The Differential Effects of Noneconomic Damage Cap Levels on Medical Malpractice Insurers

Risk Management and Insurance Review

C© Risk Management and Insurance Review, 2013, Vol. 17, No. 2, 163-181DOI: 10.1111/rmir.12005

THE DIFFERENTIAL EFFECTS OF NONECONOMIC DAMAGECAP LEVELS ON MEDICAL MALPRACTICE INSURERSPatricia BornFaith Roberts Neale

ABSTRACT

This study examines the effect of tort reform on medical malpractice insurerswith an emphasis on the effect of cap levels on noneconomic damages. Whileprevious research finds that caps on noneconomic damages have a beneficialeffect on insurer performance, these studies do not evaluate the effects of capsof varying size. Examining insurer data from 1997 to 2007, we test whethercap levels matter. We find that insurer performance generally improves whenthe cap is set at $250,000, but caps exceeding $250,000 are not associated withimproved performance, as they are possibly not binding on award amounts.

INTRODUCTION

Beginning in the early 1970s the professional health care industry has experienced threedistinct hard markets, commonly known as crises, when the availability of medicalliability insurance was limited and/or premiums were so high as to be perceivedas unaffordable by health care professionals. The second crisis occurred in the mid-1980s and the third, most recent crisis occurred in the early 2000s culminating in 2001.1

Although medical liability crises have a broad impact on our national health care system,solutions such as tort reforms are implemented at the state level. Each crisis is mani-fested differently depending on local conditions, with some states incurring significantdistress while others experienced no obvious crisis. Accordingly, attempts at solutionsvary widely across states.

This article was subject to double-blind peer review.Patricia Born is at Florida State University, 821 Academic Way, Tallahassee, FL 32306-1110; phone:850-644-7884; e-mail: [email protected]. Faith Roberts Neale is at University of North Carolinaat Charlotte, 9201 University City Boulevard, Charlotte, NC 29223-0001; phone: 704-687-7636;e-mail: [email protected]. This research is supported by the John H. Biggs Faculty FellowshipProgram established at the University of North Carolina at Charlotte by TIAA-CREF. This articleand its contents do not reflect the views or beliefs of TIAA-CREF.

1 Neale et al. (2009) find the medical malpractice market deteriorated significantly between 1993and 2001 when the market began to improve. For further discussion of indications of thesecrises, see Thorpe (2004).

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164 RISK MANAGEMENT AND INSURANCE REVIEW

With the most recent medical liability crisis, the federal and many state governmentsrecommended placing caps on noneconomic damages in medical malpractice claims atsome level, most commonly $250,000. As in the past, there is a recurring discussion asto the efficacy of caps on noneconomic damages.

In the event of medical malpractice, monetary damages are generally paid to a third partyas a result of the negligence of an insured medical provider. These damages are typicallypaid at settlement contingent upon full and final release of all claims by the injured party.The amount paid to settle the claim may result from negotiations between parties beforelitigation or during trial proceedings, or settlement may be made after trial based on theamount determined by a jury. A claim for bodily injury consists of two types of damages,special damages and general damages. Special damages, or economic damages, aredamages that are measurable, out-of-pocket expenses such as past and future medicalbills and lost wages, expenses for medical devices and extra assistance needed as aresult of the bodily injury. General damages, also called noneconomic damages, are veryhard to measure and, as a result, can be very contentious. General damages include, butare not limited to, pain and suffering, loss of consortium, embarrassment, humiliation,disfigurement and emotional distress. A spouse or family member may file a claimfor general damages, particularly for loss of consortium and emotional distress, as theresult of an injury or death of their loved one. An additional type of damages, punitivedamages, are not generally allowed but may be claimed when the defendant’s conducthas been willful and wanton or grossly negligent.2 Punitive damages are used to first,“punish” the defendant and second, deter them from engaging in the offending conductin the future. Depending on the financial size of the defendant and the offense committed,punitive damages may be much higher than compensatory amounts awarded undergeneral and special damages.

Special damages may be complex especially when future expected values are estimatedand discounted back to present value; however, they are still measurable. In contrast,general or noneconomic damages are very difficult to measure and subject to widevariation depending on the jurisdiction and the composition of the jury.3

There is also a great deal of concern regarding the use of noneconomic damages byjuries. Noneconomic damages, including pain and suffering, are meant to compensate

2 States vary widely on the use of punitive damages with some states setting a very high require-ment that must be breached in order to claim punitive damages. In addition, some states allowpunitive damages to be insured and some states do not.

3 http://www.judicialhellholes.org/wp-content/uploads/2011/12/Judicial-Hellholes-2011.pdf, “2011/2012 Judicial Hellholes.” Each year the American Tort Reform Association (ATRA)evaluates regions within the United States and publishes a report ranking areas based on theperformance of their judicial system. The worst performing regions, those in which ATRA feelsdefendants have a high probability of not receiving a fair trial, are named “Judicial Hellholes.”Several factors are used by ATRA to evaluate these areas including the ability of plaintiffsto “shop around” for the best venue with the largest probability of receiving a high award:the history of the courts and use of “novel legal theories,” appropriateness of class actioncertification and working relationships between plaintiff attorneys, and the judges that they trytheir cases in front of as well as the attorney generals of their states. ATRA also examines thecredibility or abuse of the discovery process, the methodology used in trial and how consumerprotection acts are used.

DIFFERENTIAL EFFECTS OF NONECONOMIC DAMAGE CAP LEVELS 165

the injured plaintiff, not to punish the negligent party. Concerns have been expressed thatwithout clear direction or improper instructions from the judge, juries may incorrectlyuse these damages to punish the defendant while bypassing strict evidentiary rules andoversight required in the allocation of actual punitive damages. There are many casesin which plaintiffs have small economic damages but receive very large noneconomicdamages. One example in Mississippi involves a pharmaceutical company where 10plaintiffs were awarded $10 million dollars each in compensatory damages even thougheach plaintiff’s injuries, economic damages with small amounts of medical expenses,preexisting medical conditions, life expectancies, and actual exposures to the drug weresignificantly different.4 Admittedly, this is an extreme case but does illustrate how theallocation of noneconomic damages can be made.

As illustrated, measurement of noneconomic damages is very difficult even in the bestof circumstances. When juries are encouraged, or not discouraged, to use noneconomicdamages to punish or express anger at the defendants, or sympathy with the plaintiffs,then measurement becomes even more difficult leading to arbitrary awards.

The literature shows that of all the tort reforms, noneconomic damage caps have themost consistently significant effect on insurance markets. All but one of the previousstudies, however, treat all reforms to noneconomic damages caps equally; that is, a capof $250,000 is treated the same as a cap of $500,000. Does the level of cap matter?

It stands to reason that insurers in states with low absolute caps on noneconomic dam-ages would perform differently than insurers in states with high absolute caps if capsare, in fact, binding on the amounts awarded for the cases that make it to the courts. Onthe other hand, it may be that caps are beneficial, on average, because a cap of any levelwill reduce the probability of the most extreme award amounts, those that affect insurerperformance to the greatest degree. In that case, we would expect caps of any size tohave the same general effect. In this study, we provide a new perspective on the role ofnoneconomic damages caps. We classify states by the type of caps implemented, if any,and evaluate the differential effects of the caps on insurers operating in these states.5

The results of our assessment have important implications for states considering furtherreform of the tort environment; we show the particular effects of cap size, a componentof reform activity that is often more contestable than a cap itself, especially given socialwelfare and equity concerns.

This article proceeds as follows. In “State Tort Reform,” we describe state efforts toaddress the crises in the medical malpractice environment, review the literature assessingthe influence of these reforms on the legal environment and the medical malpractice

4 This case is located on page 48 of the “Judicial Hellholes 2005” publication by ATRA and locatedat www.atra.org.

5 Several different sources were used to classify states including Ronen Avraham’s Database ofState Tort Law Reforms (DSTLR, 2nd) available on SSRN, the American Tort Reform Associationat http://www.atra.org, the National Conference of State Legislatures at www.ncsl.org, and theindex of McCullough, Campbell & Lane LLP at www.mcandl.com/states.html. Discrepanciesamong these sources were resolved using the LexisNexis Academic database to access statecodes and verify the specific laws for each state. Following Avraham (2010), reforms effectivebefore July 1st are coded and considered effective in that same year. Reforms effective on orafter July 1st are coded and considered effective in the following year.


insurance market, and discuss our expectations of the effects of noneconomic damagescaps on insurer performance. In “Data and Empirical Approach,” we describe the dataand empirical methodology we use for our analysis. We also discuss our expectationsfor all other variables not discussed in “State Tort Reform.” The empirical results arepresented in “Results.” A final section contains our conclusions and a discussion of theimplications of our results.

STATE TORT REFORM

After each hard market several states enacted some type of tort reform in an effort toincrease availability and/or affordability of medical malpractice insurance.6 The specificreforms that limit recovery for noneconomic damages typically fall into one of threegeneral categories: (1) states with total caps on all noneconomic damages, (2) stateswith no caps on noneconomic damages, and (3) states that have progressive caps, veryhigh caps, conditional caps, or caps on only certain types of noneconomic damagessuch as pain and suffering or emotional distress.7 Other tort reforms include caps onpunitive damages, limitations on attorney contingency fees, modifications to collateralsource rules, limitations on liability, modifications to joint and several liability, and theestablishment of patient compensation funds. While our objective is to examine insurerperformance at different levels of caps on noneconomic damages, we control for theinfluence of these other reforms as well. We discuss these measures and our hypothesesin the next section.

Since California first enacted a package of reforms in 1975, researchers have studiedthe effects of various tort reform measures on liability claims and insurance companyperformance. Damage caps and collateral source rules implemented after 1975 wereshown by Danzon (1984) to significantly reduce the severity of claims. However, sub-sequent retroactive changes in liability rules led to price increases (Doherty and Kang,1988; Cummins and Danzon, 1994). Studies using data from the 1980s and 1990s findthat tort reform reduces the level of losses and increases insurer profitability (Bornand Viscusi, 1994; Viscusi and Born, 2005; Kessler, 2006). Tort reform is also shown toslow the growth of premiums (Thorpe, 2004; Kane and Emmons, 2005; Kessler, 2006).Similarly, insurer performance is significantly improved with the least profitable insur-ers and those with the least effective underwriting policies receiving the most benefitfrom the reforms (Born and Viscusi, 1998). There is substantial evidence that caps ondamages significantly reduce medical malpractice losses and/or premiums (see, e.g.,Viscusi et al., 1993; Viscusi and Born, 1995; Born and Viscusi, 1998; Danzon et al., 2004;Hoyt and Powell, 2006; Kessler, 2006). Most recently, Born et al. (2009) find that thelong run benefits of tort reform, as measured by developed losses, are even more thaninsurers expected, and insurers with the largest losses appear to receive the most benefit.Grace and Leverty (2010) examine data from 1985 to 2005 and find insurers do accountfor states’ legal environments when setting premiums; insurers who expect reforms to

6 Mello (2006) provides a comprehensive survey of the tort reform literature through 2005.7 For example, in some states, stipulations are included to allow plaintiffs to obtain higher awards

for noneconomic damages if certain criteria are met such as proof of permanent loss; substantialdisfigurement; the plaintiff is a paraplegic, quadriplegic, or mentally or reproductively impaired;gross misconduct; or the plaintiff demonstrates a clear need for a higher award.


stay in place over time charge lower premiums than insurers who expect the reforms tobe repealed.8

We place states into five categories based on the type of cap in place. We list thesecategories in order of anticipated effect in Table 1 with the reforms expected to havethe greatest effect listed first: states with a $250,000 total cap on noneconomic damages,states with caps on noneconomic damages higher than $250,000 and less than or equal to$500,000, states with caps on noneconomic damages greater than $500,000 and less thanor equal to $1 million, states with noneconomic damages reform that cannot be classi-fied elsewhere, and states with no caps on noneconomic damages.9 The categories thatinclude states with no caps and those with total cap amounts are self-explanatory. Weset the lowest category at the $250,000 level for three main reasons. First, California im-plemented $250,000 caps on noneconomic damages in 1975 and has had very favorableresults (see Pace et al., 2004). Second, several states, such as Florida, have implementeda $250,000 cap. Finally, $250,000 caps on noneconomic damages have been proposed atthe federal level as well as by the American Medical Association.10 The table provides asummary of states’ classification based on implemented laws regarding caps on noneco-nomic damages. In 2007, only six states have a total cap of $250,000 on noneconomicdamages, but during our sample period, eight states had total caps of $250,000 at somepoint. As illustrated, some states enter and exit categories over time as they modify theircaps.

We evaluate the relationship between caps and two measures of performance: total lossesand the loss ratio, defined as losses incurred divided by premiums earned. In the firstspecification, we evaluate the relationship between reform and losses while controllingfor the volume of premiums earned for which the losses are incurred. This specificationallows us to assess whether, for a given volume of premiums, reforms are significantlyrelated to the concurrent losses incurred. The second specification allows us to assesswhether reforms are related to the simultaneous movements of premiums earned andlosses incurred, since insurers’ expectations of the effects of reform might already beconsidered in the premiums charged.11 In both specifications, we hypothesize that thecaps have a beneficial effect on insurer performance, that is, lower losses and lower lossratios, as this was the general intent of the reforms.

Overall, medical malpractice insurers should experience the most sizable effects in statesthat have the lowest caps ($250,000) on noneconomic damages since this limit is themost binding on the distribution of award amounts. Insurers operating in states withhigher total caps on noneconomic damages should also perform better than insurers

8 For further discussion of the constitutionality of malpractice damage caps, see Kelly and Mello(2005).

9 Very little tort reform took place from the years 1995 to 2001. Three states implemented caps onnoneconomic damages in 1995: Montana, North Dakota, and Wisconsin. Alaska implemented“modified” caps in 1997 and Virginia implemented $1.5 million caps in 1999. No other capswere implemented until 2002.

10 There is no inflation adjustment allowed in California’s cap or in the proposed state and federalcaps.

11 The loss ratio is used to measure insurer profitability and can be interpreted as the inverse ofthe ex post insurance price.

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operating in states with no caps if there are statistically significant numbers of claims fornoneconomic damages that exceed the cap level. The performance of insurers operatingin states with other definitions of caps on noneconomic damages is difficult to anticipatedue to the varying language and applicability; for example, some states would actuallyfall into the “higher total caps” category except under certain, and at times very limited,circumstances. On the one hand, the more flexible language in these reforms suggeststhey are not likely to be as binding as those with specific amounts. However, it mightbe that the reforms are designed to address a specific problem in the state, for which asimple cap amount would not suffice.

The other tort reform measures are also likely to affect performance in a positive way.That is, these measures were designed to have a direct effect on losses (e.g., limits onattorney contingency fees) or to reduce insurer uncertainty (e.g., modifications to jointand several liability, punitive damages caps). However, we note that, in many cases,the prior literature does not find these other reforms to have a sizable effect on insurerperformance. This is likely because states enacted packages of reform measures, whichare difficult to disentangle, and the application of the different types of measures variesacross states.

If our results indicate a significant difference in the performance of insurers acrossstates with different levels of caps on noneconomic damages, we could suggest thatthe actual level of caps matters when assessing insurer performance. For reasons notedabove, we expect that the underwriting performance of insurers in states with somelevel of noneconomic damages cap will be better than the experience of insurers instates with lower cap amounts or no caps. Differential results across insurers in stateswith different cap amounts will confirm whether it is the mere existence of a capthat matters and whether cap amounts are, in fact, significantly binding on awardamounts.

DATA AND EMPIRICAL APPROACH

We use data from insurers’ annual statutory accounting statements for the period 1997–2007 obtained from SNL Financial, Inc., to perform our analysis of the influence ofvarying levels of caps on noneconomic damages.12 We include in our analysis all insurerswriting more than $10,000 in direct premiums written for the years studied, in themedical malpractice market in all states. Therefore, an insurer may participate, and beincluded, in more than one state with state specific data being used for each state inwhich it operates.13

We evaluate the effect of the level of noneconomic damages caps on insurer performanceusing two measures of performance: direct losses incurred and the loss ratio. We uselogged values of these measures to satisfy normality assumptions and improve the fit

12 These data are used with the permission of the National Association of Insurance Commissioners(NAIC) and results or conclusions reached from using these data in this project are not reflectiveof the opinions of the NAIC or SNL Financial, Inc.

13 For each insurer, the NAIC annual statement data report certain performance variables, such asdirect premiums written and direct losses incurred, by state and by line of insurance. Monetaryvalues are adjusted for inflation using the annual Consumer Price Index (CPI). Premiums net ofreinsurance are not available at the state level.


of our models.14 We use a panel data regression technique, controlling for insurer-statefixed effects as well as other insurer characteristics that may be related to performance.Since most insurers operate in more than one state, we also adjust our standard errorsfor clustering by insurer. Our key variables of interest are those that capture the varyinglevels of caps on noneconomic damages. Specifically, we estimate the following twoequations for insurer i in state j and year t:

LogDirLossesIncurredijt = α+β LogDirPremiumsEarnedijt + δ j tϕ

+� j tλ + ωi t p + vi j + εi j t (1)

LogLoss Ratioijt = α+δ j tϕ+�jtλ+ωit p+vi j+εi j t, (2)

where

δ is a vector of noneconomic damage cap levels with (omitting) states with no capsas the base;

� is a vector of other tort reform variables (i.e., 1 if caps on punitive damages or 0 ifno caps);

ω is a vector of control variables including log of assets, number of states in which theinsurer writes medical malpractice, share of total medical malpractice business instate j, medical malpractice business as a share of total premiums for all lines, t-billrate, and per capita income by state;

v is unit (insurer-state) specific residual.

We estimate each equation four times. For the total sample, we estimate two models: onein which we include a dummy variable, which equals 1 if the state has any noneconomicdamages cap, and 0 otherwise. This first model allows us to confirm what most otherstudies of the tort reforms have found by capturing only the existence of a cap, butnot the size of the cap. Then, we estimate the same equation with a vector of variablesthat capture the different cap levels. Since many of the tort reforms have been in placefor some time, while others are quite new, we estimate these models for two othersamples. Whereas the first sample contains all insurers with premiums written greaterthan $10,000 in all states for all years, the second sample consists only of insurer-stateobservations in which the state implemented caps on noneconomic damages after thebeginning of our sample period. This sample allows us to assess whether the newercaps on noneconomic damages have a stronger correlation with performance than thoseenacted previously. The third sample contains all observations for the years 2001–2007,wherein we include in the vector ω four measures of the insurers’ exposure types (e.g.,physicians versus health care facilities) that were not available until 2001. Statisticsfor our three samples are provided in Table 2. We expect that the caps will have thesame beneficial effects on insurer performance in each of our three samples, although

14 The natural log of the loss ratio is used because it increases explanatory power and mitigates theeffect of large outliers on results (Born and Viscusi, 1994). Using natural logs of the independentvariables also enables interpretation of results in that the coefficients in the log–log specification


TABLE 2Sample Statistics for All Insurers and Subsample, 1997–2007

Total Sample(N = 15,761)

Subsamplea

(N = 3,308)Total Sample, Year>2000 (N = 10,633)

Variable Mean Std Dev Mean Std Dev Mean Std DevLog direct losses incurred 13.283 2.123 13.456 2.127 13.234 2.132Log direct premium earned 13.953 1.690 14.067 1.670 13.972 1.726Log direct premiums

written13.923 1.613 14.042 1.585 14.003 1.638

Log direct loss ratio −0.295 1.056 −0.252 1.096 −0.370 1.051Any nonecon damages cap 0.379 0.485 0.299 0.458 0.379 0.485$250K cap on noneconomic

damages0.116 0.324 0.062 0.242 0.119 0.323

$251K to $500K cap onnoneconomic or totaldamages

0.163 0.370 0.157 0.364 0.175 0.380

$501K to $1M cap onnoneconomic or totaldamages

0.131 0.337 0.052 0.223 0.142 0.349

Other noneconomicdamages reform

0.043 0.203 0.066 0.248 0.051 0.220

Punitive damages cap 0.528 0.499 0.744 0.437 0.531 0.499Joint and several liability 0.758 0.428 0.836 0.371 0.773 0.419Collateral source rule 0.624 0.485 0.406 0.491 0.657 0.475Attorney contingency fee 0.362 0.481 0.288 0.453 0.362 0.481Patient compensation fund 0.200 0.400 0.065 0.247 0.209 0.407Risk retention group 0.153 0.360 0.161 0.367 0.182 0.386Reciprocal exchange 0.049 0.216 0.039 0.194 0.046 0.209Mutual company 0.068 0.252 0.053 0.224 0.070 0.255Lloyd’s company 0.000 0.008 0.000 0.017 0.000 0.000Stock company 0.695 0.461 0.710 0.454 0.666 0.472Share physicians 0.373 0.443Share hospitals 0.149 0.307Share healthcare facilities 0.137 0.304Share healthcare

professionals0.241 0.392

Share other medicalproviders

0.099 0.299

Log assets 13.091 2.063 12.916 2.110 13.067 2.179Log number of states 3.181 1.072 3.170 1.047 3.148 1.108Log state share −3.504 1.699 −3.213 1.544 −3.507 1.722Log mm share −1.475 1.689 −1.497 1.729 −1.430 1.704Log tbill rate 1.121 0.584 1.137 0.579 0.879 0.568Log state per capita income 10.477 0.144 10.434 0.113 10.500 0.139

Source: SNL Insurer Statutory Financial Data, 1997–2007.aThe subsample consists of insurers in all states that had not passed any tort reform measure priorto the beginning of our data sample (1997).


the magnitudes might differ; the use of three samples provides a further test of therobustness of these relationships.

We turn now to our hypotheses for those variables included as controls in our models.In 1, we include two other measures of underwriting operations that we expect to bestrongly related to our dependent variable. By design, we expect state direct medicalmalpractice premiums earned to be positively related to losses incurred. Although lossesare random, by nature, we generally expect the estimated coefficient to be somewhereclose to one.

Five dummy variables are included in each model to capture other changes in states’legal environments over our time frame. Specifically, the variables indicate the pres-ence of a cap on punitive damages, a limit on attorney contingency fees, modifi-cation of joint and several liability, modification of the collateral source rule, andthe establishment of a patient compensation fund.15 If these reforms are effectivewe anticipate they would be associated with lower losses incurred and lower lossratios.

We include additional control variables to capture insurer characteristics and marketconditions that may relate to performance. Total assets are included to control for thesize of the insurer, which may be associated with specific economic opportunities. Forexample, a larger insurance company may achieve economies of scale relative to asmaller insurer and hence, exhibit lower claim costs. Dummy variables to account fororganizational form and group membership are included to capture differential accessto internal and external capital. Finally, we include two measures to proxy the insurer’s“stake” in the market. First, we include the share of the insurer’s total business (all lines)earned in the state. We expect insurers with a larger state market share achieve certainbenefits, including perhaps more lenient regulatory oversight, over those with lowmarket shares. The second measure is the share of the insurer’s total business in medicalmalpractice, which we expect might capture specific benefits due to specialization inthe line. We anticipate both share measures to be negatively related to our performancemeasures; that is, larger shares in either sense are associated with lower losses and lowerloss ratios.

The number of states in which an insurer writes medical malpractice is a proxy fordiversification. If insurer diversification across states is beneficial for insurers leadingto decreased costs or risk then we should find a negative relationship between num-ber of states and our performance measures. However, if expansion does not provideeconomies of scope, then a positive relation between number of states and losses incurredmight be found (Thorpe, 2004).16

indicate elasticity of the loss ratio and can be interpreted as a percentage change in the loss ratiofor a percentage change in the independent variables.

15 We cannot include the patient compensation fund variable in our third specification becausethere were no changes in this variable for the states included in our subsample, which creates acollinearity problem with our insurer-state fixed effects.

16 Thorpe (2004) reports that several insurers expanded beyond their home state and incurredlarge losses with some becoming insolvent or dropping the medical malpractice line as a result.These insurers included St. Paul, PHICO, and PIE Mutual.


Medical malpractice insurers write coverage for different entities, and some may special-ize to this regard; for example, they write coverage only for medical facilities. Becausethe incidence of malpractice may differ across these entities, we would ideally includesome control for the insurer’s involvement in these different coverage groups, that is,physicians, health care facilities, health care professionals, and hospitals. Unfortunately,data on these groups are only available from 2001 on, so we estimate our models ona subsample for the period 2001–2007 only, and include four variables to capture thisvariation: the share of medical malpractice direct premiums written for physicians, hos-pitals, health care facilities, and other health care professionals, respectively. The shareof direct premiums written for physicians is the omitted comparison group.

The t-bill rate is included in our models to account for the time value of money anddiscounting of loss reserves.17 It is also a proxy for the interest rate. We expect to finda negative relationship between the t-bill rate and losses incurred; as the discount rateincreases, the present value of losses incurred decreases. We expect to find a similarnegative relationship between the t-bill rate and the loss ratio. Higher interest ratesallow insurers to charge lower premiums but losses would also be discounted at ahigher rate. In addition, the underwriting risk portfolio may change as a result of thelower price. However, the net effect of higher interest rates is that loss ratios are reduced(Born and Viscusi, 1994).

Per capita income by state is a proxy for the average income of the claimants (Avraham,2007). We expect a positive relation between average income and performance: as thestate average income increases, losses incurred, which includes lost wages are expectedto increase.

RESULTS

Our analysis yields several interesting results that confirm our expectations. All resultsare provided at a confidence level of 5 percent or less unless otherwise noted. We report inTable 3 the results from estimating 1 for our four models. For the total sample we find thatinsurers in states with any type of noneconomic damages cap in place have, on average,7.6 percent lower direct losses incurred than states with no caps, though the result is notsignificant. In our second model specification, we find that the level of the cap matters.Insurers in states with $250,000 caps on noneconomic damages have significantly lowerlosses incurred, approximately 20 percent lower, than insurers in states with no caps.18

Insurers operating in states with the caps that range from $250,000 to $500,000 do notreport significantly different losses, but at a 10 percent significance level, those in stateswith caps from $500,000 to $1 million report losses that are approximately 15 percentlower, on average, than insurers in states with no caps. We find that insurers in states

17 Specifically, we use the annualized 3-month Treasury bill rate. Statutory accounting principlesdo not allow insurers to discount loss reserves except in the case of long-tail lines such as medicalmalpractice and workers compensation. In these cases insurers can request permission from thestate regulator to discount these loss reserves if it is not permitted by insurance law. Elliott (2012)notes that in medical malpractice insurance, discounting loss reserves over time may result in a50 percent or more reduction of nominal loss reserves.

18 The percentage impact of dummy variables in a semi-logarithmic function is calculated as eδ – 1(Kennedy, 1998, p. 228).


TABLE 3Effect of Noneconomic Damages Caps on Direct Losses Incurred (DLI), 1997–2007

Log DLI

(1)Total

Sample

(2)Total

Sample

(3)Subsample(Without

ControllingClustering

by Company)

(4)Total

Sample Year> 2000

Log state DPE 0.866*** 0.866*** 0.870*** 0.848***(0.043) (0.043) (0.042) (0.043)

Any noneconomic damages cap −0.076(0.047)

$250K cap on noneconomic −0.196** −0.229 −0.190**damages (0.092) (0.149) (0.094)

$251K to $500K cap on −0.038 −0.046 0.088noneconomic or total damages (0.084) (0.114) (0.094)

$501K to $1M cap on −0.151* −0.039 −0.106noneconomic or total damages (0.085) (0.120) (0.084)

Other noneconomic damages −0.227 0.024 −0.022reform (0.161) (0.219) (0.199)

Punitive damages cap 0.018 0.051 0.081 0.052(0.071) (0.074) (0.157) (0.090)

Joint and several liability 0.016 −0.009 0.166 −0.038(0.076) (0.076) (0.127) (0.086)

Collateral source rule −0.119* −0.106 −0.297** −0.152*(0.063) (0.066) (0.149) (0.085)

Attorney contingency fee 0.186 0.294* 0.139 0.227(0.136) (0.165) (0.250) (0.182)

Patient compensation fund −0.121 −0.183 −0.147(0.217) (0.259) (0.259)

Risk retention group 0.188 0.178 0.380(0.159) (.154) (0.163)

Reciprocal exchange −0.312** −0.309** −0.670(0.141) (0.140) (0.496)

Share phys 0.222(0.173)

Share hc fac 0.151(0.159)

Share hc prof 0.197(0.153)

Share med pr 0.134(0.209)

Log assets −0.111 −0.111 −0.206*** −0.070(0.097) (0.097) (0.079) (0.127)

Log number of states 0.070 0.073 0.217** 0.138(0.072) (0.072) (0.096) (0.096)

(Continued)


TABLE 3Continued

Log DLI

(1)Total

Sample

(2)Total

Sample

(3)Subsample(Without

ControllingClustering

by Company)

(4)Total

Sample Year> 2000

Log state share −0.117*** −0.118*** −0.058 −0.093**(0.045) (0.045) (0.050) (0.043)

Log mm share −0.270*** −0.271*** −0.347*** −0.201**(0.073) (0.073) (0.057) (0.093)

Log tbill −1.571 −1.532 −2.433** −0.551(1.014) (1.020) (1.075) (0.986)

Log state per capita income −0.023 0.201 −1.711 1.103(0.514) (0.562) (1.723) (0.783)

Constant 4.15 1.72 23.836 −9.820(6.161) (6.692) (18.529) (9.027)

F-value 81.30*** 81.05*** 38.88*** 46.06***R2 within 0.2704 0.2708 0.2889 0.2403R2 between 0.6737 0.6618 0.5802 0.6828R2 overall 0.6315 0.6229 0.5480 0.6552N observations 15,549 15,549 3,258 9,921N groups 3,648 3,648 744 2,916

Notes: Insurer-state fixed effects; the values are the coefficients, with the standard error below thecoefficients in parentheses. The dummy variables that capture the level of noneconomic damagescaps are: states with $250,000 total caps, states with $251,000–500,000 caps, states with higher totalcaps up to $1 million, and states with modified caps or caps higher than $1 million. The base caseis states with no caps on noneconomic damages. Additional dummy variables capture the effect ofother tort reforms and are set to 1 if a state has enacted caps on punitive damages, rescinded part orall of joint and several liability, allows evidence of collateral sources, limits attorneys’ contingencyfees, or has a patient compensation fund. All models include year dummies; estimated effectsfor these variables are not shown. F-tests were performed to compare the significance of thedifferences between cap levels. In the second and fourth specifications, the estimated coefficientson the $250,000 cap are significantly different than the estimated coefficients on the $500,000 capat the 5 percent level and 1 percent level, respectively; differences between the other estimatedcoefficients are not statistically significant.aThe variable was omitted due to collinearity.***Coefficient different from zero at the 1 percent level.**Coefficient different from zero at the 5 percent level.*Coefficient different from zero at the 10 percent level.

that we classify as having an “other noneconomic damages reform” cap do not reportsignificantly lower losses, on average, than insurers in states with no caps. These capsmay not be binding on court outcomes given their more flexible nature, and hence wouldhave little effect on insurers.

When we estimate our loss equation for our subsample of insurers, we do not find thecaps of any level to have a significant relationship with losses. This subsample contains


only those insurers in states that enacted a cap during our sample period, but manyof these states had enacted other tort reform measures previously. Thus, the marginaleffect on losses of enacting a cap on noneconomic damages may be difficult to identifystatistically.

The results for our fourth model are mostly consistent with those obtained for thefull sample. Again, we find that insurers in states with the $250,000 cap on noneco-nomic damages report significantly lower losses than insurers in states with no cap,and otherwise insurers in states with other caps do not report significantly lowerlosses than insurers in states with no cap. The four measures included to cap-ture the insurers’ exposure types are not significant determinants of losses, all elseequal.

In all four models we find a positive relation between direct losses incurred and directpremiums earned; a 1 percent increase in direct premiums earned results in approx-imately 0.83–0.87 percent increases in direct losses incurred. Insurers that write morebusiness or charge a higher rate per unit of insurance experience higher losses, as wouldbe expected.

We find that insurer size, measured by log of assets, and the number of states in whichthe insurer does business are not consistent significant determinants of losses, all elseequal. However, all models indicate negative relationships between direct losses in-curred and our two share measures. Insurers who have a larger “stake” in the statemedical malpractice market report significantly lower losses, all else equal. We suspectthat these measures are capturing the benefits of economies of scale and expertise inmedical malpractice insurance. While our findings indicate that modifications to thecollateral source rule appear associated with lower losses, the other tort reforms in-cluding modifications to joint and several liability, punitive damage caps, limits onattorney contingency fees and patient compensation funds are not significantly relatedto insurers’ direct losses incurred. When using the total sample we find reciprocal ex-changes have significantly lower losses, approximately 31 percent lower, than stockcompanies.

Table 4 presents the results from estimating our second equation. In the total sample wefind insurers with any type of cap report loss ratios that are 7.8 percent lower than forthose insurers in states with no caps. When we look to the three specifications with caplevels, we find that insurers in states with a $250,000 cap report significantly lower lossratios. Interestingly, the estimated effect is largest when estimated for our subsampleof insurers, the “newer” reformers. This suggests that the influence of noneconomicdamages caps is stronger when first implemented. However, we are cautious in ourinterpretation given the lack of significance on this variable in the loss equation, and thelow R2 for the loss ratio equation.

The estimated effects of our control variables are generally consistent with the resultsreported in Table 3. Again, we find that the measures we include to proxy the in-surer’s “stake” in the market are both associated with improved underwriting per-formance: the larger the insurer’s stake, the better the performance, as expected. Fur-ther, we note that insurer size is also a significant factor affecting loss ratios: largerinsurers report lower loss ratios, all else equal. At a significance level of 10 per-cent and using the total sample, reciprocal exchanges loss ratios are approximately


TABLE 4Effect of Noneconomic Damages Caps on Loss Ratios, 1997–2007

Log LR

(1)

Total

Sample

(2)

Total

Sample

(3)

Subsample

(Without

Controlling

Clustering

by Company)

(4)

Total

Sample

Year > 2000

Any noneconomic damages cap −0.078**

(0.038)

$250K cap on noneconomic damages −0.170** −0.259** −0.129*

(0.079) (0.126) (0.073)

$251K to $500K cap on noneconomic or −0.043 0.011 0.071

total damages (0.071) (0.098) (0.078)

$501K to $1M cap on noneconomic or −0.097 −0.090 −0.071

total damages (0.062) (0.102) (0.067)

Other noneconomic damages reform −0.197 −0.089 −0.063

(0.133) (0.186) (0.143)

Punitive damages cap −0.035 −0.007 0.021 −0.024

(0.063) (0.066) (0.135) (0.088)

Joint and several liability 0.005 −0.017 0.089 −0.019

(0.074) (0.073) (0.109) (0.082)

Collateral source rule −0.075 −0.064 −0.225* −0.095

(0.054) (0.056) (0.127) (0.075)

Attorney contingency fee 0.127 0.214* 0.140 0.149

(0.122) (0.131) (0.211) (0.136)

Patient compensation fund −0.222 −0.218 −0.219

(0.297) (0.291) (0.294)

Risk retention group −0.102 −0.110 0.171

(0.201) (0.193) (0.977)

Reciprocal exchange −0.154* −0.151* −0.357

(0.088) (0.087) (0.513)

Share phys 0.195

(0.163)

Share hc fac 0.145

(0.130)

Share hc prof 0.084

(0.165)

Share med pr 0.181

(0.169)

(Continued)


TABLE 4Continued

Log LR

(1)

Total

Sample

(2)

Total

Sample

(3)

Subsample

(Without

Controlling

Clustering

by Company)

(4)

Total

Sample

Year > 2000

Log assets −0.154** −0.154** −0.276*** −0.137

(0.073) (0.073) (0.063) (0.088)

Log number of states −0.011 −0.010 0.070 0.007

(0.065) (0.065) (0.077) (0.079)

Log state share −0.224*** −0.224*** −0.201*** −0.206***

(0.027) (0.027) (0.033) (0.037)

Log mm share −0.377*** −0.378*** −0.433*** −0.302***

(0.057) (0.057) (0.042) (0.092)

Log tbill −1.115 −1.120 −0.930 −0.411

(0.765) (0.771) (0.909) (0.732)

Log state per capita income −0.783 −0.600 −0.874 0.564

(0.487) (0.544) (1.468) (0.599)

Constant 10.455* 8.464 12.300 −5.209

(5.466) (6.089) (15.790) (6.804)

F-value 8.06*** 7.10*** 9.77*** 4.38***

R2 within 0.0619 0.0622 0.0907 0.0456

R2 between 0.0011 0.0010 0.0107 0.0002

R2 overall 0.0009 0.0009 0.0001 0.0004

N observations 15,342 15,342 3,221 9,825

N groups 3,651 3,651 746 2,927

Notes: Insurer-state fixed effects: the values are the coefficients with the standard error below thecoefficients in parentheses. The dummy variables that capture the level of noneconomic damagescaps are: states with $250,000 total caps, states with $251,000–500,000 caps, states with higher totalcaps up to $1 million, and states with modified caps or caps higher than $1 million. The base caseis states with no caps on noneconomic damages. Additional dummy variables capture the effectof other tort reforms and are set to 1 if a state has enacted caps on punitive damages, rescindedpart or all of joint and several liability, allows evidence of collateral sources, limits attorneys’contingency fees, or has a patient compensation fund. Areas shaded in gray indicate the variableis not included in the model specification or has been dropped from the model due to collinearity.All models include year dummies; estimated effects for these variables are not shown. F-tests wereperformed to compare the significance of the differences between cap levels. Differences betweenthe estimated coefficients are not statistically significant.***Coefficient different from zero at the 1 percent level.**Coefficient different from zero at the 5 percent level.*Coefficient different from zero at the 10 percent level.


15 percent lower than those of stock companies. Overall, the R2 measures from ourloss ratio models indicate that our covariates do a poor job in explaining the vari-ance in loss ratios. This is not surprising given the random nature of underwritingperformance.

CONCLUSIONS AND DISCUSSION

Our analysis suggests that the existence of a cap on noneconomic damages may be moreimportant as a factor affecting insurer performance than the actual level of the cap. Theresults in Table 3 indicate that while the existence of a reform seems to matter, onlythe lowest cap amount prevails as a significant determinant of insurer performance. The$250,000 cap amount is most likely to be binding on damages amounts awarded throughthe legal system. Our results are consistent with other studies that have documented asignificant relationship between insurer performance and the presence of a noneconomicdamages cap, but our findings further suggest that this effect is largely driven by theperformance of insurers in states with the lowest cap levels.

Our analysis suggests that higher cap levels on noneconomic damage caps may notbe effective in reducing losses for medical malpractice insurers, all else equal. Insurersin states with a $250,000 cap on noneconomic damages awards experience 20 percentlower losses over our whole sample period. For those insurers in states that enacted thisreform more recently, loss ratios are significantly lower: these insurers experience lossesthat are 45 percent lower than insurers in states with no caps.

States enact tort reform generally to increase availability and affordability of insurance.We find some evidence that caps on noneconomic damage awards reduce losses. A capreduces uncertainty regarding the extent of damages payable for noneconomic losses, ahistorically difficult claim to measure, as it places a boundary on the maximum level ofnoneconomic damages that can be claimed.

The decision to implement caps on noneconomic damages in the case of medical mal-practice liability requires significant intervention in the market with important conse-quences for all stakeholders involved including medical providers, insurers, and thepublic at large. We emphasize that this article is not meant to provide an argument insupport of caps on noneconomic damages but merely to offer an analysis of the effects ofvarying cap levels on insurer performance. Our objective was to determine if cap levelshave differential effects on mitigating overall claim costs. Our results confirm that capson noneconomic damages are the most effective of all tort reform measures, but capsexceeding $250,000 are not associated with improved performance, as they are possiblynot binding on award amounts.

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Documents

The Differential Effects of Noneconomic Damage Cap Levels on Medical Malpractice Insurers