitation on the ability of injured parties to sue for damages following an accident. Due to concerns about rising costs and other signs of system dysfunction, several 5

8 states with no-fault regimes repealed these systems and returned to a traditional tort system employing primarily third-party insurance and no restriction on lawsuits. Because the level of insurance benefits provided under a traditional tort system are arguably lower than benefits under no-fault, one might expect no-fault repeal to reduce insurance premiums. Finally, I consider reforms that allow policyholders to pursue tort actions for insurer bad faith. Traditionally, policyholders who believe they have been unfairly denied compensation by their own insurers have available remedies through contract law, but the amount of recovery in contract cases is limited to the amount at issue based upon the contract. Some states have passed reforms that recognize a tort cause of action for insurer bad faith, offering plaintiffs the opportunity to collect non-economic or punitive damages arising from non-payment of claims. First-party bad faith claims can potentially arise in the auto context in a number of ways, including when claims are filed for property damage, in Med-Pay claims 12, or for claims involving underinsured/uninsured motorist coverage. This reform is expected to, if anything, increase the cost of insurance given that makes insurers more vulnerable to lawsuits. III. Empirical Approach My primary empirical specification is a DD regression that compares consumer auto insurance costs in periods following the passage of tort reform in a state to costs in the same state prior to reform, controlling for other factors that may affect insurance costs. Let Y ist denote an outcome measure for consumer i residing in state s in quarter t. Let Reform st represent a vector of indicator variables capturing whether state s has enacted a series of tort reforms as of time t, with separate indicators for each reform of interest. In the regression: Y ist Reform X P (1) st st i s t ist 12 Med-Pay is an optional first-party coverage available in many states that reimburses policyholders for medical costs incurred in an auto accident regardless of fault. 6

9 the vector of coefficient estimates α measures the effect of the tort reforms on the outcome of interest. I consider two primary outcomes of interest log quarterly expenditures on auto insurance, a measure of consumer costs for insurance, and an indicator variable for whether a respondent made any auto insurance payments during the past quarter, a measure of insurance take-up. This regression includes a full set of state fixed effects (γ s ) to account for time invariant factors that vary across states, such as physical geography and more permanent features of tort law. The time dummies (η t ) account for macro factors that affect consumer auto insurance costs, including general improvements in vehicle safety over time and changes in the price level. I also control for time-varying state level factors that are likely to affect loss costs and which therefore may affect premiums. These controls include measures of the demographic characteristics of the population, the unemployment rate and per capita income, average annual vehicle miles travelled per driver, and indicators for whether the state has graduated drivers licensing, primary or secondary seatbelt enforcement, and administrative license revocation following a drunk driving offense. 13 This approach measures the effects of tort reform under the assumption that there are no omitted factors from eq. (1) correlated with the passage of tort reform that also affect auto insurance costs. In contrast to the prior single-state studies relating tort reform to auto insurance outcomes, a key advantage of my approach is that it exploits information from numerous states implementing reforms at different points in time. While for any particular state it seems possible to imagine that some unobserved factor relevant for auto insurance might change at the same time that tort reform is implemented, such confounding seems less likely across multiple states and time periods. Moreover, the DD approach 13 For each tort reform, I also include separate indicators for the year immediately following the passage of the reform as additional controls. Because premiums cannot be adjusted to take into account changes in the legal environment until polices come up for renewal, the full effects of any legal change are likely to not be felt until at least a year following the implementation of the new policy, at which point all policies have had a chance to be renewed. The timing of effects in the first year is likely to depend on how aggressively insurers update policy language, and this may vary according to the reform, so I employ indicators so as to be able to remain relatively agnostic regarding the precise timing of changes. In a robustness check below, I present evidence regarding the time path of effects for no-fault repeal that suggests a gradual transition to a new equilibrium during the first year post reform. 7

10 essentially provides an estimate of the average effect of a reform across all states that implemented that reform, which may provide policymakers considering a new reform a better indication of that reform s expected impact than the experience of a single state. Although the CEX does not include data about the specific parameters of a household s auto insurance policy, such as the deductible or policy limit, it does include rich information about the economic circumstances of respondents that allows me to account for a range of household-level factors that are likely to affect auto insurance premiums. My analysis controls for the age, gender, educational attainment, and marital status of the two primary adults in the household; householder race; the number of children over age 16 by gender; number of vehicles owned; and household income. Although I cannot observe the value of insured vehicles or numbers of miles driven each year two significant determinants of insurance premiums I can proxy for these using quarterly gasoline expenditures, new vehicle expenditures, and non-insurance transportation expenditures, which I control for flexibly so as to allow for the possibility of non-linearities in the relationship between vehicle use and insurance costs. These flexible controls for transportation expenditures are helpful in addressing biases that might arise due to time-varying differences across states in vehicle use patterns. Table 1 presents summary statistics for the outcome variables and main covariates used in my analysis. IV. Results a. Overall Effects of Reform on Insurance Cost and Take-Up Table 2 presents results from my main specifications linking tort reform and auto insurance expenditures. Column I reports coefficient estimates from a specification with no controls, column II adds household-level controls, and column III adds state-level controls. All specifications include state and year fixed effects. Across specifications, there is no consistent evidence of a relationship between implementation of caps on noneconomic damages or limits on JSL and consumer auto insurance costs, and these estimated 8

11 effects are sufficiently precise so as to rule out impacts of more than a few percentage points. The absence of an impact of damage caps may be attributable to the fact that cap levels are often set in reference to medical malpractice cases, and auto cases with non-economic damages that are sufficiently large to breach a cap are relatively rare. These findings do, however, contrast with those of Browne et al. (2004) and Asmat and Tennyson (2013), who find evidence of lower settlement amounts in states with punitive damage caps. Impacts of JSL limits are potentially moderated by the fact that JSL only comes into play in accidents involving multiple at-fault parties, which represent a minority of all accidents. There is evidence of a statistically significant 6% decline in auto insurance costs following collateral source reform, and a 12% decline in costs following no-fault repeal in my preferred specification (column III). For first-party bad faith torts, I do not observe a statistically significant change in costs, but this estimate is fairly imprecise, and I cannot preclude moderate (e.g. 10%) changes in costs associated with this reform. Even without specific insurance policy parameters, I can explain roughly 20% of the household-level variation in insurance expenditures in these regressions, largely due to the rich set of demand proxies included as controls. Because consumers have some ability to alter the cost of their auto insurance by changing the available coverages, deductibles, and policy limits, the declines measured above are best thought of as lower bounds on the effects of collateral source and no-fault reform. Standard models of utility maximization would predict that households might choose to consume some of the benefits of lower auto insurance prices in the form of better coverage. To the extent that consumers partially offset premium reductions by upgrading their policies, my estimates will understate the true gains to consumers from tort reform. The coefficients on the included covariates generally accord with intuition and are interesting in their own right. As expected, auto insurance expenditures grow with income, number of vehicles owned, number of drivers, and fuel expenditures--my proxy for vehicle use. Conditional on income and other characteristics, more highly educated householders spend more on auto insurance. Conditional on proxies 9

12 for individual demand, there is not a strong correlation between general state economic conditions and costs, nor is there a measurable relationship between certain types of safety legislation--such as graduated driver s licensing and primary seatbelt enforcement and consumer costs. Table 3 reports odds ratios from a logit regression where the outcome of interest is an indicator for whether a household had any insurance expenditures during the quarter, which is one proxy for whether or not a household has insurance. 14 Controls are the same as in the preferred specification from Table 2. None of the coefficients are statistically significantly different form unity, although the estimates for some reforms, such as collateral source reform, are somewhat imprecise. To the extent that these results can be interpreted as a quantity effect, it appears that tort reform does not have large effects on the equilibrium quantity of insurance purchased. Moreover, when combined with the results on expenditures, these results seem most consistent with an environment where collateral source reform and no-fault reform lower price and do not decrease quantity, which would imply that these reforms increase insurance supply. 15 b. Robustness Checks Table 4 presents results from a series of alterative regression models designed to explore the robustness of my findings to choice of sample and econometric specification. My first robustness check replicates the specification in column III of Table 2, but includes an additional set of state-specific time trends as controls. Although the coefficient on collateral source reform is not as precisely estimated and is therefore no longer statistically significant in this specification, it remains of comparable magnitude to the preferred specification, and the estimated effects of no-fault repeal are similar. 14 Because some policyholders pay premiums on an annual or semi-annual basis, some individuals who have insurance will not report expenditures in a given quarter. Although this would lead us to understate the absolute fraction of households with insurance, estimates based on relative changes in the fraction of households making payments would not be biased so long as payment scheduling practices are not correlated with tort reform status. Estimation using probit or a linear probability model yields similar results. 15 Effects on demand are more ambiguous. In theory, a reform could reduce demand for insurance by lessening the value of the product for consumers. With these data I cannot clearly distinguish a situation where demand is elastic, demand decreases, and supply increases from a situation where demand is inelastic and supply increases. 10

13 In theory, changes in the cost of insurance could alter consumer choices about whether to purchase cars or how much to drive. If such behavioral effects are present, it may be inappropriate to control for gasoline consumption or number of vehicles owned as I do in my preferred specification. Specification 2 in Table 4 omits any such potentially endogenous variables as controls and obtains very similar results to the baseline. Because effects of tort reform may differ for individuals who purchase less conventional policies, such motorcycle coverage, coverage for large numbers of vehicles, etc., in Specification 3 I confine the sample to households that own exactly one or two automobiles about twothirds of the overall sample. This specification also yields similar results. The baseline results flexibly model the effects of law changes to allow them to phase in at any time in the year following the change. In Specification 4, I test models that assume that the impacts of law changes are immediate. This alternative generates point estimates that are slightly smaller than the baseline but of similar statistical significance. In Specification 5, I limit the analysis to the 20 states most consistently included in the CEX throughout the entire sample period. Focusing on a more balanced sample of states the increases the salutary effect of collateral source reform, while the effect of no-fault repeal also remains negative and significant. As an additional check of the econometric specification, in the bottom row of Table 4 I use logged quarterly expenditures on life insurance rather than auto insurance as the outcome variable for the analysis. With the possible exception of bad faith reforms, life insurance premiums should not be affected by the reforms considered thus far in the paper, as these reforms affect only apply to situations where individual plaintiffs seek compensation for a third party following an injury. Thus, if the main specification correctly isolates the impacts of tort reform, one should not observe effects of reform in this regression. Alternatively, if there are unobserved shocks to the insurance industry that are correlated with the passage of reform, these placebo regressions the use life insurance premiums as an outcome might reveal a correlation between reform and life insurance costs, which would indicate that the DD approach is inadequate to identify the true effects or tort reform. 11

14 As shown in Table 4, none of the estimated coefficients on the various tort reforms is statistically significant, and the point estimates for all the reforms except bad faith reform (which could plausibly increase life insurance costs) are small in magnitude. This pattern provides some reassurance that the DD strategy can isolate the effects of reform from more general factors affecting insurance markets. For no-fault reform, I can also examine the dynamics of auto insurance expenditures around the reform period to assess whether my results are likely to reflect policy endogeneity or mean reversion rather than a true impact of reform 16. In Figure 1, I present coefficient estimates from a variant of eq. (1) where the impact of the reform is modeled more flexibly so as to allow variations in expenditures both before and after the reform. If no-fault is repealed as a result of temporary spike in costs and my measured effects simply represent mean reversion, one might expect to observe a pre-repeal trend in costs, but no such trend is apparent in the figure. Indeed, costs trend in states about to repeal no-fault are similar to costs in other states conditional on the covariates in the model, and I observe a steady decline in costs beginning at the point of repeal that stabilizes with the first few years following repeal, just as one would expect if cost changes are caused by repeal. c. Effects for Population Subgroups My results thus far present average effects of tort reform across the entire population. Policy discussions of the merits of reform often consider not only potential effects on average costs, but effects for particular subsets of the population, such as younger or lower-income drivers. Many prior studies of tort reform have focused on state-level average outcomes, and have thus been limited in their ability to consider whether tort reform has heterogeneous effects across different types of consumers. In Table 5, I present coefficient estimates from variants of (1) where the effects of tort reform have been allowed to differ across different segments of the population defined by income, marital status, 16 Most changes to the collateral source regime that I study arose due to Supreme Court invalidations of existing statutes, which seem less likely to be endogenous with respect to auto insurance costs, both because these decisions are likely driven by the legal facts of a particular case rather than the general business environment, and because many of the cases overturning collateral source reform involved injuries sustained in non-auto contexts. 12

15 race/ethnicity, age, and education. To the extent that tort reform disproportionately affects certain segments of the population, I should observe larger or smaller coefficients for particular subgroups as compared to the baseline. I also report p-values from statistical tests of the null hypothesis that the effects of tort reform do not vary across the subgroups defined for a particular characteristic. Table 5 demonstrates that the benefits of collateral source reform and no-fault repeal are felt fairly widely throughout the population, and the other reforms largely do not generate measureable benefits for drivers from particular demographic subgroups. 17 The one exception is no-fault reform, which appears to benefit middle- and older-age drivers more than younger drivers. Although the precise explanation for this differential effect remains unclear, it is possible that younger drivers pay less for PIP that older drivers due to the fact that they have lower wages. Alternatively, it may be the case that higher than average coverage gaps for health insurance among young adults make them more likely to purchase Med-Pay policies following a no-fault repeal, dampening the salutary effect of repeal on expenditures. d. Effects by Cost of Policy Many policy debates regarding the cost of auto insurance include discussions of consumers with basic or low-cost policies, under the premise that insurance affordability may be particularly salient for such consumers. Beyond looking at different income segments of the population, I can also examine whether the impacts of tort reform differ for those with low-cost policies versus those with more expensive policies. Reforms that generate cost savings for those with more basic policies may be viewed more favorably by some policymakers than reforms providing savings to those who are already able to afford substantial amounts of coverage. To estimate the impacts of no-fault reform and collateral source reform on individuals with different levels of expenditure on insurance, I estimate regressions analogous to eq. (1) but using a quantile regression framework, which allows me to observe the effects of changes in the tort environment 17 The finding that establishment of a damage cap is actually associated with a statistically significant increase in expenditures for households with lower educational attainment is not expected, but it could occur if the presence of caps increases demand for auto insurance. 13

16 at different points in insurance expenditure distribution. 18 Figure 2 plots coefficients from quantile regressions that represent the estimated effect of these reforms on premiums for those at the 10th through 90th percentiles of the expenditure distribution. 19 Figure 2 demonstrates that for both collateral source reform and no-fault repeal, policyholders with less expensive policies disproportionately benefit from reform. For collateral source reform, those in the lowest decile of spend roughly 10% less on insurance post-reform, as compared to a roughly 5% savings for other consumers. For no-fault repeal there is a clear gradient in effects, with larger percentage cost reductions for those with lower cost policies. Those with the least expensive policies save more than 15% following no-fault reform, versus roughly 7% for those with the most expensive policies. One potential explanation for the differential impact of no-fault repeal on consumers with basic policies has to do with the somewhat inflexible nature of no-fault required coverages in most states. To manage costs, consumers can adjust a variety of parameters of the typical policy, including the amount of the deductible, the policy limits, and the presence of optional coverages such as collision. However, because no-fault states require all policyholders to hold a minimum level of medical/wage loss insurance, in these states there is something akin to a fixed cost of holding policy equal to the value of the no-fault coverage. For consumers with basic policies, this fixed cost is likely to represent a significant fraction of their total policy costs, and removing this requirement thus may offer them a greater opportunity to lower their premiums in proportional terms. V. Conclusions A clear understanding of the effects of reform on consumer costs is an important ingredient in policy discussions surrounding tort reform, and this paper provides some of the first rigorous empirical evidence of such effects for auto insurance. I demonstrate that collateral source limits and no-fault repeal generate reductions in consumer auto insurance costs of 5-15%, while JSL reform, damage caps, and bad 18 Athey and Imbens (2006) provide a more detailed discussion of quantile differences-in-differences models. 19 The 10th percentile corresponds to $120 in auto insurance expenditures during a quarter, while the 90 th percentile represents $750 in quarterly expenditures. 14

17 faith reform do not measurably affect premium expenditures. The cost savings from collateral source reform and no-fault repeal accrue widely throughout the population, with savings observed among policyholders who vary in their age, educational attainment, and income. There are no measurable effects on insurance take-up, suggesting these policies increase the supply of insurance in the marketplace. The largest impacts of no-fault repeal and collateral source repeal, at least in percentage terms, are observed among those with low-cost policies. While consumer cost savings are one criterion that should be considered in evaluating tort reform proposals, a well-functioning tort system should balance the interests of insurers and their policyholders with those of injury victims. The reforms considered in this paper primarily shift the burden of losses following an injury across plaintiffs and insurers or auto insurers and other types of insurers. Reforms that reduce policyholders costs may still be undesirable from a social standpoint if these cost savings come at the expense of causing many plaintiffs to obtain inequitable compensation following an injury. 20 Alternatively, some reforms that do not generate measurable cost savings may still be justifiable on other grounds, such as fairness. Moreover, given that most of the policy changes under consideration here apply to other types of personal injury cases beyond auto cases, in assessing the merits of particular reforms, it is also important to consider how such reforms might affect costs and recovery following other types of injuries. Thus, these results do not offer a definitive indication of whether tort reform is good or bad, but rather offer important new information that can be used to better evaluate tort reform proposals and their likely effects on consumers and insurers. 20 Anderson et al. (2010) for example, demonstrate that while insurance costs are appreciably higher in no-fault states, auto crash victims in these states do also have a higher fraction of their economic losses reimbursed by auto insurance. 15

18 References Anderson, J.M., Heaton, P., & Carroll, S.J. (2010). The US Experience with No-Fault Automobile Insurance: A Retrospective. RAND MG-860. Santa Monica, CA: RAND Corporation. Asmat, D.P., & Tennyson, S. (2013). "Does the Threat of Insurer Liability for 'Bad Faith' Affect Insurance Settlements?" The Journal of Risk and Insurance, forthcoming. Athey, S., & Imbens, G.W. (2006). "Identification and Inference in Nonlinear Difference-in-Differences Models." Econometrica, 74(2), Avraham, R. (2011). Database of State Tort Law Reforms, 4 th Edition. Law and Econ Research Paper No. 184, University of Texas School of Law. Avraham, R., Dafny, L.S., & Schanzenbach, M.M. (2012). "The Impact of Tort Reform on Employer- Sponsored Health Insurance Premiums." Journal of Law, Economics & Organization, 28(4), Browne, M.J., Pryor, E.S., & Puelz, B. (2004). "The Effect of Bad-Faith Laws on First-Party Insurance Claims Decisions." Journal of Legal Studies, 33(2), Browne, M.J., & Schmit, J.I. (2008). "Litigation Patterns in Automobile Bodily Injury Claims : Effects of Time and Tort Reforms." Journal of Risk and Insurance, 75(1), Carvell, D., Currie, J., & MacLeod, W.B. (2012). "Accidental Death and the Rule of Joint and Several Liability." RAND Journal of Economics, 43(1), Crain, N.V., Crain, M.W., McQuilan, L.J., & Abramyan, H. (2009). Tort Law Tally: How State Tort Reforms Affect Tort Losses and Tort Insurance Premiums. San Francisco, CA: Pacific Research Institute. Cross, F.B. (2011). "Tort Law and the American Economy." Minnesota Law Review, 96(1), Currie, J., & Macleod, W.B. (2008). "First Do No Harm? Tort Reform and Birth Outcomes." Quarterly Journal of Economics, 123(2), Eisenberg, T. (2012). "The Empirical Effects of Tort Reform." Forthcoming in Jennifer Arlen, Ed, Research Handbook on the Economics of Torts. Edward Elgar. Eisenbrey, R. (2006). Tort Costs and the Economy: Myths, Exaggerations, and Propaganda. Washington DC: Economic Policy Institute. Grace, M.F., & Leverty, J.T. (2012). "How Tort Reform Affects Insurance Markets." Journal of Law, Economics, and Organization, forthcoming. Hawken, A., Carroll, S.J., & Abrahamse, A. (2001). The Effects of Third-Party Bad Faith Doctrine on Automobile Insurance Costs and Compensation. RAND MR-1199-ICJ. Santa Monica, CA: RAND Corporation. 16

19 Helland, E., & Showalter, M. H. (2009). "The Impact of Liability on the Physician Labor Market". Journal of Law and Economics, 52(4), Hinton, P.J., & McKnight, D.L. (2011). Creating Conditions for Economic Growth: The Role of Legal Environment. New York: NERA Economic Consulting. Hunter, J.R., & Doroshow, J. (2002). Premium Deceit - The Failure of Tort Reform to Cut Insurance Prices. New York: Center for Justice and Democracy. Hyman, D.A., Silver, C.M., Black, B.S., & Paik, M. (2012). "Does Tort Reform Affect Physician Supply? Evidence from Texas." Law and Economics Research Paper 12-11, Northwestern University School of Law Insurance Information Institute. (2013). "Auto Insurance - Costs and Expenditures." From accessed 7/22/2013 Insurance Resource Council (IRC). (2008). Auto Injury Insurance Claims: Countrywide Patterns in Treatment, Cost and Compensation. Malvern, PA. Insurance Resource Council. (2011). The Impact of Third-Party Bad-Faith Reforms on Automobile Liability Insurance Costs in West Virginia. Malvern, PA. Kessler, D., & McClellan, M. (1996). "Do Doctors Practice Defensive Medicine?" Quarterly Journal of Economics, 111(2), Kessler, D., & McClellan, M. (2002). "How Liability Law Affects Medical Productivity." Journal of Health Economics, 21(6), Klick, J., & Stratmann, T. (2007). "Medical Malpractice Reform and Physicians in High-Risk Specialties." Journal of Legal Studies, 36(S2), S121-S142. Loughran, D.S. (2001). The Effect of No-Fault Automobile Insurance on Driver Behavior and Automobile Accidents in the United States. RAND MR-1384-ICJ. Santa Monica, CA: RAND Corporation. Matsa, D. A. (2007). "Does Malpractice Liability Keep the Doctor Away? Evidence from Tort Reform Damage Caps." Journal of Legal Studies, 36(S2), S143-S182. Moller, E. (1996). Trends in Civil Jury Verdicts Since RAND MR-694-ICJ. Santa Monica, CA: RAND Corporation. Morrisey, M.A., Kilgore, M.L., & Nelson, L. (2008). "Medical Malpractice Reform and Employer- Sponsored Health Insurance Premiums." Health Services Research, 43(6), Rubin, P.H., & Shepherd, J.M. (2007). "Tort Reform and Accidental Deaths." Journal of Law & Economics, 50(2), Shepherd, J.M. (2013). "Products Liability and Economic Activity: An Empirical Analysis of Tort Reform's Impact on Businesses, Employment, and Production." Vanderbilt Law Review, 66(1),

20 Sloan, F.A., & Shadle, J.H. (2009). "Is There Empirical Evidence for 'Defensive Medicine'? A Reassessment." Journal of Health Economics, 28(2), Viscusi, W.K., Zeckhauser, R.J., Born, P., & Blackmon, G. (1993). "The Effect of 1980s Tort Reform Legislation on General Liability and Medical Malpractice Insurance." Journal of Risk and Uncertainty, 6(2),

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