THE UNIVERSITY OF MICHIGAN LAW SCHOOL

The Law and Economics Workshop

Presents

THE DEMOGRAPHICS OF TORT

REFORM: WINNERS AND LOSERS

by

Joanna Shepherd, Emory Paul H. Rubin, Emory

THURSDAY, March 29, 2007 3:40-5:30

Room 236 Hutchins Hall

Additional hard copies of the paper are available in Room 972LR or available electronically at http://www.law.umich.edu/centersandprograms/olin/workshops.htm

The Demographics of Tort Reform:

Winners and Losers

Paul H. Rubin Emory University Dept. of Economics and School of Law

Joanna Shepherd

Emory University School of Law*

Abstract Tort reforms that limit certain types of damages may disproportionately affect the

types of plaintiffs most likely to receive those damages. Studies have shown that many tort reforms disproportionately reduce compensation to women, children, the elderly, disadvantaged minorities, and less affluent people. Theory indicates two possible affects of the reduced compensation. First, the reduced compensation may result in reduced deterrence if tortfeasors shift their efforts at risk reduction to accidents more likely to be suffered by victims with higher expected damages awards and relatively greater access to legal representation. Second, the groups with disproportionately reduced compensation under tort reform might actually disproportionately benefit from tort reform if they benefit more from increased numbers of doctors in tort-reform states. Using the most accurate, comprehensive data on medical malpractice tort reforms and state-level data from 1980-2000, we examine the disproportionate effect of tort reforms on different demographic groups. We find that the impact of tort reform varies substantially among demographic groups. Most notably, the net effect of tort reform is to decrease male death rates, but to increase female death rates. Thus, several reforms may not only disproportionately reduce compensation to females, they are also associated with disproportionately more deaths. *Contact info: Paul H. Rubin, Department of Economics and School of Law, Emory University Atlanta, GA 30322; 404-931-0493; prubin@emory.edu and Joanna M. Shepherd, Emory University School of Law, Gambrell Hall, Atlanta, GA 30322-2770; (404) 727-8957; jshepherd@law.emory.edu. The authors would like to thank seminar participants at Northwestern University School of Law, Michigan University School of Law, and Emory University School of Law, and at the annual meetings of the American Law and Economics Association, the European Association of Law & Economics, and the South-Eastern Association of Law Schools. We also appreciate helpful comments from Robert Ahdieh, Bill Buzbee, Michael Kang, Jonathan Klick, Kay Levine, Ani Satz, Robert Schapiro, George Shepherd, and Frank Vandall. We also thank Conny Chen for valuable research assistance.

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The Demographics of Tort Reform: Winners and Losers

1. INTRODUCTION

In a previous article, we have shown that some tort reforms reduce accidental death rates while other reforms increase accidental death rates (Rubin and Shepherd, 2007). However, tort reform may not affect all segments of society equally. Differences exist among the types of damages awarded to different segments of the population. Because tort reforms limit certain types of damages relative to others, reforms may disproportionately impact the groups that would otherwise be most likely to receive the capped damages. For example, because women, children, the elderly, disadvantaged minorities, and the poor have, on average, relatively lower incomes, more of their total damage awards are in the form of noneconomic damages. Thus, caps on noneconomic damages are likely to reduce compensation to these groups disproportionately.

The reduced compensation may, in turn, result in reduced deterrence if potential tortfeasors shift their efforts at risk reduction to accidents more likely to be suffered by victims with higher expected damages. Because tort reform limits the damages that these groups will receive if they are injured, potential tortfeasors will expend less effort attempting to avoid injuring them. This shift may be exacerbated because reduced damage payments may also reduce access to legal representation; attorneys may be less willing to represent those who are eligible for smaller damage payments. Thus, women, children, the elderly, disadvantaged minorities, and the poor could lose again, as they are injured more and are less able to find lawyers to help them obtain compensation for their injuries.

However, it is possible that tort reform could also have the opposite effect: the groups with disproportionately reduced compensation under tort reform might actually disproportionately benefit from tort reform. Numerous studies have shown that tort reform increases the supply of physicians in tort reform states. Women, children, the elderly, disadvantaged minorities, and the poor may disproportionately benefit from more doctors, especially ER doctors and OB/GYNs, whose location decisions are most strongly influenced by tort reform.

In this paper, we conduct the first empirical analysis of whether the groups with disproportionately reduced compensation under tort reform are also disproportionately victimized, or whether they disproportionately benefit. Using the most accurate, comprehensive, data on medical malpractice tort reforms and state-level data from 1980-2000, we examine the effect of tort reforms on the non-motor vehicle accidental death rates of different demographic groups: women, children, the elderly, and African-Americans.

We first perform group-specific estimations that allow computation of numbers of deaths so that we can understand the absolute effects of tort reform on each demographic group. Then, we test whether the differences in tort reform’s impact among demographic groups are statistically significant using both standard differences-in-differences estimations and differences-in-differences-in-differences estimations that control for simultaneity bias.

The results show that individual reforms affect different demographic groups differently. We find that caps on noneconomic damages and reforms to punitive damages

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disproportionately increase female death rates relative to males, but caps on total damages disproportionately reduce female death rates. Although reform of joint-and-several liability disproportionately increases African-American death rates, reforms to punitive damages disproportionately decrease African-American death rates. Caps on noneconomic damage disproportionately increase the death rates of children under five.

The total impact of tort reform also varies substantially among demographic groups. Most notably, the net effect of tort reform is to decrease male death rates, but increase female death rates. Thus, several reforms may not only disproportionately reduce compensation to females, but they are also associated with disproportionately more deaths.

The paper proceeds as follows. In section 2, we discuss the literature on tort reform’s disproportionately reduced compensation to women, children, the elderly, and the poor. Section 3 discusses the possible impacts of tort reforms on these groups’ accident rates. We discuss both the specific tort reforms in our data and their likely impacts, in section 4. Section 5 presents empirical tests and results, and section 6 concludes.

2. DISPROPORTIONATE COMPENSATION UNDER TORT REFORM

By limiting certain types of damages relative to other damages, tort reform may disproportionately reduce damage payments to specific segments of the population. The existing literature suggests that the groups that might be disproportionately harmed include women, children, the elderly, and less affluent members of society, including many disadvantaged minorities. Several prominent legal scholars have argued that different types of damages have different relative importance for different demographic groups (Finley, 2004; Finley, 1997; Koenig and Rustag, 1995; Cassels, 1992; Chamallas, 1994; Rustad, 1996; Donald, 2005; Hollander-Blumoff and Bodie, 2005; Rustad and Koenig, 2002). The most important of these is noneconomic damages which are relatively more important for women, children, the elderly, and the poor. Thus, caps on these damages will disproportionately reduce compensation for these groups.

Former President Bill Clinton addressed tort reform’s disproportionate harm: “This provision is all the more troubling because it unfairly discriminates against the most vulnerable members of our society--the elderly, the poor, children, and nonworking women--whose injuries often involve mostly noneconomic losses. There is no reason for this kind of discrimination. Noneconomic damages are as real and as important to victims as economic damages. We should not create a tort system in which people with the greatest need of protection stand the least chance of receiving it.”1

We now discuss the impact of reforms both on the damage awards that individual

demographic groups receive, as well as on the groups’ access to legal representation.

2.1. FEMALES Tort reforms that cap noneconomic damages reduce compensation to females

more than to males because a much greater proportion of female’s damage awards are in the form of noneconomic damages. Because women, on average, have lower incomes than men, they have correspondingly less economic loss and relatively more 1 Veto Message from the President, 142 Cong. Rec. H4425 (daily ed. May 6, 1996).

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noneconomic loss. (Schlegel, 2002). Moreover, women more frequently bring claims for emotional damages and reproductive wrongs, both noneconomic losses (Ruda, 1993).

Similarly, caps on punitive damages may disproportionately reduce compensation to women: “Punitive damage awards have clustered around contraceptive and cosmetic products, including: IUDs; breast implants; sexual assault by health care providers; unnecessary reproductive surgery, such as hysterectomies, performed on women without their consent; grossly deficient cosmetic surgery; and abuse or neglect of elderly women in nursing homes” (Finley, 1997). Thus, general punitive damage caps, and especially caps when a drug or device has received pre-market approval by the FDA, may disproportionately harm the many women injured by reproductive drugs and medical devices (Finley, 1993; Koenig and Rustag, 1995).

Although the empirical evidence is mixed, several studies do find that tort reform lowers women’s damage awards more than men’s awards (Finley, 2004; Pace et al., 2004; Kinney et al., 1991).2

Tort reform may not only disproportionately reduce the compensation to women, it may also disproportionately limit their access to the legal system, further limiting their ability to obtain compensation. Evidence suggests that attorneys may disproportionately refuse to represent female plaintiffs on a contingency fee basis because the potential recovery is less after tort reforms that cap noneconomic and punitive damages (Schlegel, 2002; Zimmerman and Hallinan, 2004; Sharkey, 2005; Daniels and Martin, 2006).

2.2. THE YOUNG AND THE ELDERLY

The young and the elderly may also be disproportionately penalized by limits on noneconomic damages since retirees and children suffer no income loss from life-altering injuries (Rustad, 2005; Donald, 2005). Because few elderly people or children lose wages after physical injury, noneconomic damages are critical to their compensation. Indeed, some empirical studies show that noneconomic damage caps have disproportionately reduced the damage awards to children and the elderly (Finley, 2004; Pace et al., 2004).

Moreover, scholars argue that, in states with caps on noneconomic damages, the elderly and parents whose children die as a result of medical malpractice have difficulty finding lawyers willing to take their cases, since the majority of the compensation will be for nonpecuniary losses (Zimmerman and Hallinan, 2004; Sharkey, 2005).

2.3. THE LESS AFFLUENT

Similarly, tort reform may disproportionately reduce the compensation for less affluent people. The absolute level of the wages of the less affluent suffers less from physical injury than for highly compensated people; a person who earns $20,000 per year can suffer wage loss of at most $20,000 per year. Thus, more of the total damage awards to lower income people will be in the form of noneconomic loss. Thus, caps on noneconomic losses will disproportionately reduce compensation to the less affluent.

This is especially true for racial minorities that earn, on average, lower incomes than their white counterparts. One authority argues that “Working class and poor people, regardless of their race, depend completely on their minds and bodies, rather than 2 But see Studdert et al. (2004) who find that women and the elderly are no more heavily burdened by caps than their male and younger counterparts, even when the reductions are examined in proportional terms.

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property ownership, to survive. They lack sufficient disposable income to purchase enough insurance to protect themselves in the event of serious personal injury. Since working-class people -- and that includes most people of color -- have no means of supporting themselves in the event of injury other than receiving government support, the tort system is important for the preservation of both economic well-being and human dignity” (McClellan, 1996).

Like women, and the very young and old, the poor will undoubtedly experience restricted court access. As caps on noneconomic damages and punitive damages greatly reduce plaintiffs’ recoveries, lawyers will be less likely to represent poor plaintiffs, where a contingency fee is the only means of attorney compensation (Cady, 1997; Schlegel, 2002).

3. POSSIBLE IMPACTS OF TORT REFORM

Theory suggests that tort reform could have either of two impacts on accidental deaths. First, reforms could increase accidental deaths as tortfeasors internalize fewer of the costs of externalities, and thus, have less incentive to reduce the risk of accidents. Second, tort reforms could decrease accidental deaths as lower expected liability costs result in increases in the supply of doctors, reductions in the prices of risk-reducing products, and as consumers take additional precautions to avoid accidents.

As we will discuss, previous studies have shown that doctors do tend to move to states that have adopted tort reforms. Other studies have shown that the benefit from more doctors offsets the reduction in deterrence for some tort reforms, especially caps on noneconomic damages and reforms to punitive damages, producing decreases in accidental deaths.

In contrast to the last section, which discussed the disproportionate reduction in damages awards that tort reforms impose on certain at-risk groups, this section discusses whether tort reform disproportionately affects the groups’ number of accidental deaths. Theory suggests that tort reform might have either of two contrasting impacts on the groups: tort reform could either disproportionately benefit or disproportionately harm them.

3.1. DISPROPORTIONATE HARM TO AT-RISK GROUPS

Tort reform might disproportionately affect accidental deaths for at-risk groups for two reasons. First, the disparate impacts of tort reform might not only reduce compensation for these groups, it may also change potential tortfeasors’ relative efforts at deterrence, so increasing accidental deaths for the group. Second, even if tort reforms do not increase accidental deaths for at-risk groups, they may reduce accidental deaths only for other groups; if tort reforms have benefits in reducing accidental deaths, the at-risk groups may not share in the benefits.

3.1.1 SHIFT IN RELATIVE DETERRENCE EFFORTS

All tort reforms that lower damages may decrease deterrence as tortfeasors internalize less of the costs of externalities, and thus, have less incentive to reduce the risk of accidents. However, if reforms reduce damages to certain groups more than others, then tortfeasors may shift their deterrence efforts to target accidents more likely to be suffered by victims with higher expected damages.

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Similarly, many tort reforms have been found to limit access to the legal system among clients with low expected damage payments. Because certain reforms, and especially caps on noneconomic damages, disproportionately lower the expected damage payments for women, children, the elderly, disadvantaged minorities, and the poor, these groups may be disproportionately excluded from legal representation. The effect of this exclusion is an even further reduction in expected damages that may cause even greater shifts in deterrence efforts away from the at-risk groups.

Thus, regardless of whether these groups have disproportionately reduced compensation or reduced legal representation, relative deterrence may change after tort reform. That is, doctors and hospitals may devote more resources to reducing medical malpractice of white, affluent, male patients than medical malpractice of females, children, the elderly, and the poor.

Numerous studies have shown that gender and racial disparities exist in the treatment of many medical conditions. Females and minorities have been found to receive worse care for heart conditions (Vaccarino, et al., 2005; Hollenbeak, et al., 2006; Jha et al., 2005; Johnson et al., 1996; Petticrew, McKee, and Jones, 1993; Lee, 2000), brain injury treatment (Bazarian, et al., 2003), STD testing (Garfinkel and Blumstein; 1999), cancer treatment (McFarlane, Feinstein, and Wells, 1986; Austin, Romney, and Goldsmity, 1992; Lydiatt, 2002), treatment for renal disease (Kjellstrand and Logan, 1987; Alexander and Sehgal, 1998), and HIV treatment (Gebo, et al., 2005). Several of studies have found unequal treatment in emergency rooms (Cydulka, et al., 2005; Pezzin, Keyl, and Green, 2007; Bazarian, et al., 2003; Garfinkel and Blumstein; 1999).

If differences in care already exist, it is plausible that tort reform’s reduction in expected damages for at-risk groups could exacerbate the differences in medical care. If it does, tort reform could disproportionately harm females, children, the elderly, and the poor.

3.1.2. DISPROPORTIONATE BENEFITS TO NON-AT-RISK GROUPS

Tort reform might disproportionately benefit non-at-risk groups. As we now discuss, studies show that tort reform increases the supply of doctors in a state. However, the new doctors tend to provide types of care that disproportionately benefit non-at-risk groups. One testable hypothesis is that tort reform would thus lead to disproportionately greater reductions in death rates for non-at-risk groups than for at-risk groups.

Studies show that tort reform influences the location decisions of many doctors, including ER doctors. Several studies have found that different types of tort reforms have lowered liability costs by decreasing both lawsuits filed and damages awarded (Brown and Puelz, 1999; Yoon, 2001; Avraham, 2007). Many studies find that tort reforms that reduce liability costs lower the cost of both medical malpractice and general liability insurance (Viscusi, et al., 1993; Born and Viscusi, 1994, 1998; Born, 2005; Viscusi and Born, 2005; Zuckerman, Bovbjerg, and Sloan, 1990; Mello, Studdert, and Brennan, 2003; Studdert, Mello, Brennan, 2004; Thorpe, 2004).

These decreased insurance premiums have been found to have great influence on doctors’ location decisions. For example, Klick and Stratmann (2003) find that tort reforms, in general, lead to increased numbers of physicians in a state. Mello and Kelly (2005) find that many physicians, including emergency room doctors, decide not to locate in a jurisdiction (in their case, Pennsylvania) because of high malpractice premiums. In

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fact, malpractice costs were listed as the primary reason that physicians left Pennsylvania; indeed, this reason was listed three times more than any other factor. Kessler, Sage, and Becker (2005) find an increase in the number of physicians, and especially emergency medicine physicians, in states that have adopted tort reform.

Similar studies have found that high malpractice premiums affect doctors’ willingness to practice various high-risk procedures. For example, Mello and Kelly (2005) find that physicians that do not leave states with high malpractice premiums are less likely to practice high-risk specialties, including trauma care. Dranove and Gron (2005) find that high malpractice premiums have driven neurosurgeons to perform fewer brain surgeries. Brooks, et al. (2004) find that high medical malpractice premiums have caused 52% of Florida physicians to decrease hospital-based surgical procedures, 46% of physicians have reduced emergency department coverage, and 42% of physicians have reduced endoscopic procedures. Over 78% of general surgeons claimed to have eliminated services they provide, and 74% of surgical specialists eliminated procedures. Avoiding high medical malpractice premiums was listed as the most important factor for doctors that eliminated services. In a survey of Pennsylvania physicians, Mello et al. (2005) found that 83% of specialists reported increases in waiting times for specialist care or surgery and 82% of physicians reported increases in the waiting time for emergency department care. Moreover, they found that over one-third of Pennsylvania doctors expected to retire or relocate their practices out of state within two years, citing malpractice premiums as a driving force in their decision.

In addition, data show that males have more injury-related emergency department visits than females (McCaig and Nawar, 2006, at 21). Thus, they may be more harmed from a shortage of ER doctors, and disproportionately benefited from increases in ER doctors. Results that show disproportionate benefits for males from tort reform could result from males’ disproportionate benefit from increases in the supply of doctors.

Thus, whether the disparate impacts of tort reform induces tortfeasors’ to shift their relative efforts at deterrence, or the non-at-risk groups disproportionately benefit from tort reform, we may see disproportionately more deaths among the at-risk groups after tort reform.

3.2. DISPROPORTIONATE BENEFITS TO AT-RISK GROUPS

However, the opposite impact might also occur. At-risk groups could disproportionately benefit from tort reform that increases doctor supply.

The previously discussed studies found increases in the number of doctors in tort-reform states and, in non-reform states, reductions in medical procedures among physicians trying to avoid high medical malpractice premiums. Increases in the number of doctors and procedures after tort reform could disproportionately benefit minorities, who, compared to non-minorities, tend to lack access to care. (Laditka and Laditka, 2006; Bethell, Lansky, and Fiorillo, 2001). An increase in physician supply after tort reform could reduce the existing access-to-care problems among minorities.

This effect may be even more pronounced in emergency rooms, where financial constraints and limited options cause a disproportionate number of minorities to seek medical care in emergency departments (EMPATH, 2004; McCaig and Nawar, 2006, at 14). That is, because minorities utilize emergency departments and physicians more than

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whites, they may disproportionately benefit from increases in emergency physicians and procedures.

Moreover, in states without tort reforms, many doctors may refuse to see patients with Medicare or Medicaid because the money they receive from treating these patients may not be worth the risk of liability and high damages. During the 1990s, Medicare payments were 71% of private insurer payments and Medicaid payments were only 45% of private insurer payments (Medicare Payment Advisory Commission, 2005; Zuckerman, et al., 2004). Although the evidence is mixed, Rosenblatt, et al. (1991) and Rosenblatt, Whelan, and Hart (1990) argue that high malpractice premiums may contribute to the barriers to care that exist for Medicaid patients.3

Women may also disproportionately benefit from tort reforms that increase their access to OB/GYNs. Numerous studies have found that tort reform increases the supply of OB/GYNS and the procedures they perform. For example, Donlen and Puro (2003) find that high malpractice premiums led several OB/GYN practices in New Jersey to stop delivering or caring for high-risk babies, stop performing surgical procedures, and stop delivering babies altogether. In a survey of Florida physicians, Brooks et al. (2004) found that over 61% of obstetrics physicians had decreased or eliminated vaginal deliveries and 53% had decreased cesarean sections. Mello and Kelly (2005) find that many OB/GYNs, decided to either leave Pennsylvania, or reduce the scope of their practice because of high malpractice premiums. Rosenblatt et al. (1991) find evidence in four states that is consistent with the theory that tort reform decreases the rate at which physicians give up obstetric practice.4

4. SPECIFIC TORT REFORMS In the empirical section of this paper, we examine the relationship between

accidental death rates and several different tort reforms that apply in medical malpractice cases. The tort reform data is from the Database of State Tort Law Reforms, the most current, comprehensive dataset available on state-level tort reforms. This data avoids many of the problems with other tort reform datasets, namely: missing reforms, erroneously coded effective dates of reforms, and missing dates on unconstitutionality rulings (Avraham, 2006).

We explore the impact of six tort reforms on accidental death rates. These reforms apply to medical malpractice cases and are among the most common reforms enacted in the states. Moreover, most of the reforms appear in federal malpractice bills recently debated in Congress.5 3 But see Cunningham and Nichols (2005) who argue that the association between Medicaid reimbursement and access to care is weak. 4 Tort reform could also disproportionately benefit the at-risk groups if the reforms lower prices for risk-reducing goods and services. Because the elderly and the poor would be disproportionately harmed by high prices, they should also disproportionately benefit from low prices that enable them to buy safer products. Studies have established that lower liability costs result in lower prices; for example, Manning (1994; 1997) finds that that reductions in liability costs result in lower prices for both vaccines and prescription drugs. However, because these effects would likely be national in scope, we may not detect them in this study which is based on state level data. 5 The most recent federal bills (109 H.R. 5 and 109 S.22) included statute of limitations on filing medical malpractice lawsuits, a $250,000 cap on noneconomic damages, abolition of joint-and-several liability, contingent fee limitations, collateral source rule abolition, a clear-and-convincing evidence standard for punitive damages, a $250,000 cap or 2x compensatory damages cap on punitive damages, periodic

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A. Joint and several liability. Reforms to joint-and-several liability (JSL) of medical malpractice defendants are the most common reforms passed in the states. Forty-one states have reformed their JSL rules. Before reforms, a plaintiff could recover the full cost of her injury from any party that was partially responsible for the injury, no matter how small the party’s responsibility. Essentially, this allowed plaintiffs to collect from “deep pockets” even if they were only marginal contributors. Although the standard rule protects the rights of plaintiffs to be fully compensated, it often fails to distribute liability equitably among defendants. Most reforms to the standard JSL rules involve some sort of proportionate liability reform that limits exposure for those who played only a small part in causing the injury.

These reforms could especially benefit medical malpractice defendants like emergency room physicians. Medical malpractice by an ER doctor typically follows an injury that first sent the victim to the hospital. Before reforms, ER doctors and hospitals would most likely be the deep pockets that would end up paying for the entire injury, even if they were only responsible for a small proportion of the entire injury. After the reforms, the ER doctors and hospitals would be responsible for a smaller percentage. Thus, JSL reforms may especially help the demographic groups that disproportionately use emergency departments for injury-related visits: males and African-Americans (McCaig and Nawar, 2006, at 21).

B. Caps on noneconomic damages. The second reform we consider is caps on noneconomic damages in medical malpractice cases, enacted by 23 states. Noneconomic damages are damages for nonpecuniary losses such as pain and suffering, loss of consortium, emotional distress, and other intangible losses. As previously discussed, these caps may disproportionately affect females, the less affluent, children, and the elderly, who suffer a larger proportion of their overall injuries in the form of noneconomic damages.

We also consider reforms to punitive damages. Punitive damages are awarded not to compensate plaintiffs, but to punish defendants for intentional and malicious conduct and to deter future conduct. Punitive awards are infrequent, but have increased in frequency and size in recent years. For example, in a study of punitive damage awards in State courts in the Nation’s 75 largest counties in 2001, punitive damage awards were only awarded in 15 out of 1,156 medical malpractice cases, or 4.9% (Cohen, 2005). However, in one-third of the medical malpracitce cases—a larger percent than for any other type of case—punitive damages exceeded $1 million, and in two of the cases, punitive damages exceeded $10 million. In most states, reforms to punitive damages have taken one of two forms: either caps on punitive damages or higher evidence requirements before punitive damages are awarded. We combine these into one tort reform variable.

As previously discussed, punitive damage reforms may disproportionately affect women if they are clustered around contraceptive and cosmetic products (Finley, 1997). They could also disproportionately affect African-Americans, because the caps may have the largest impact in largely African-American areas. Researchers have found that civil trial damage awards are significantly higher in counties with large African-American areas. This effect is especially strong in medical malpractice cases where a one percent payments for future damages exceeding $50,000, and drug manufacturer immunity for FDA-approved drugs.

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increase in the African-American population increases medical malpractice awards by $36,000 (Helland and Tabarrok, 2006). Thus, caps on punitive damages (and noneconomic damages) will result in a larger reduction of damage awards in largely African-American areas. Because doctors, and especially ER doctors, seem to migrate to states that have adopted tort reforms, a cap on punitive damages that has a greater impact in African-American areas may cause a disproportionate increase in doctors in African-American areas, and lead to a disproportionate benefit to African-Americans.

C. Reform of the collateral source rule. Collateral source rules prevent the admission of evidence at trial that shows that a plaintiff’s losses have been compensated by other sources, such as insurance or workers’ compensation. Such rules promote efficient deterrence by requiring a tortfeasor to pay damages even when victims have received payments from a source other than the tortfeasor. However, proponents of tort reform claim that collateral source rules promote double recovery and result in higher insurance premiums.

Reforms to collateral source rules include allowing evidence of collateral source payments or completely offsetting awards by the amount of collateral source payments. The reforms may be especially relevant in medical malpractice cases where the reforms would prevent an injured party from recovering damages from doctors or hospitals if they have already collected benefits from their own health insuror.

Some reforms give the source of collateral payments (a health insurance company, for example) a right of subrogation. This allows the collateral source to collect from the tortfeasors, so that there is no double compensation to victims, but tortfeasors are still held liable for the total harm. However, other collateral source reforms do not give collateral sources a right of subrogation so that defendants pay only the portion of the total harm that is not paid for by the collateral source.6

D. Allowing periodic payments. Periodic Payment reforms allow defendants to pay large awards for future damage in periodic installments. Only future damage awards above some threshold, often $200,000, are allowed to be paid in periodic installments. This reform benefits defendants who can purchase an annuity that will generate the periodic payments. Moreover, if the plaintiff dies before all of the periodic payments have been made, the defendant is typically relieved from making the rest of the payments.

E. Caps on total damages. Finally, we include reforms that cap total damage payments in medical malpractice cases. Although these reforms are enacted less frequently than the others, they may have the greatest impact because they cap all damages, not just the noneconomic or punitive portion of damages. Typical cap amounts on total damages range from $500,000 to $1,250,000. These caps may have the largest impact on affluent, white, males, who, on average, have the highest salaries, and thus, the highest damages for lost income. Thus, the caps may disproportionately reduce their damage payments.

5. EMPIRICAL ANALYSIS OF TORT REFORM

Next, we test empirically the relationship between tort reform and death rates that Section 3 explored theoretically. Figures 1-3 present the average accidental, non-motor

6 In California, for example, collateral sources have no right of subrogation: “No source of collateral benefits . . . shall recover any amount against the plaintiff nor shall it be subrogated to the rights of the plaintiff against a defendant” (Avraham, 2006, at 175).

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vehicle, death rates for different demographic groups in the United States from 1980 to 1998.7 Figure 1 presents the rates for African-Americans and non-African-Americans, figure 2 presents the rates for males and females, and figure 3 presents the rates for ages 4 and under, 5 through 64, and 65 and over.

The figures indicate that, although the accidental, non-motor vehicle death rate for African-Americans has steadily decreased since 1980, the rate for non-African-Americans increased after an initial decrease. The death rates for men have slightly decreased over this period, and the death rates for women have slightly increased. The death rates for people age 65 and over are about four times the death rates of other ages and have increased slightly between 1980 through 1998. In contrast, the death rates for people age 5 through 64 have remained constant, and the death rates for people age 4 and under have slightly decreased.

In this section, we first perform group-specific estimations that allow computation of real-world magnitudes of deaths so that we can understand the absolute effects of tort reform on each demographic group. Then, we test whether the differences in tort reform’s impact among demographic groups are statistically significant.

5.1 GROUP-SPECIFIC ESTIMATIONS AND REAL-WORLD MAGNITUDES

To explore the relationship between tort reform and individual demographic groups’ death rates, we use a state-level, panel data set from 1981-2000.8 First, we isolate the net effect of tort reform on each demographic group by estimating regressions of the form: (1) rate REFORM Z Xs t s t s t s t s t s t, , , , ,= + ⋅ + ⋅ + ⋅ + ⋅ + ⋅ +α β β β β σ β τ ε1 2 3 4 5 where rate is each demographic group’s accidental, non-motor-vehicle death rate in state s and year t. We estimate equation (1) for 8 separate demographic groups: males, females, non-African American, African American, under age 65, age 65 and over, age 5 and over, and age 4 and under.

REFORM includes six individual tort reform indicator variables that indicate whether a state has the relevant tort reform in effect that year. The tort reforms we include are: caps on noneconomic damages, reforms to punitive damages (either caps or higher evidence requirements), caps on total damages, reforms to the collateral source rule (that either require courts to offset awards by the amount of collateral source payments or permit the admissibility of evidence of collateral source payments), reforms to joint and several liability rules, and periodic payment reforms.

The vector Z includes state-level controls that are the same for all demographic groups in a given year: the unemployment rate, real per capita personal income, per capita alcohol consumption, and the number of hospital beds per capita.

The vector X includes state-level controls that are specific to each demographic group in each year. In the female and male regressions, X includes the percentage of each gender that is African American, the percentage of each gender that is age 4 and under, 7 We do not include motor vehicle death rates for several reasons. These death rates are about one-half of all accidental deaths (National Safety Council, 2004). But they are affected by many statutory changes in addition to tort reform, such as no-fault insurance laws (Cohen and Dehejia, 2004) and changes in speed limits. In a related paper, we are examining the effects of tort reforms on automotive deaths after adjusting for these changes. 8 Some of the variables are not available after 2000.

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and the percentage of each gender that is age 65 and older. In the African-American and non-African-American regressions, X includes four percentages: the percentages of each race that is male of any age, male between the ages of 15-24, any gender age 4 and under, and any gender age 65 and older. In the age 4 and under and age 5 and up regressions, X includes the percentage of people in each age category that are male, and the percentage that are African-American. In the age 65 and over/under age 65 regressions, X includes the percentage of people in each age category that are male, and the percentage that are African-American.

In equation (1), σs and τt represent state and year fixed effects. These variables capture systematic differences in death rates among states and year-specific effects on death rates. All regressions are weighted least squares with weights based on the relevant demographic group’s state population, and robust standard errors are used to compute t-statistics. The variables and sources are described in the Data Appendix, and Table 2 presents the summary statistics for each variable.

In Table 3, we present the coefficient estimates and 3 sets of t-statistics. Given the concerns raised by Bertrand, Duflo, and Mullainathan (2004) about serial correlation in difference-in-difference studies, we present three sets of t-statisitcs errors for each coefficient. The first are t-statistics computed from robust standard errors, which allow for heteroskedasticity. Next, we implement two of the serial correlation remedies suggested by Bertrand, Duflo, and Mullainathan. The second set of t-statistics are computed from Newey-West Heteroskedastic-Autocorrelation Consistent (HAC) standard errors, choosing the potential lag structure optimally, as described in Stock and Watson (2003, pp. 505-506). Finally, we present t-statistics computed from standard errors clustered by state.

The results for the non-at-risk groups (males, non-African Americans, under age 65, and age 5 and over) are similar; caps on noneconomic damages and reforms to punitive damages are associated with decreases in death rates, whereas caps on total damages and collateral source reforms are associated with increases in death rates. The coefficients are all statistically significant, except for punitive damage reforms in the non-African American estimations. These results are consistent with the overall impacts of tort reform that we measured in our previous study (Rubin and Shepherd, 2007).9

In contrast, the results for the at-risk groups vary among tort reforms. Although the results between males and females are similar in sign and significance for caps on noneconomic damages, caps on total damages, collateral source reform, and punitive damage reform have no significant relationship with female death rates. The results between non-African Americans and African-Americans are similar in sign and significance for caps on total damages and collateral source reform. However, punitive

9 We used variations of these tort reform variables (our previous variables were not specific to medical malpractice) and different data sources for the tort reform data because the Database of State Tort Law Reforms was not yet available in the previous study. Nevertheless, we produced similar results: caps on noneconomic damages, a higher evidence standard for punitive damages, product liability reform, and prejudgment interest reform are associated with fewer accidental deaths, while reforms to the collateral source rule are associated with increased deaths. The positive coefficients on the collateral source reforms are also consistent with previous empirical findings Klick and Stratmann (2005) find that collateral source reform leads to higher infant mortality rates. Apparently for this variable, the reduction in deterrence seems to outweigh any change in the supply of doctors.

13

damages reform is associated with decreases in African-American death rates, whereas reform of joint and several liability is associated with increases in their death rates.

In the estimations of elderly death rates, only caps on total damages and collateral source reform are similar in sign and significance to the results for the under 65 group. In the estimations of death rates for people under age 5, only caps on total damages is similar in sign and significance to the results for people over 5, but joint and several liability reform has a significant negative relationship with under 5 death rates.

We can use the coefficients in Table 3 to estimate real-world magnitudes of the relationship between tort reforms and group-specific death rates; the results of these computations are presented in Tables 4 and 5.10 Table 4 presents the number of deaths in 2000 that were associated with tort reforms that existed that year. In contrast, Table 5 presents the total number of deaths associated with tort reforms in all states during the years 1980-2000.

As the tables show, caps on noneconomic damages and reforms to punitive damages are associated with net decreases in deaths across all groups, but caps on total damages and collateral source reforms are associated with net increases. Two at-risk groups show net effects that are the opposite of the corresponding non-at-risk groups: there is a net decrease in male deaths but a net increase in female deaths, and a net decrease in under 65 deaths but a net increase in over 65 deaths.

5.2 COMPARING TORT REFORM’S IMPACT

The previous results suggest that the overall impact of tort reform differs among groups. Next, we test whether the differences of each tort reform are statistically significant. We begin with standard differences-in-differences regressions, in which the differential impacts of tort reform on at-risk groups are captured in an interaction term. We estimate regressions of the form:

(2)rate REFORM demo REFORM Z X

demoi s t s t i s t s t i s t

i s t i s t

, , , , , , ,

, ,

*= + ⋅ + ⋅ + ⋅ + ⋅ +

⋅ + ⋅ + ⋅ +

α β β β ββ β σ β τ ε

1 2 3 4

5 6 7

where rate is demographic group i’s accidental, non-motor-vehicle death rate in state s and year t. We estimate four separate regressions. In the first regression, the dependent variable is either the female death rate or the male death rate in each state and year, and demo takes a value of 1 when it is the female death rate. In the second regression, the dependent variable is either the African-American death rate or the non-African- American death rate in each state and year, and demo takes a value of 1 when it is the African-American death rate. In the third regression, the dependent variable is either the death rate for children age 4 and under or the death rate for people over age 4, and demo takes a value of 1 when it is the death rate for children age 4 and under. Finally, in the last regression, the dependent variable is either the death rate for people over age 65 or the death rate for people younger than 65, and demo takes a value of 1 when it is the death rate for people older than 65.

REFORM includes the six tort reforms previously discussed. The demo*REFORM variable takes the value of 1 if both the demographic group’s state has

10 The coefficients in Table 3 are the partial derivatives of group-specific deaths per 100,000 population with respect to the enactment of each tort reform. Thus, the number of deaths associated with each tort reform is given by β1*(group-specific population in tort reform states/100,000).

14

the relevant tort reform in effect that year, and the demographic group is one of the four demographic groups that theory predicts may be disproportionately affected by tort reform: females, African-Americans, children age four and under, and people age 65 and over. If the deterrence-shifting effect dominates, we would expect to see a positive coefficient on the demo*REFORM variable. In contrast, if the access-to-doctors/reduced prices effect dominates, we would expect a negative coefficient on the demo*REFORM variable.

The vector Z once again includes the state-level controls that are the same for all demographic groups in a given year, and the vector X includes the state-level controls that are specific to each demographic group in each year. In equation (2), demoi, σs, and τt represent demographic group, state, and year fixed effects. These variables capture systematic differences in death rates among demographic groups in all states and years, systematic differences in death rates among states across all demographic groups and years, and year-specific effects on death rates across all states and demographic groups. All regressions are weighted least squares with weights based on the relevant demographic group’s state population, and robust standard errors are used to compute t-statistics.

The coefficient estimates and t-statistics for the tort reform and interaction variables are shown in Table 6. The negative and significant coefficients on the individual tort reform variables show that, in general, caps on noneconomic damages and reforms to punitive damages are associated with decreases in overall death rates. The positive and significant coefficients on collateral source reform and total damage caps suggest that these reforms are associated with increases in overall death rates.

The coefficients on the interactions between each tort reform variable and each demographic group show that three tort reforms produce a statistically significant difference in the impact on male and female death rates. Caps on noneconomic damages and reforms to punitive damages have a statistically significant, increasing effect on female death rates relative to males, but caps on total damages produce a statistically significant decreasing effect on female death rates compared to males. Only reform of joint-and-several liability produces a statistically significant difference in the impact on African-American and non-African American death rates: JSL reforms increase African-American death rates compared to rates for non-African Americans. Similarly, only noneconomic-damage caps produce a statistically significant difference in the impact on under 5 and over 5 death rates: caps on noneconomic damages have an increasing effect on under 5 death rates relative to over 5 death rates.

The differences-in-differences estimations allow us to measure the marginal differences among the death rates of at-risk groups, while controlling for two factors: contemporaneous changes within the states as observed in non-at-risk groups, and time effects that are unrelated to tort reform by using at-risk groups and non-at-risk groups in non-tort reform states as controls. However, the estimations do not allow for any sort of simultaneity between group-specific death rates and the adoption of tort reform. For example, if tort reform tends to be enacted in states with high female death rates in order to reduce damage awards, or if low female death rates lead to more tort reform because

15

there is less opposition from potential victims, then our results could suffer from simultaneity bias.11 To minimize simultaneity bias, we can control for systematic differences among states in the death rates of each demographic group. Thus, if female death rates drive the adoption of tort reform, controlling for systematic differences in female death rates between tort reform and non-tort reform states will minimize simultaneity bias and better isolate the effect of tort reform. To do this, we use the “differences-in-differences-in-differences” model introduced by Gruber (1994). This model not only measures differences across tort reform and non-tort reform states, and differences pre- and post-tort reform, but also measures differences among demographic groups in each state and year. Thus, we can control not only for death-rate trends specific to each demographic group, but also for idiosyncratic differences between group-specific death rates in tort reform and non-tort reform states.

We estimate the following differences-in-differences-in-differences model:

(3) rate Z X demo demo demo

demoi s t s t i s t i i s i t

s t i s t i s t

, , , , ,

, ,

( * ) ( * )( * ) ( * * )

= + ⋅ + ⋅ + ⋅ + + +

+ +

α β β β β σ β τβ σ τ β σ τ ε

1 2 3 4 5

6 7

where i continues to index each demographic group, s indexes states, and t indexes years. We continue to include the state-level controls common to all demographic groups with β1, and state-level controls that are specific to each demographic groups with β2.

We continue to control for systematic differences among each demographic group’s death rate across all states and years with β3. With β4, we control for systematic differences among states in the death rates of each demographic group in order to control for baseline differences in a demographic group’s death rates between tort reform and non-tort reform states. With β5, we also control for separate year effects for each separate demographic group to control for any yearly shocks that affect a specific demographic group’s death rates. With β6, we control for any time effect that is common to all individuals in tort reform states after the enactment of tort reform. That is, β6 controls for other unobservables that may affect both reforms and overall death rates so that our treatment effect can isolate the residual effect of tort reform on the group-specific death rate in isolation from the any other unobservables. The treatment effect, β7, isolates tort reform’s relationship with each at-risk group. This coefficient will capture variation in death rates specific to our less-compensated demographic groups (relative to the other demographic groups), in the tort 11 In our previous study, we investigated the possibility of simultaneity between tort reform and overall death rates. Reverse causation between overall death rates and tort reform could produce biased overall results, but it is unlikely that it could drive our differential results between at-risk and non-at-risk groups. We also concluded in the previous paper that reverse causality was not responsible for the overall results: “Previous papers have concluded that the primary drivers of tort expansion and tort reform are the relative power of lawyers and businesses in a state, not death rates (This literature is summarized in Rubin, 2005). If anything, increasing death rates should lead to more tort reform: increases in death rates increase tort claims which should motivate potential defendants to fight for tort reform to lower liability damage payments. However, this relationship would cause a bias in the opposite direction of our results: we should find a positive relationship between tort reform and death rates, not a negative one.” (Rubin and Shepherd, 2007, at text surrounding footnote 17. Moreover, IV estimations suggested that reverse causality was not driving our results.

16

reform states (relative to non-tort reform states), in years after tort reforms have been enacted (relative to before tort reform). Table 4 presents the coefficient estimates and t-statistics computed from robust standard errors. 12 The results indicate that, after controlling for baseline differences in the death rates of each demographic group among tort reform and non-tort reform states, several tort reforms continue to have statistically significant, disproportionate effects on at-risk groups. Both caps on noneconomic damages and reforms to punitive damages continue to have a statistically significant, increasing effect on female death rates relative to males. Likewise, caps on total damages continue to have a statistically significant decreasing effect on female death rates compared to males.

Joint-and-several liability reform continues to have a statistically significant, increasing effect on African-American death rates compared to non-African Americans. In addition, reforms to punitive damages now have a statistically significant, decreasing effect on African-American death rates compared to non-African Americans. Caps on noneconomic damage continue to have a statistically significant, increasing effect on under 5 death rates relative to over 5 death rates.13

Thus, while several reforms produce different effects on the death rates of at-risk groups compared to non-at-risk groups, the differences are statistically significant primarily only for females.

6. CONCLUSIONS Tort reforms that limit certain damages relative to others may disproportionately

impact the plaintiffs most likely to receive those damages. The results of several previous studies suggest that women, children, the elderly, disadvantaged minorities, and less affluent people find their expected damage payments disproportionately reduced by certain tort reforms.

This study goes beyond tort reform’s disproportionate effect on compensation, to explore whether tort reform also has a disproportionate effect on death rates. We find that caps on noneconomic damages and reforms to punitive damages disproportionately increase female death rates relative to males, but caps on total damages disproportionately reduce female death rates. Joint-and-several liability reform disproportionately increases African-American death rates, but reforms to punitive damages disproportionately decrease African-American death rates compared to others.

12 Although not shown in the tables for brevity, several of the control variables also have significant relationships with accidental death rates in most specifications. Per capita alcohol consumption, the percentage of the demographic group that is age 4 and under, the percentage of the demographic group that is age 65 and over, and the percentage of the demographic group that is African-American are positively associated with most accidental death rates. In contrast, per capita hospital beds, the percentage of the demographic group that is male, and the percentage of the demographic group that is male and age 15-24 are all negatively associated with most accidental death rates. 13 Although we do not report the results here for brevity, we performed several robustness checks of all of our specifications of equations (1), (2), and (3), 32 specifications in all. For example, we performed estimations with rates of all accidental deaths, including motor-vehicle deaths, as the dependent variable to test the robustness of our results to the type of accidental deaths used as the dependent variable. We also performed estimations using the log of death rates, instead of the level, as the dependent variable. Moreover, for equations (2) and (3) we also computed Newey-West heteroskedastic and autocorrelation-consistent standard errors. These different estimations produced results that were similar in sign, significance, and magnitude for most of the specifications.

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Caps on noneconomic damage disproportionately increase the death rates of children under 5 compared to others.

In sum, the overall impact of tort reform varies substantially among demographic groups. Most notably, the net effect of tort reform is to decrease male death rates, but increase female death rates. Thus, several reforms may not only disproportionately reduce compensation to females, they are also associated with disproportionately more deaths.

References

Alexander, GC and AR Sehgal. 1998. “Barriers to cadaveric renal transplantation among blacks, women, and the poor” 280 JAMA 1148-1152.

Austin, JH, BM Romney, LS Goldsmith. 1992. “Missed bronchogenic carcinoma: radiographic findings in 27 patients with a potentially resectable lesion evident in retrospect” 182 Radiology 115-122.

Avraham, Ronen. 2006. “Database of State Tort Law Reforms” (Northwestern Law & Economics Research Paper No. 902711)

---------------------. 2007. “An Empirical Study of the Impact of Tort Reforms on Medical Malpractice Settlement Payments,” Northwestern Law & Econ Research Paper No. 06-0.

Bazarian Jeffrey, Charlene Pope, Jason McClung, Yen Ting Cheng, and William Flesher. 2003. “Ethnic and racial disparities in emergency department care for mild traumatic brain injury,” 10 Academic Emergency Medicine 1209-17..

Born, Patricia H. and Kip Viscusi. 1994. “Insurance Market Responses to the 1980s Liability Reforms: An Analysis of Firm-Level Data,” 61 Journal of Risk and Insurance, 192-218.

---------------. “The Distribution of the Insurance Market Effects of Tort Liability Reforms,” Brookings Papers on Economic Activity: Microeconomics, 55-100.

Browne, Mark J. and Robert Puelz. 1999. “The effect of Legal Rules on the Value of Economic and Non-Economic Damages and the Decision to File,” 18 J. of Risk and Uncertainty, 189-213.

Cady, Troy L. 1997. “Note, Disadvantaging the Disadvantaged: The Discriminatory Effects of Punitive Damage Caps,” 25 Hofstra L. Rev. 1005.

Calfee, John E. and Paul H. Rubin. 1992. “Some Implications of Damage Payments for Nonpecuniary Losses,” 21 Journal of Legal Studies, 371-411.

Cassels, Jamie. 1992. “Damages for Lost Earning Capacity: Women and Children Last!,” 71 Can. B. Rev. 445.

Chamallas, Martha. 1994. “Questioning the Use of Race-Specific and Gender-Specific Economic Data in Tort Litigation: A Constitutional Argument,” 63 Fordham L. Rev. 73.

18

Cohen, Alma and Rajeev Dehejia. 2004. “The Effect of Automobile Insurance and Accident Liability Laws on Traffic Fatalities,” 67 Journal of Law and Economics, 357-394.

Cohen, Thomas. 2005. Punitive Damage Awards in Large Counties, 2001, Civil Justice Survey of State Courts, 2001, NCJ 208445.

Cydulka, Rita K. Brian Rowe, Sunday Clark, Charles Emerman, Alfred Rimm, and Carlos Camargo, Jr. 2005. “Gender differences in emergency department patients with chronic obstructive pulmonary disease exacerbation” 12 Academic Emergency Medicine 1173-1179.

Daniels, Stephen and Joanne Martin. 2006. “The Texas Two-Step: Evidence on the Link Between Damage Caps and Access to the Civil Justice System,” 55 DePaul L. Rev. 635.

Donald, Mark. 2005. “Access Denied: Does Tort Reform Close Courthouse Doors to Those Who Can Least Afford It?,” Tex. Law., Jan. 10, 2005;

Finley, Lucinda M. 1993. “Tort Reform: An Important Issue for Women,” 10 Circles 3.

-------------. 2004. “The Hidden Victims Of Tort Reform: Women, Children, And The Elderly,” 53 Emory L.J. 1263.

--------------. 1997. “Female Trouble: The Implications of Tort Reform for Women,” 64 Tenn. L. Rev. 847. (1997)

Garfinkel, M. and H. Blumstein. 1999. “Gender differences in testing for syphilis in emergency department patients diagnosed with sexually transmitted diseases,” 17 Journal of Emergency Medicine 937-40.

Gebo, Kelly A., John A. Fleishman, Richard Conviser, Erin Reilly, Todd Korthuis, Richard Moore, James Hellinger, Philip Keiser, Haya Rubin, Lawrence Crane, Fred Hellinger, and Christopher Mathews. 2005. “Racial and gender disparities in receipt of highly active antiretroviral therapy persist in a multistate sample of HIV patients in 2001” 38 Journal of Acquired Immune Deficiency Syndromes 96-103.

Gruber, Jonathan. 1994. “The Incidence of mandated Maternity Benefits,” 84 American Economic Review 622.

Helland, Eric and Alexander Tabarrok, Judge and Jury: American Tort Law on Trial.

Hollander-Blumoff, Rebecca and Matthew T. Bodie. 2005. “The Effects of Jury Ignorance About Damage Caps: The Case of the 1991 Civil Rights Act,” 90 Iowa L. Rev. 1361.

Hollenbeak, Christopher S., Carol S. Weisman, Michael Rossi, and Steven Ettinger. 2006. “Gender disparities in percutaneous coronary interventions for acute myocardial infarction in Pennsylvania” 44 Medical Care 24-30.

Johnson, P A., L. Goldman, E.J. Orav, L. Zhou, T. Garcia, S. Pearson, and T.H. Lee. 1996. “Gender differences in the management of acute chest pain. Support for the ‘Yentl syndrome’,” 11 Journal of General Internal Medicine 209-17.

19

Kessler, Daniel P., William M. Sage and David Becker. 2005. “Impact of Malpractice Reforms on the Supply of Physician Services,” 293 JAMA, 2618–2625

Kinney, Eleanor D. et al. 1991. “Indiana's Medical Malpractice Act: Results of a Three-Year Study,” 24 Ind. L. Rev. 1275.

Kjellstrand, CM, GM Logan. 1987. “Racial, sexual and age inequalities in chronic dialysis” 45 Nephron 257-263

Klick, Jonathan and Thomas Stratmann. 2003. “Does Medical Malpractice Reform Help States Retain Physicians and Does It Matter,” available form SSRN.

Koenig, Thomas and Michael Rustag. 1995. “His and Her Tort Reform: Gender Injustice in Disguise,” 70 Wash. L. Rev. 1.

Lee TH. 2000. “Gaps in quality of cardiovascular care transcend social bias” 102 Circulation 943-944.

Lydiatt, DD. 2002. “Medical malpractice and cancer of the larynx” 112 Laryngoscope 445-448.

Manning, Richard L. 1994. “Changing Rules in Tort Law and the Market for Childhood Vaccines,” 37 Journal of Law and Economics, 247-275

--------------. 1997. “Products Liability and Prescription Drug Prices in Canada and the United States,” 40 Journal of Law and Economics, 203-43.

McClellan, Frank M. 1996. “The Dark Side of Tort Reform: Searching for Racial Justice,” 48 Rutgers L. Rev. 761.

McFarlane, MJ, AR Feinstein, CK Wells. 1986. “Necropsy evidence of detection bias in the diagnosis of lungcancer”146 Arch lntern Med. 1695-1698.

Medicare Payment Advisory Commission, Report to the Congress: Medicare Payment Policy (March 2005).

Mello, Michelle and Carly Kelly. 2005. “Effects of a Professional Liability Crisis on Residents’ Practice Decisions,” 106 Obstetrics & Gynecology, 1287-1295.

Mello MM, DM Studdert, TA Brennan. 2003. “The New Medical Malpractice Crisis” 348 New England Journal of Medicine.

Pace, Nicholas M., Laura Zakaras, and Daniela Golinelli. 2004. Capping Non-Economic Awards in Medical Malpractice Trials: California Jury Verdicts Under MICRA 30-33. Rand .

Petticrew M, M. McKee, J. Jones J. 1993. “Coronary artery surgery: are women discriminated against?” 306 BMJ 1164-1166

Pezzin, Liliana, Penelope M. Keyl, and Gary B. Green. 2007. “Disparities in the emergency department evaluation of chest pain patients,” 14 Academic Emergency Medicine 149-56.

Rubin, Paul H. 2005. “Public Choice and Tort Reform,” 124 Public Choice, 223-236.

20

Ruda, Lisa M. 1993. “Note, Caps on Noneconomic Damages and the Female Plaintiff: Heeding the Warning Signs,” 44 Case W. Res. L. Rev. 197.

Rustad, Michael L. 1996. “Nationalizing Tort Law: The Republican Attack on Women, Blue Collar Workers, and Consumers,” 48 Rutgers L. Rev. 673.

----------. 2005. “Heart of Stone: What is Revealed About the Attitude of Compassionate Conservatives Toward Nursing Home Practices, Tort Reform, and Noneconomic Damages,” 35 N.M. L. Rev. 337.

---------- and Thomas H. Koenig. 2002. “Taming the Tort Monster: The American Civil Justice System as a Battleground of Social Theory,” 68 Brooklyn L. Rev. 1.

Schlegel, Christian E. 2002. “Note, Is a Federal Cap on Punitive Damages in Our Best Interest?: A Consideration of H.R. 956 in Light of Tennessee’s Experience,” 69 Tenn. L. Rev. 677.

Sharkey, Catherine M. 2005. “Unintended Consequences of Medical Malpractice Damage Caps,” 80 N.Y.U. L. Rev. 391.

Stock, James H. and Mark W. Watson. 2002. Introduction to Econometrics, Boston, MA: Addison Wesley.

Studdert, David, et al. 2004. “Are Damage Caps Regressive? A Study of Malpractice Jury Verdicts in California, 23 Health Aff. 54.

Studdert DM, MM Mello, TA Brennan. 2004. “Medical Malpractice” 350 New England Journal of Medicine.

Thorpe, Kenneth E. 2004. “The Medical Malpractice ‘Crisis’: Recent Trends and the Impact of State Reforms,” Health Affairs (http://content.healthaffairs.org/ cgi/reprint/hlthaff/w4.20v1.pdf)

Vaccarino V, Rathore SS, Wenger NK, Frederick PD, Abramson JL, Barron HV, Manhapra A, Mallik S, Krumholz HM, the National Registry of Myocardial Infarction Investigators. 2005. “Sex and Racial Differences in the Management of Acute Myocardial Infarction, 1994 through 2002.” 353 New England Journal of Medicine 671–682

Viscusi, Kip W. and Patricia H. Born. 2005. “Damage Caps, Insurability, and the Performance of Medical Malpractice Insurance,” 72 Journal of Risk and Insurance, 23-43.

Viscusi, Kip W., et. al. 1993. “The Effect of the 1980s Tort Reform Legislation on General Liability and Medical Malpractice Insurance,”6 Journal of Risk and Insurance, 165-186.

Yoon, Albert. 2001. “Damage Caps and Civil Litigation: An Empirical Study of Medical Malpractice Litigation in the South,” 3 American Law and Economics Review, 199-227.

Zimmerman, Rachel and Joseph T. Hallinan. 2004 “As Malpractice Caps Spread, Lawyers Turn Away Some Cases,” Wall St. J., Oct. 8, 2004, at A1

21

Zuckerman, S., R. Bovbjerg, and F. Sloan. 1990. “Effecs of Tort Reforms and Other Factors on Medical Malpractice Insurance Premiums,” 27 Inquiry 167-82

Zuckerman, Steve, Joshua McFeeters, Peter Cunningham and Len Nichols. 2004. “Changes in Medicaid Physician Fees 1998-2003: Implications for Physician Participation,” Health Affairs, Web Exclusive (June 23, 2004).

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Data Appendix Death Rate Data Data on death rates are from the Centers for Disease Control and Prevention, National Centers for Injury Prevention and Control. Web-based Injury Statistics Query and Reporting System (WISQARS). Available from: www.cdc.gov/ncipc/wisqars Tort Reform Variables Tort reform data are from the Database of State Tort Law Reforms available at: http://www.law.northwestern.edu/faculty/fulltime/avraham/docs/tortreformshort110206.xls Unemployment Rate Unemployment rate data were collected from the Bureau of Labor Statistics, Local Area Unemployment Statistics: http://www.bls.gov/lau/home.htm. Income Per capita income data were obtained from the Bureau of Economic Analysis at http://www.bea.gov/bea/regional/spi/. The nominal data were changed into real using consumer price index series (with 1983/1984 as the base year) obtained from the Bureau of Labor Statistics, http://data.bls.gov/cgi-bin/surveymost?cu. Demographic Variables Age, gender, race, and population data were compiled from the U.S. Census Bureau’s Population Division, available at: http://www.census.gov/popest/states/. Per Capita Alcohol Consumption This variable is the per capita ethanol consumption from beer, wine, and spirits for each state. It is obtained from the National Institute of Health, National Institute on Alcohol Abuse and Alcoholism, available at: http://www.niaaa.nih.gov/databases/consum03.htm. Hospital Beds per Capita Data on per capita beds in hospitals that are AHA members (excluding nursing homes) is compiled from American Hospital Association, Hospital Statistics annual publications.

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Table 1:

Number of States with Tort Reform Reform 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00

ND 3 3 3 3 3 8 15 17 18 17 16 14 14 14 15 18 19 17 17 17PD 9 9 9 10 13 17 24 32 36 36 36 38 38 39 39 41 41 40 40 40TD 6 6 6 6 6 8 11 8 9 9 9 9 9 9 9 7 7 7 7 7 CS 12 13 13 13 14 17 23 31 31 33 32 32 31 30 30 30 31 31 31 30JSL 6 6 6 7 8 17 22 29 31 34 34 36 36 36 38 39 40 40 40 40PP 9 9 9 9 11 18 22 26 29 29 29 30 30 30 28 28 29 29 29 29

ND=Noneconomic Damage Caps, PD=Punitive Damages Reform, TD=Total Damage Caps, CS=Collateral Source Reform, JSL=Joint and Several Liability Reform, PP=Periodic Payments. Only reforms that were effective for more than 6 months of a year are coded as present in that year. (Source: Avraham, 2007, at 7)

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Table 2 Descriptive Statistics

Variable Obs Mean Standard Deviation

African-American non-motor vehicle, accidental death rate 1173 20.55 10.78 non-African-American non-motor vehicle, accidental death rate 1122 20.87 5.54 Female non-motor vehicle, accidental death rate 1173 14.66 3.41 Male non-motor vehicle, accidental death rate 1122 28.38 8.51 Age 0-4 non-motor vehicle, accidental death rate 1173 12.98 5.67 Age 5+ non-motor vehicle, accidental death rate 1122 21.93 5.67 Age 65+ non-motor vehicle, accidental death rate 1173 74.98 16.69 Age 0-64 non-motor vehicle, accidental death rate 1122 13.92 5.60 Caps on Noneconomic Damages 1150 0.269 0.443 Reforms to Punitive Damages 1150 0.616 0.487 Caps on Total Damages 1150 0.129 0.336 Collateral Source Reform 1150 0.531 0.499 Joint and Several Liability Reform 1150 0.543 0.498 Periodic Payments 1150 0.489 0.500 Unemployment Rate 1173 6.02 2.13 Real Per Capita Personal Income 1173 11906.96 2214.55 Per Capita Alcohol Consumption 1020 2.47 0.66 Hospital Beds per Capita 1173 0.003 0.001

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Table 3 Effect of Tort Reform on Death Rates: Group-Specific Estimations

(T-statistics computed from Robust S.E.) [T-statistics computed from Newey-West Heteroskedastic & Autocorrelation Consistent S.E.]

{T-statistics computed from S.E. Clustered by State} Male Female Non-

African Americans

African-Americans

Under 65

Age 65 and over

Age 5 and over

Under 5

-1.284 -0.445 -0.744 -0.606 -0.617 -1.084 -0.898 -0.084 ND (4.02)* (2.31)+ (3.48)* (1.25) (3.41)* (1.2) (3.94)* (0.25)

[3.07]* [1.96]+ [2.72]* [1.14] [2.64]* [1.0] [3.01]* [0.27] {1.91}ª {1.45} {1.73}ª {0.89} {1.68}ª {0.75} {1.97}* {0.24} -0.855 -0.208 -0.281 -1.043 -0.495 -0.682 -0.636 -0.03

PD (2.67)* (1.33) (1.42) (2.36)+ (2.56)+ (0.91) (2.68)* (0.1) [2.05]+ [1.12] [1.14] [2.0]+ [1.98]+ [0.77] [2.03]+ [0.1] {1.24} {0.87} {0.73} {1.75}ª {1.17} {0.61} {1.16} {0.1} 1.868 0.983 1.433 1.812 0.975 3.988 1.404 2.128

TD (3.66)* (4.65)* (4.68)* (2.49)+ (4.03)* (3.95)* (4.6)* (3.86)* [2.86]* [4.16]* [3.69]* [2.5]+ [3.46]* [3.61]* [3.67]* [4.06]* {2.33}+ {3.5}* {3.12}* {2.39}+ {4.08}* {3.08}* {3.04}* {4.75}* 0.973 0.779 0.742 1.248 0.432 3.196 0.883 0.417

CS (3.06)* (3.7)* (3.23)* (2.68)* (2.41)+ (2.95)* (3.76)* (1.16) [2.48]+ [3.05]* [2.63]* [2.29]+ [1.94]ª [2.32]+ [2.94]* [1.2] {1.72}ª {2.2}+ {2.03}+ {1.68}ª {1.31} {1.61} {1.99}+ {1.09} 0.433 0.068 0.059 1.054 -0.252 -0.157 -0.098 -0.583

JSL (1.33) (0.37) (0.26) (2.44)+ (1.21) (0.18) (0.37) (1.92)ª [1.08] [0.31] [0.22] [2.21]+ [0.95] [0.15] [0.29] [1.91]ª {0.69} {0.23} {0.16} {1.68}ª {0.51} {0.12} {0.16} {1.52} 0.026 -0.033 -0.037 0.379 0.101 0.369 -0.02 0.032

PP (0.08) (0.16) (0.17) (0.7) (0.49) (0.39) (0.08) (0.09) [0.06] [0.12] [0.12] [0.58] [0.36] [0.29] [0.06] [0.09] {0.03} {0.06} {0.07} {0.36} {0.24} {0.16} {0.04] {0.07}

Obs. 1000 1000 1000 1000 1000 1000 1000 1000 R2 0.833 0.805 0.837 0.793 0.838 0.878 0.814 0.792

The dependent variable in each specification is the accidental, non-motor vehicle death rate of the relevant demographic groups. See equation 1 for other variables included by not presented for brevity. ND=Noneconomic Damage Caps, PD=Punitive Damages Reform, TD=Total Damage Caps, CS=Collateral Source Reform, JSL=Joint and Several Liability Reform, PP=Periodic Payments. Absolute values of t-statistics are in parentheses. “*”, “+”, and “ª” represent significance at the 1%, 5% ,and 10% levels, respectively.

26

Table 4 Magnitude of Relationship between Tort Reform and Group-Specific Death Rates in 2000

Average Change in the Number of Deaths in 2000 Associated with each Tort Reform

Caps on Noneconomic Damages

Reforms to Punitive Damages

Caps on Total Damages

Collateral Source Reform

Joint and Several Liability Reform

Periodic Payments

Total Impact of Tort Reform on Each Demographic Group

Males -533.8 -1007.4 233.9 801.8 -- -- -505.5 Females -189.5 -- 127.2 663.4 -- -- 601.1 Non-African American -570.8 -- 311.2 1116.2 -- -- 856.6 African-American -- -324.6 67.9 213.8 260.5 -- 217.6 Under 65 -458.6 -1040.2 219.7 632.6 -- -- -646.5 65 and older -- -- 116.6 675.4 -- -- 791.9 Age 5 and older -703.1 -1419.2 332.9 1379.0 -- -- -410.4 Under 5 -- -- 37.2 -- -84.0 -- -46.8 The number of deaths associated with each tort reform is given by β1*(group-specific population in tort reform states/100,000).

27

Table 5 Magnitude of Relationship between Tort Reform and Group-Specific Death Rates: 1980-2000

Average Change Across all Years Associated with each Tort Reform

Caps on Noneconomic Damages

Reforms to Punitive Damages

Caps on Total Damages

Collateral Source Reform

Joint and Several Liability Reform

Periodic Payments

Total Impact of Tort Reform on Each Demographic Group

Males -10607.6 -15203.3 5665.2 15435.3 -- -- -4710.5 Females -4017.6 -- 3237.8 13684.1 -- -- 12904.3 Non-African American -11367.2 -- 7627.1 21552.2 -- -- 17812.1 African-American -- -4882.2 1648.7 4459.9 4170.1 -- 5396.5 Under 65 -9139.3 -15735.1 5367.5 12227.2 -- -- -7279.7 65 and older -- -- 2865.7 13921.7 -- -- 16787.4 Age 5 and older -13931.4 -21386.8 8035.7 26525.9 -- -- -756.6 Under 5 -- -- 1039.3 -- -1464.0 -- -424.7 The number of deaths associated with each tort reform is given by β1*(group-specific population in tort reform states/100,000).

28

Table 6.

Differential Effect of Tort Reform: Difference-in-Difference Model (Robust T-statistics in Parentheses)

Female/Male

African-American/Non-

African-American

Age 4 and Under/Age 5

and over

Age 65 and Over/Under

Age 65 1 2 3 4 5 6 7 8

At-Risk Group -18.41 -23.37 8.04 14.09 -7.41 -9.25 62.29 36.21 Indicator (19.52)* (17.96)* (6.07)* (7.36)* (7.47)* (3.84)* (26.2)* (4.62)* -1.15 -1.32 -0.71 -0.80 -0.76 -0.90 -0.80 -1.11 ND Caps (3.81)* (4.34)* (3.28)* (3.65)* (3.33)* (3.98)* (4.58)* (5.39)* Demo*ND 0.91 0.92 0.27 0.39 0.92 0.90 0.75 0.84 Caps (2.47)+ (2.5)+ (0.48) (0.72) (2.28)+ (2.29)+ (0.71) (0.83) -1.01 -0.96 -0.37 -0.27 -0.62 -0.63 -0.57 -0.65 PD Reform (2.94)* (2.91)* (1.57) (1.36) (2.48)+ (2.66)* (2.74)* (2.93)* Demo*PD 0.84 0.84 -0.86 -0.71 0.50 0.54 0.27 0.25 Reform (2.09)+ (2.3)+ (1.57) (1.44) (1.29) (1.47) (0.29) (0.29) 2.00 2.05 1.43 1.41 1.29 1.41 1.15 1.27 TD Caps (3.78)* (4.00)* (4.33)* (4.68)* (4.02)* (4.69)* (4.18)* (3.99)* Demo*TD -1.23 -1.25 -0.05 -0.41 0.86 0.84 1.30 1.54 Caps (2.11)+ (2.24)+ (0.06) (0.54) (1.35) (1.33) (1.1) (1.38) 0.82 1.11 0.45 0.75 0.62 0.88 0.48 0.64 CS Reform (2.67)* (3.71)* (2.08)+ (3.36)* (2.63)* (3.79)* (2.61)* (2.91)* Demo*CS -0.44 -0.48 0.62 0.17 -0.40 -0.42 0.65 0.65 Reform (1.15) (1.33) (1.08) (0.33) (0.97) (1.07) (0.54) (0.58) -0.08 0.40 -0.51 0.17 -0.21 -0.09 0.08 0.26 JSL Reform (0.23) (1.29) (1.85)ª (0.77) (0.77) (0.34) (0.39) (1.15) Demo*JSL -0.38 -0.32 1.60 0.95 -0.62 -0.53 -0.76 -0.97 Reform (0.89) (0.85) (2.87)* (1.95)+ (1.44) (1.33) (0.63) (0.88) 0.32 0.08 0.15 -0.09 0.22 -0.05 0.14 0.01 PP (0.93) (0.23) (0.63) (0.42) (0.84) (0.22) (0.64) (0.03) Demo*PP -0.16 -0.15 0.95 0.77 0.20 0.17 1.12 1.19 (0.37) (0.39) (1.33) (1.24) (0.45) (0.41) (.94) (1.1) Full Set of Controls No Yes No Yes No Yes No Yes No. of Obs. 2000 2000 2000 2000 2000 2000 2000 2000

R-Squared 0.9419 0.9471 0.8181 0.8418 0.8385 0.8512 0.9819 0.9828 Notes: The dependent variable in each specification is the accidental, non-motor vehicle death rate of the relevant demographic groups. See equation 2 for other variables included by not presented for brevity. Absolute values of t-statistics are in parentheses. “*”, “+”, and “ª” represent significance at the 1%, 5% ,and 10% levels, respectively.

29

Table 7 Differential Effect of Tort Reform:

Differences-in-Differences-in-Differences Model (Robust T-statistics in Parentheses)

Females African-Americans

Elderly Young

1 2 3 4 5 6 7 8 Noneconomic 0.901* 0.666+ 0.201 0.118 0.593 0.891 0.926+ 0.84+ Damage Caps (3.5) (2.49) (0.34) (0.22) (0.47) (0.71) (2.16) (1.97) Punitive 0.822* 0.734* -1.227+ -0.95ª 0.267 0.171 0.495 0.589 Damages Reform

(2.77) (2.62) (2.31) (1.91) (0.23) (0.16) (1.14) (1.34)

Total -1.25+ -1.395* -0.273 -0.285 1.234 1.922 0.895 0.804 Damage Caps

(2.28) (2.58) (0.28) (0.28) (0.85) (1.45) (1.13) (1.0)

Collateral -0.42 -0.294 0.347 -0.127 0.732 0.796 -0.42 -0.424 Source Reforms

(1.41) (0.97) (0.58) (0.23) (0.48) (0.56) (0.9) (0.91)

Joint and Several -0.389 -0.25 1.58* 0.85+ -0.774 -0.891 -0.579 -0.357 Liability Reform

(1.29) (0.88) (2.92) (1.66) (0.53) (0.69) (1.23) (0.72)

Periodic -0.149 -0.237 1.024 0.757 1.25 1.436 0.178 0.169 Payments

(0.47) (0.77) (1.45) (1.22) (0.86) (1.08) (0.36) (0.35)

Full Set of Controls

No Yes No Yes No Yes No Yes

No. of Obs.

2000 2000 2000 2000 2000 2000 2000 2000

Adj. R-Squared .983 .984 .956 .961 .989 .989 .976 .976 Notes: The dependent variable in each specification is the accidental, non-motor vehicle death rate of the relevant demographic groups. See equation 3 for other variables included by not presented for brevity. Absolute values of t-statistics are in parentheses. “*”, “+”, and “ª” represent significance at the 1%, 5% ,and 10% levels, respectively.

30

Figure 1. Accidental, Non-Motor Vehicle Death Rate:

African-Americans and Non-African-Americans

15

17

19

21

23

25

27

29

1981 1986 1991 1996

Black

Non-Black

31

Figure 2. Accidental, Non-Motor Vehicle Death Rate:

Males and Females

10

15

20

25

30

35

1981 1986 1991 1996

Female

Male

32

Figure 3. Accidental, Non-Motor Vehicle Death Rate: Ages 4 and under, 5 – 64, and 65 and over

5

15

25

35

45

55

65

1981 1986 1991 1996

age 5 - 64

age 4 and under

age 65 and over