Pain and Suffering Damages in Personal Injury Cases: An Empirical Study

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1 Draft of June 5, 2014 Pain and Suffering Damages in Personal Injury Cases: An Empirical Study Yun chien Chang, * Theodore Eisenberg, ** Tsung Hsien Li, *** Martin T. Wells **** Abstract Many jurisdictions award pain and suffering damages yet it is difficult for judges or juries to quantify pain. Several jurisdictions, such as California, cap pain and suffering damages or other noneconomic damages, and legal scholars have proposed ways to control such damages. Reforms and proposals, however, have been based on limited empirical evidence. It remains an open question whether components of economic damages explain pain and suffering damages. This study employs a unique data set of Taiwan district court cases and uses detailed information on the components of pecuniary damages. Pain and suffering damages highly correlate with the plaintiff s medical expenses, level of injury, and with the amount requested by the plaintiff. The association with the amount requested by the plaintiff persists when one accounts for the likely quantifiable influences on pain and suffering damages, evidence of a possible anchoring effect. The strong correlation between economic damages and noneconomic damages persists in a large U.S. dataset of judge and jury trials, in which the noneconomic fraction of total damages is no greater than the pain and suffering fraction of total damages in Taiwan. Decision makers consistently produce coherent patterns of noneconomic damages. Keywords Pain and suffering damages, medical expenses, anchoring effect, lost earning capacity, salary, pecuniary damages, non medical expenses, judges, juries, Taiwan * Associate Research Professor & Deputy Director of Center for Empirical Legal Studies, Institutum Iurisprudentiae, Academia Sinica, Taiwan. J.S.D., New York University School of Law. Corresponding author. We thank for comments Ronen Avraham, Oren Bar Gill, Omri Ben Shahar, Bernie Black, John MacDonald, Valerie Hans, Jim Hines, Jr., William Hubbard, Xifen Lin, Chengxin Peng, Wei Zhang, and participants at the 2013 Conference on Empirical Legal Studies held at University of Pennsylvania Law School; the 2013 meeting of the Italian Society for Law and Economics held at the Universita della Svizerra Italiana; the 2014 American Law and Economics Association Annual Meetings held at the University of Chicago; Shanghai Jiao Tung University Faculty of Law at Shanghai, China; 2014 Asian Law and Economics Association Annual Meeting at Taipei, Taiwan. We also thank the judges at the Judicial Yuan, Taiwan, who provided valuable feedbacks to this project. Yueh Hsun Yang provided research assistance. ** The late Henry Allen Mark Professor of Law and Adjunct Professor of Statistical Science, Cornell University. *** Ph.D. in Criminology, National Chung Cheng University, Taiwan. **** Charles A. Alexander Professor of Statistical Sciences, Cornell University. 1

2 Table of Contents I. INTRODUCTION... 3 II. TAIWAN S PAIN AND SUFFERING DAMAGES LAW... 5 III. HYPOTHESIS AND METHODOLOGY... 7 A. RESEARCH QUESTIONS... 7 B. THE DATA... 8 C. REGRESSION MODELS One Equation Models Structural Equation Model IV. FINDINGS AND DISCUSSION A. MEDICAL EXPENSES AND LEVEL OF INJURY BEST EXPLAIN PAIN AND SUFFERING DAMAGES B. EVIDENCE FROM REGRESSION RESULTS C. LOST SALARY AND PAIN AND SUFFERING D. OTHER VARIABLES OF INTEREST Victim s Fault Victim s Age Pain and Suffering Damages as a Percentage of Total Damages Car Accident versus Medical Malpractice E. ACCOUNTING FOR PLAINTIFFS REQUESTED PAIN AND SUFFERING DAMAGES V. RELATION TO U.S. TRIAL OUTCOMES VI. CONCLUSION

3 I. INTRODUCTION Pain and suffering and other noneconomic damages awarded by courts have generated much normative and policy debate in the U.S. (see, e.g., Bovbjerg, Sloan, and Blumstein 1988; Croley and Hanson 1995; Geistfeld 1995; McCaffery, Kahneman, and Spitzer 1995; Viscusi 1996; Diamond, Saks, and Landsman 1998; Vidmar, Gross, and Rose 1998; Niemeyer 2004; Avraham 2005; Geistfeld 2005; Rabin 2005; Sharkey 2005; Avraham 2006; Sugarman 2006; Viscusi 2007: 120) and elsewhere (Flatscher Tho ni et al. 2013a; 2013b). In Taiwan, doctors have long contended that the medical malpractice law, which can lead to millions of Taiwan dollars (NTD) in pain and suffering damages, has caused young generations of doctors to choose high profit and low risk specialties, such as plastic surgery and dentistry, rather than surgery. 1 Concerns about the unpredictability of damages have led to controversial caps on noneconomic damages, such as the California Medical Injury Compensation Reform Act (MICRA) of 1975, 2 and to caps on punitive damages in many states. Statutes capping damages have generated much litigation under U.S. state constitutions (Love 2012). Taiwan s highest judicial authority, the Judicial Yuan, has commissioned a leading tort scholar to develop a regression model to help judges determine the amount of pain and suffering damages. Whether pain and suffering damages and other noneconomic awards are too capricious is also an important question in European legal systems (Karapanou and Visscher 2010a). The stakes of connecting pain and suffering damages to underlying measurable quantities are high. Noneconomic damages are a substantial fraction of all damages (Bovbjerg, Sloan, and Blumstein 1988; Viscusi 1988: ; Avraham 2006). Lack of a rational basis for them would call into question about half or more of tort damages. Pain and suffering damages also are an instance of unbounded damages, which generate positively skewed award distributions (Kahneman, Schkade, and Sunstein 1998; Guthrie, Rachlinski, and Wistrich 2000), which in turn lead to reform proposals (e.g., Kahneman, Schkade, and Sunstein 1998). The other major category of unbounded damages, also skewed, is punitive damages. If pain and suffering damages cannot be connected to objective quantities, it might be inferred that punitive damages, which are less related to the victim s harm, are even less explicable. One test of pain and suffering damages is whether they are associated with objective damages measures in cases. For example, the amount of medical expense, economic damages, and the severity of injury (Flatscher Tho ni et al. 2013b) are expected to be associated with the amount of pain and suffering damages. Significant associations would be evidence of rationality in pain and suffering awards since greater medical costs and more severe injuries likely are associated 1 In a famous recent case, three doctors and the hospital that hired them had to pay 2.5 million NTD (roughly 0.83 million US Dollars) in pain and suffering damages for negligent treatment. 2 Cal. Civ. Code (West 1997 & Supp. 2013). MICRA limits damages for noneconomic losses in actions for professional negligence against health care providers to $250,000. 3

4 with objectively more pain and more suffering. The absence of associations would, absent other explanatory factors, be evidence of arbitrariness in a system. Connections between pain and suffering damages and objective loss measures have been infrequently studied, probably because detailed data rarely are available. 3 Prior empirical investigations of pain and suffering damages utilize datasets from insurance companies (Viscusi 1988), insurance regulators (Kritzer, Liu, and Vidmar 2014), U.S. state court datasets (Hans and Reyna 2011), court cases (Leiter, Tho ni, and Winner 2012; Flatscher Tho ni, Leiter, and Winner 2013, 2014), or combinations of sources (Kritzer, Liu, and Vidmar 2014). But, with the exception of some sources used in Kritzer, Liu, and Vidmar (2014), they lack detailed information about pain and suffering and pecuniary damages. The major determinants of pain and suffering damages thus remain unclear. Are they, for example, strongly associated with the total pecuniary loss or medical expenses? Or are they indeed, as some have alleged, utterly random, as such claims are described in Avraham (2006)? Using randomly sampled cases from Taiwan, we provide two innovative analyses of pain and suffering damages. First, we obtained detailed break downs of damages categories and assess their influences on pain and suffering damages. We find that the career professional judges base their decisions on proxies of pain and suffering exactly what the law mandates. More specifically, the proxies are medical expenses and the level of injury. The victim s annual salary, among other factors, is not influential. The absence of association with salary is important because it avoids providing higher paid workers with greater pain and suffering damages than lower paid workers. The strength of the medical expenses association is important for two reasons. It is obviously rationally related to pain and suffering and suggests a coherence to the damages system. In addition, medical expenses outperform other pecuniary components of damages in explaining pain and suffering. This is evidence of judges distinguishing between the components of pecuniary damages less likely to be associated with pain and suffering. Second, our data include the amount of pain and suffering damages requested by the plaintiff. This allows us to assess whether, holding constant the exogenous influences on pain and suffering damages, the amount the plaintiff requests is associated with the amount the judge awards. If the requested amount independently influences the awarded amount, that may be evidence that anchoring is at work. Since the defendant almost never supplied the court with a pain and suffering damages amount, the expected direction of the anchoring effect is reasonably clear. As the plaintiffs requests for pain and suffering damages increased, anchoring theory would forecast that the judge awarded more in such damages. Plaintiff s request, holding constant other variables, has a substantial, statistically significant, and positive effect on the pain and suffering award. This could be interpreted as real world evidence for the anchoring effect. This 3 Sharkey (2005: ) notes that although the National Center for State Court project has tried to code the components of economic and noneconomic damages, the data were so incomplete that the Center would rather not publish them. 4

5 contributes to the empirical literature as well as to the policy debate. For example, plaintiffs in a handful of states in the U.S. are not allowed to bring up a concrete compensation amount (the ad damnum clause) (Franklin, Cardi, and Green 2008: 299), partly due to concerns over the anchoring effect. Yet in many states, plaintiffs can specify a dollar amount, on the assumption that juries or judges are free to regard it as irrelevant (Diamond et al. 2011: ). Therefore, for policy reformers in either type of jurisdiction, it is critical to ascertain whether the ad damnum clause creates the anchoring effect. Our findings lend empirical foundation to this policy debate. Our Taiwan data are rare in being a non U.S. source of pain and suffering damages information. We exploit these novel data by comparing the Taiwan results with analogous data from U.S. trial outcomes. We find little evidence that noneconomic damages form a higher percentage of total damages in the U.S. than in Taiwan. We do, however, present evidence that noneconomic awards, by both U.S. juries and judges, are higher per unit of economic damages than in Taiwan. Our research also extends the prior pain and suffering literature to the study of career judges in a civil law country. Part II of this article describes Taiwan s law relating to pain and suffering damages. Part III addresses our hypotheses and methodology. Part IV reports and discusses our results. Part V addresses the results relation to U.S. data, and Part VI concludes. II. TAIWAN S PAIN AND SUFFERING DAMAGES LAW Pursuant to Articles 193 and 195 of the Taiwan Civil Code, victims of a tortious act can request the tortfeasor to pay pecuniary damages and pain and suffering damages. 4 For example, medical doctors can be liable to a patient for both types of damages if they fail to diagnose her cancer or other major diseases. Courts in Taiwan 5 break down damages in such cases into ten sub categories, as shown in Table 1. We will sometimes use the labels in Table 1 to refer to damages types. 4 Taiwan Civil Code art 193I states: If a person has wrongfully damaged to the body or health of another, and caused the injured person to lose or decrease his laboring capacity, or to increase the need in living, the tortfeasors shall be bound to make compensation to the injured person for any injury arising therefrom. Taiwan Civil Code art. 195I states: If a person has wrongfully damaged to the body, health, reputation, liberty, credit, privacy or chastity of another, or to another's personality in a severe way, the injured person may claim a reasonable compensation in money even if such injury is not a purely pecuniary loss. 5 Judges in Taiwan are career judges who serve on the bench after passing a judiciary examination and receiving training for 2 years. As of 2013 December, there is no jury system in Taiwan, though a pilot program on introducing lay observer system is under way (Huang and Lin 2013). 5

6 Table 1 Types of awarded damages Label Expense type Expense item A1 Already incurred medical treatment and operation A2 Already incurred* nursing care, medical devices, and nutritious food E1 Estimated future medical treatment and operation E2 Estimated future* nursing care, medical devices, and nutritious food A3 Already incurred victim s lost salary during hospitalization and recovery E3 Estimated future victim s future lost salary (discounted to present value or paid as annuities), if the tortious act decreases the victim s capability to work and earn A4 Already incurred increased travelling expenses (e.g., taxi fares to and from hospitals) A5 Already incurred property damages (e.g., repair fee for damaged cars) E4 Estimated future other expenses (including, among others, increased travelling expenses) PS pain and suffering damages * A2 and E2 can each be further divided into nursing care, medical devices and nutritious food, but during the coding process, we pool these three items together. No formula exists for courts to determine the amount of pain and suffering damages. The civil code provides no guidance and no conventional wisdom or rules of thumb exist for quantifying pain and suffering. The plaintiff generally simply claims an amount, contending that it is just, with little supporting evidence. The court decisions usually start with a template discussion (stating that the socioeconomic status, total asset, annual income, age, educational background, etc. of both sides, the plaintiff s level of pain and harm, the plaintiff s negligence, the defendant s repentance, and so on have to be taken into account), 6 then summarizes the facts of the case at hand, and at the end awards an amount. Judges likely consider all facets of the case holistically, perhaps take a quick look at the decisions by their colleagues, and then follow their gut feelings. It is doubtful to what extent the factors listed in the template arguments match the key elements in a judge s heuristic decision making process. 7 Plaintiffs do not have an incentive to claim unrealistically high amounts of pain and suffering damages. First, the court fee is proportionate to the amount of claimed total damages (roughly, around 1% of the total claimed damages). 8 Second, the losing party has to pay the court fee. In a tort lawsuit, usually the plaintiff has to pay part of the court fee if the court does not grant all her claims. The plaintiff generally has to pay [1 (court award/plaintiff s claim)] court fee. So claiming a 6 Not all courts use the same template. The factors that a court explicitly claims to take into account slightly differ. 7 In unreported tables, we explored the factors that Taiwanese courts purport to have considered in determining pain and suffering damages. The tables, however, suggest no clear pattern. 8 Pursuant to Article of Civil Procedure Code of Taiwan, the court fee is assessed in the following way: 1,000 NTD on the first NTD100,000 of the price or claim's value, and an additional amount shall be taxed for each NTD10,000 thereafter in accordance with the following rates: NTD100 on the portion between NTD100,001 and NTD1,000,000 inclusive; NTD90 on the portion between NTD1,000,001 and NTD10,000,000 inclusive; NTD80 on the portion between NTD10,000,001 and NTD100,000,000 inclusive; NTD70 on the portion between NTD100,000,001 and NTD1,000,000,000 inclusive; and NTD60 on the portion over NTD1,000,000,000. A fraction of NTD10,000 shall be rounded up to NTD10,000 for purposes of taxing court costs. 6

7 high amount of pain and suffering damages increases both the court fee and the probability of bearing the cost of a higher percentage of the court fee. Taiwan can generally be considered as a civil law country. Almost all judges are career judges who may or may not have (most didn t) practiced law before serving on the bench. Most jurists in Taiwan major in law as an undergraduate, whereas a minority of jurists are trained in a JD like graduate program. Jurists who pass the bar exam and finish six months of practical training are qualified to practice law. Jurists who pursue a career as judges or prosecutors have to take the court officer examination. Those who pass the examination will receive training in the court officer institutes for two years. At the end of their training, based on their grades, preferences, and openings, they will become judges or prosecutors. Judges are tenured, and thus presumably less influenced by external political influences. For civil matters, there are three levels of courts: district courts, appellate courts, and the supreme court. The former two can determine both questions of fact and questions of law, while the supreme court only deals with questions of law. Appealing to the appellate court is as of right, whereas large stake cases represented by attorneys can be appealed to the supreme court, subject to its discretion (Eisenberg and Huang 2012; Chen, Huang, and Lin 2014). III. HYPOTHESIS AND METHODOLOGY A. Research Questions Our core research question is to identify the major determinants of courtadjudicated pain and suffering damages. Our dataset contains detailed information regarding the components of damages (we can break down, in every case, total damages into ten components; see Table 1). Avraham (2006: 112) conjectures that pain and suffering damages might be positively correlated with medical costs (see also Epstein 1999: 442), but points out that the data available only enable researchers to test pain and suffering damages versus all kinds of pecuniary damages mixed together (Avraham 2006: 114). Kritzer, Liu, and Vidmar (2014) provide a review of the relevant literature and a rare study of the relation between noneconomic damages and economic damages. They report a mixture of consistent and inconsistent patterns across multiple data sets. They conclude (Kritzer, Liu, and Vidmar (2014: 38) that there tends to be considerably more variability in the relationship between non economic and economic damages than between punitive and compensatory damages. Our detailed data allow us to assess which subcategory of pecuniary damages is most strongly correlated with pain and suffering damages. The issue is normatively important. For example, if adjudicators use plaintiffs future lost salaries as a reference point, white collar workers would tend to receive more pain and suffering damages, while it is unclear whether high wage earners suffer from more pain than the low wage earners for a given bodily injury, and whether the rich would need more compensation to ease their pain (Avraham 2006: 114). Pecuniary damages to property would be another example of dubious anchors. In lawsuits involving car accidents, such a reference effect would give Lexus 7

8 owners more pain and suffering damages than Toyota owners. Using medical expenses as the benchmark would make more sense because medical expenses should be a reasonable proxy for the seriousness of the injury, which in turn is a reasonable proxy for the amount of pain the victim endures. 9 Our first hypothesis is that the pain and suffering award will be associated with objective losses and injury severity in the case, as studies of U.S. juries have found. Hans and Reyna (2011: 141), using U.S. state court data, found that the amount of noneconomic damages is positively correlated with that of pecuniary damages. Other empirical studies have also found that that jury determined pain and suffering damages are neither random nor capricious; rather, pain and suffering damages are often some multiples of the plaintiff s pecuniary losses, or at least significantly correlated with the pecuniary losses (Bovbjerg, Sloan, and Blumstein 1988; Viscusi 1988: ; Geistfeld 1995: 787) 10 and injury severity (Flatscher Tho ni et al. 2013b). The level of injury has been empirically demonstrated to affect the amount of pain and suffering damages (Vidmar, Gross, and Rose 1998). As our database contains an index of the level of injury as well as the amount of medical expense, we are able to examine the effects of both these factors. Secondly, judges, in determining a number absent legislative guidance, are likely to be subject to the anchoring effect. 11 That is, another number, even an arbitrary or irrelevant one, might influence the amount of pain and suffering damages. In a tort lawsuit that leads to awards of pain and suffering damages, several salient numbers may exist. Pecuniary damages or components of them may influence awards. Such influences may be positively and normatively relevant to the amount of pain and suffering. More harm, higher medical bills, and other factors may reflect greater pain and suffering and one cannot readily separate out such direct influences from possible anchoring effects unrelated to pain and suffering. Judges appear to be influenced by meaningful and other anchors (Rachlinski, Guthrie, and Wistrich 2006). In this article, as elaborated below, we focus on examining the anchoring effect created by the plaintiff s requested amount of pain and suffering damages. B. The Data Using carefully chosen keywords, we limited the cases yielded by our search to ones the plaintiff won. We limit our search to the district court cases rendered between January 1, 2008, and December 31, The research period was chosen because other research teams in Taiwan have collected data on similar issues before 2008 and are collecting data on similar issues resolved in appellate courts. Our data thus fill in a potential data gap. Moreover, we focus on decisions by the court of first 9 Courts in Taiwan will review the receipts of the expenses and only award the plaintiff with reasonable expenses. Due to the national health care system that covers most basic medical treatments and medication, only medical expenses that are not covered by the health care plans (such as co pay and certain special medicines) can be recovered by the victim. 10 For critique of this practice, see e.g. Geistfeld (1995: 787). 11 For introduction to the anchoring effect, see, e.g., Ariely (2008: 25 48); Kahneman (2011: ); Teichman and Zamir (2014). 8

9 instance. As emphasized by Guthrie, Rachlinski, and Wistrich (2007: 4) and Eisenberg and Heise (2013), most cases are handled by them, many of these decisions are final in that they are not appealed, and such cases avoid the selection issues that arise in studying appellate cases, such as the parties decisions to appeal and settlement of cases pending appeal. Small claim and simple proceeding cases are excluded because the judgments in these cases usually do not contain enough information about the cases. We searched for and coded pain and suffering damages cases related to personal injury. We limit our search to two types of tort cases: medical malpractice and car accident. After filtering out irrelevant cases, there are surprisingly few medical malpractice cases that end with an award of positive pain and suffering damages. We coded all 46 of them. By contrast, more than 3,000 car accident cases showed up in our search. We coded a random sample of one tenth of the car accident cases. To assure geographic representation of the whole country, we stratified the sample by judicial district to obtain 10% of car accident cases from each jurisdiction. This resulted in 302 car accident cases in our dataset. We examined whether substantial differences in awards existed across courts. There was no significant difference in the ratio of pain and suffering damages to non pain and suffering damages across the courts (Kruskal Wallis p=0.33; ANOVA (log of ratio) p=0.19). 12 The absence of difference persisted when we subdivided the sample into car accident cases and medical malpractice cases. The absence of intercourt difference persisted when using the ratio of pain and suffering damages to total damages. As Figure 1 shows, the pain and suffering damages awarded by courts in Taiwan exhibit a somewhat bell shaped distribution (after a log transformation) around $10,000 US. 13 The skewed distribution supporting the log transformation is typical of unbounded award outcomes. The pain and suffering damages in medical malpractice cases, if awarded at all, is no less than $3,333 US (100,000 NTD). In all but three cases, courts in Taiwan awarded pain and suffering damages in multiples of 100,000 NTD. The most common amounts were 100,000; 150,000; 200,000; 300,000; 400,000; and 500,000 NTD. By contrast, court adjudicated medical expenses end with two or more zeros in only 17 cases. This preference for round number in noneconomic damages is consistent with Hans and Reyna (2011: ) gist based model of juries. 12 In a regression model that accounts for the sample design, the p value is Throughout this paper, the conversion rate is US Dollars: Taiwan Dollars=30:1. 9

10 Figure 1. Distribution of court adjudicated pain and suffering damages in Taiwan personal injury cases Car accident Medical malpractice Percent Pain and suffering damages (log10 USD) Note. Amounts are in U.S. dollars and the figure includes 341 Taiwan court cases decided from 2008 through Table 2 provides selected summary statistics of the dataset. Panel A summarizes continuous variables and Panel B summarizes categorical variables. Car accident cases comprise 98% of the sample and medical malpractice cases 2%. 10

11 Table 2. Summary Statistics Panel A: Continuous variables N Mean Median St. Dev. Min. Max. Court adjudicated PS damages* een 12,857 6,667 16, ,667 Plaintiff s requested PS damages * ,826 16, , ,333,334 % of plaintiff s PS request awarded Court adjudicated medical expenses* (A1+A2+E1+E2) ,986 2,994 57, ,511 Court adjudicated past lost salary* (A3) 131 5, , ,900 Court adjudicated future lost salary* (E3) 93 67,299 33,333 97, ,021 Court adjudicated nonmedical expenses* (A4+A5+E4) 224 4,437 1,765 6, ,900 Years of permanent lost earning capacity Annual income used to compute future lost salary* 63 10,082 7,933 5,111 6,000 33,070 % of lost earning capability Number of plaintiffs Number of defendants % of plaintiff s negligence % of court fee paid by plaintiff Plaintiff s annual income* ,234 10,560 22, ,957 Defendant s annual income* ,653 8,000 25, ,116 Plaintiff s current total assets* , , ,000,000 Defendant s current total assets* , ,658,380 Panel B: Categorical variables N % Plaintiff is a minor Corporate defendant Plaintiff with attorneys Defendant with attorneys Cases transferred from criminal court Tort types 349 Body injury 100 Fail to diagnose latent illness.3 Case types 349 Car accident 98 Medical malpractice 2 Injury types 349 Injured 76 Seriously injured 21 Vegetative 3 Type of plaintiffs (car accidents cases only) 300 Pedestrian 15 Bicyclist 3 Motorcyclist / motorcycle passenger 70 Sedan driver / sedan passenger 7 Truck driver / truck passenger 3 Other 2 Type of defendants (car accidents cases 301 Pedestrian 0.3 Motorcyclist 22 Sedan driver 56 Truck driver 14 Taxi driver 2 Other 6 Type of defendants II (car accident cases 302 Human 84 11

12 Government agency 0.7 Human + corporation 15 Human + government agency 0.3 Year Note. PS = pain and suffering. The A1 and similar abbreviations are explained in Table 1. Amounts column reports amounts adjusted to reflect the use of a 10% sample for car accident cases. * In US Dollars. Only amounts greater than zero are included. C. Regression Models 1. One Equation Models In addition to presenting correlation coefficients and other descriptive statistics, we also report regression models that account for stratifying the sample by court district, the 10% sampling of car accident cases, and the nonindependence of observations in cases with more than one plaintiff. The dependent variable is the natural log of the judge s pain and suffering damages award. The independent variables considered for inclusion control for types of pecuniary damages, characteristics of both parties, and the nature of the tort action. 14 Year and court fixed effects are also included. The models take the following form: PS= α+ βpec + θpl + ηdf +γtype+ ρyr + ΩCT+ ε where PS is the log of pain and suffering damages; PEC are variables representing pecuniary damages in natural log form; PL and DF are several variables capturing the characteristics of the plaintiff and the defendant, respectively; TYPE is a group of variables controlling for the nature of the disputes, particularly the tortious acts; YR and CT are dummy variables indicating the years and jurisdictions of the case, respectively. The coefficients to be estimated are α, β, θ, η, ρ, γ, and Ω; ε is an error term. More specifically, PEC includes one variable, court adjudicated medical expenses, that is used in all regression models, and one variable, future lost salary (E3), that is used in one model. 15 Medical expenses include the costs of medicines, 14 Oren Bar Gill suggests to us that whether the victim was present in the courtroom and whether the victim s injury is visible to the judge may affect the amount of pain and suffering damages. From the written decisions, we can hardly tell whether the victim was present. We interviewed a few attorneys and judges, and were informed that most attorney represented victims do not show up in the courtroom. While a few self represented victims would try to show their scars to the judges, most plaintiffs rely on photos and medical reports to demonstrate their injuries, because the tort lawsuits usually take place months after the accident, and most wounds would have healed. We go back to the written decisions and try to code a dummy variable on whether the injury would be visible, and it turns out that (at least part of) the injuries in almost all cases are visible. Therefore, we do not change our models. 15 We omit nonmedical expenses from our models, because including them greatly reduces our degrees of freedom, and the reported correlation coefficients and unreported regression models 12

13 doctor s visits, hospital expenses, medical devices, nursing care, and nutritious food (A1+A2+E1+E2). In one model, we include three variables that are components of future lost salary. They are number of years of lost earning capacity (using a square root transformation to promote normality), plaintiff s annual income (in natural log), and percentage of lost earning capability. 16 In four models, damages for nonmedical expenses are included as a variable. PL and DF include the natural log of the number of plaintiffs and naturalperson defendants; a dummy variable for whether the defendants include a corporation; a dummy variable for whether the plaintiff is a minor; a dummy variable for whether the parent of the minor defendant will incur vicarious liability (in car accident cases only); a dummy variable for whether only medical doctors are the defendants in medical malpractice cases or whether medical institutions are listed as defendants; 17 and dummy variables for whether the plaintiff and the defendant are represented by attorneys. 18 In car accident case models, we consider for inclusion dummy variables that capture whether the plaintiff or the defendant was a pedestrian, rode a bike or a motorcycle, or drove a sedan, taxi, truck, or other vehicle. We also distinguish whether the parties were a driver, a passenger, or a pedestrian. In unreported regression models, we also include the plaintiff s and defendant s annual incomes. Alternatively, we include the plaintiff s current total asset value and the defendant s current total asset value. 19 TYPE includes dummy variables capturing whether the victims were merely injured (the reference category), seriously injured, or vegetative. We classify a victim as vegetative if such a state is indicated in the judgment. Injury and serious injury are distinguished based on the standard in the Criminal Code of Taiwan. A serious injury is one of the following conditions: 1. Destruction of or seriously damage to the sight of one or both eyes; 2. Destruction of or serious damage to the hearing of one or both ears; 3. Destruction of or serious damage to the function of speech, taste, or smell; 4. Destruction of or serious damage to the function of one or more limbs; 5. Destruction of or serious damage to the power of reproduction; and 6. Other serious injury to body or to health that is either impossible or difficult to cure. TYPE also includes a continuous variable representing the proportion of the plaintiff s comparative negligence (in our dataset, from 0 to 0.75); a dummy variable indicating whether the case was transferred from criminal court; a dummy variable that distinguishes car accident cases from medical malpractice cases; another indicate that these expenses are not statistically significantly related to the court adjudicated pain and suffering damages. 16 In some cases, victims lose working and earning capacity only for a few years. In the regression models, we use the three component variables of the future lost salary only if the victim loses part of the capability permanently (there are 64 such observations) 17 In the reported regressions, we drop this insignificant variable to save degrees of freedom. 18 We have also tried the natural log of the numbers of attorneys representing the plaintiffs and defendants. The result is essentially the same. 19 As shown by the frequencies in Table 2, there are many missing values for annual income and total assets of plaintiffs and defendants. Including these variables in the regression models would greatly reduce the number of observations and degrees of freedom. Thus we exclude them in the reported models. In unreported models, neither the income nor the asset variables is statistically significant. 13

14 dummy variable that further distinguishes, in medical malpractice cases, whether doctors performed sub standard treatments/operations or failed to diagnose a latent cancer/illness. Percentage of court fee paid by the plaintiff, described above, 20 is also included in the regression models. Because it is based on the plaintiff s degree of success, it might be questionable as an explanatory variable but proved insignificant and of little effect. YR is a series of dummy variables (one for each year) that controls the timing of the judgment. CT are a series of court dummy variables that control for the variance among jurisdictions. We combine 12 of the 20 courts to produce a set of four dummies for courts that have few observations. The combinations are based on geographic proximity and similarity in economic development. Although we consider all of the above variables for inclusion in models, we report results for subsets of variables selected based on theoretical importance and Least Angle Regression, a model building algorithm that values parsimony as well as accuracy (Efron et al. 2004). 2. Structural Equation Model Our data include the amount plaintiffs requested in pain and suffering damages. Such information has not been available in prior pain and suffering studies. In the interest of simplicity, we do not include it in the above single equation regression models due to endogeneity. The requested amount is not independent of other explanatory variables such as medical expenses and degree of injury. But the requested amount is of obvious interest and potential importance. It might be expected to influence the awarded amount in two ways. First, higher requested amounts put higher numbers before the judge. Anchoring theory suggests that higher requested numbers will be associated with higher awarded numbers independently of the merits of an increased award. Second, higher requested amounts may be associated with factors that should increase awards but that are not represented by observable variables in a single equation regression model. The plaintiff s attorney, in formulating the requested amount, may have access to information about the degree or nature of pain and suffering that we cannot observe. To account for the more complex relationship among the variables in models that include the plaintiffs request, we employ a structural equation model. IV. FINDINGS AND DISCUSSION A. Medical Expenses and Level of Injury Best Explain Pain and Suffering Damages The amount of pain and suffering damages awarded is not random. Table 3 shows the correlation coefficients among pain and suffering damages, pecuniary damages, medical expenses, past and future lost salary, and percentage of lost 20 See note 8 supra and accompanying text. 14

15 earning capability. It demonstrates that pain and suffering damages are strongly and statistically significantly correlated with pecuniary damages (or its two components, medical expenses and future lost salary). 21 Judged from the correlation coefficients, damages for medical expenses is the category of damages most strongly associated with the amount of pain and suffering damages. The difference in the correlation coefficients for the relation between pain and suffering damages and (1) total pecuniary damages, and (2) medical expense damages is small so it is reasonable to use either damages amount to explain pain and suffering damages. Nevertheless, it is notable that medical expenses are slightly more strongly associated with pain and suffering than are total pecuniary damages. This stronger, though statistically insignificant, association persists in regression models of pain and suffering damages that account for the sample design and that include only medical expenses or only total pecuniary damages, as well as in regression models that include both variables and dummy variables for the level of injury. 22 With respect to the other key individual component of pecuniary damages, lost salary (or its component, percentage of lost earning capability) and medical expenses are more highly correlated with pain and suffering damages. The amount of lost salary (incurred before the judgment) is the component most weakly correlated with pain and suffering damages. The stronger association of medical expense damages with pain and suffering damages persists in the 127 cases that contain awards for both past lost salary and medical expenses. In a regression model of pain and suffering damages that includes past lost salary, medical expenses and seriousness of injury, medical expenses are highly statistically significant (p<0.001), past lost salary is not statistically significant (p=0.350), and the difference between the two damages components is significant at p= The stronger association of medical expense damages with pain and suffering damages persists in the 87 cases that contain awards for both future lost salary and medical expenses. In a regression model of pain and suffering damages that includes future lost salary, medical expenses and seriousness of injury, medical expenses are highly statistically significant (p<0.001), future lost salary is significant (p=0.017) with a coefficient about half as large as that for medical expenses, and the difference between the two damages components is significant at p= Note, however, that in 28 of the 47 medical malpractice cases, victims request only pain and suffering damages. 22 The number of observations with nonzero amounts for total pain and suffering damages and medical expenses is similar so directly comparing them is informative. The stronger association between pain and suffering damages and medical expense damages persists if one limits the sample to the 311 observations with data for both total pecuniary damages and medical expense damages. 23 The variance inflation factor for these model suggests no problem of multicollinearity. 15

16 Table 3. Correlations among pecuniary damages, medical expenses, lost salary, and pain and suffering damages Total pecuniary Pain and Medical Past lost damages Future lost suffering expenses salary (A1+A2+A3+A4+A5 salary damages (PS) (A1+A2+E1+E2) (A3) +E1+E2+E3+E4) Total pecuniary <0.001 damages 319 Medical expenses <0.001 < Past lost salary <0.001 < Future lost salary <0.001 <0.001 < % of lost working <0.001 <0.001 < <0.001 capacity Note. Abbreviations are as in Table 1. The first row in each cell shows the correlation coefficient; the second row statistical significance; and the third row N. Damages and expenses are logs. Only damages and expenses that are positive (non zero) are included here. Only cases in which victims permanently lost working capacity are included for future lost salary. Given the strong correlation between medical expenses and pain and suffering damages, Table 4 further examines the correlations of pain and suffering damages with the four components of medical expenses. It shows that future caring expenses have the strongest correlation with pain and suffering damages, but such expenses are only awarded in 51 observations. The medical treatments and operations that the victim has paid for (awarded in most observations) also demonstrate intermediate correlation with pain and suffering damages. 16

17 Table 4. Correlations among pecuniary damages and the medical expense components Future Pain and Future medical Incurred medical caring suffering treatments & treatments & expenses damages (PS) operations (E1) operations (A1) (E2) Future Medical treatments & operations Future caring < expenses Incurred medical < treatments & operations Incurred Caring < expenses (A2) Note. Abbreviations are as in Table 1. The first row in each cell shows the correlation coefficient; the second row the statistical significance; and the third row N. Damages and expenses are in natural log form. Only damages and expenses that are positive (non zero) are included here. Figure 2 further explores the strongest correlations from Table 3. It shows the relation of pain and suffering damages to total pecuniary damages in its first row of graphs and the relation of pain and suffering damages to total medical expenses in its second row of graphs. The graphs further refine the analysis by showing the relations to pain and suffering damages separately for three classes of injury and for both medical malpractice cases and car accident cases. The strong linear relations persist across injury level and case type, except that the number of cases with vegetative injury is too small to support firm inferences. The relations are similar for all three injury levels, as suggested by the similar correlation coefficients in Table 3. 17

18 Figure 2. Scatterplots of court adjudicated pecuniary damages (first row) and medical damages (second row) versus pain and suffering damages Pain & suffering damages (log10 USD) Pain & suffering damages (log10 USD) Injury Total pecuniary damages (log10 USD) Injury Total medical damages (log10 USD) Serious injury Total pecuniary damages (log10 USD) Serious injury Total medical damages (log10 USD) Vegetative Total pecuniary damages (log10 USD) Vegetative Total medical damages (log10 USD) Car accident case Medical-malpractice case Note. The first row of graphs shows the relation between pain and suffering damages and total pecuniary damages. The second row of graphs shows the relation between pain and suffering damages and medical damages. The columns show the data by characterization of injury. Amounts are in U.S. dollars and the figure includes 319 (first row) and 311 (second row) Taiwan court cases decided from 2008 through Since medical expenses are more strongly associated with pain and suffering awards than are total pecuniary damages, it is natural to explore the relation between pain and suffering awards and the nonmedical components of pecuniary damages. Some component of pecuniary awards must be less strongly associated with pain and suffering damages. Figure 3 shows the relations between pain and suffering damages and (1) future lost salary, and (2) total nonmedical pecuniary damages. The first row of graphs shows the relation between pain and suffering damages and future lost salary. Compared to Figure 2, it indicates that the association between pain and suffering damages and lost salary is noticeably weaker than the association between pain and suffering damages and medical expenses. Although the correlation coefficients between pain and suffering damages and (1) medical expenses, and (2) future lost salary are reasonably similar in Table 3, that similarity is attributable to pooling heterogeneous injury types. Separation by injury type, as shown in Figure 3, establishes a greater difference in the two individual measures relations to pain and suffering damages. Indeed, Figure 3 indicates that, in the injury and vegetative categories, no linear relation between lost salary and pain and suffering damages exists. This is confirmed by correlation 18

19 coefficients subdivided by injury level. Table 3 s correlation coefficient of 0.500, significant at p<0.001, does not persist by injury level. The correlation coefficient for injury cases is 0.104, significant at p=0.724, for serious injury cases, 0.377, significant at p=0.014, and for vegetative cases, 0.253, significant at Figure 3 s second row of graphs confirms a similar pattern when the focus shifts from lost salary to total nonmedical nonpecuniary damages. Figure 3. Scatterplots of court adjudicated future lost salary (first row) and total nonmedical pecuniary damages (second row) versus pain and suffering damages Pain & suffering damages (log10 USD) Pain & suffering damages (log10 USD) Injury Future lost salary (log10 USD) Injury Nonmed. pecun. damages (log10 USD) Serious injury Future lost salary (log10 USD) Serious injury Nonmed. pecun. damages (log10 USD) Vegetative Future lost salary (log10 USD) Vegetative Nonmed. pecun. damages (log10 USD) Car accident case Medical-malpractice case Note. The first row of graphs shows the relation between pain and suffering damages and future lost salary. The second row of graphs shows the relation between pain and suffering damages and total nonmedical pecuniary damages. The columns show the data by characterization of injury. Amounts are in U.S. dollars and the figure includes 64 (first row) and 263 (second row) Taiwan court cases decided from 2008 through Only cases in which victims permanently lost working capacity are included in the first row. B. Evidence from Regression Results Part IV.A presents evidence that medical damages are strongly associated with pain and suffering damages and that the nonmedical component of pecuniary damages is much less strongly associated with pain and suffering damages. This result is important because medical costs are more naturally associated with pain and suffering than nonmedical costs. That medical costs better explain pain and suffering damages than do total pecuniary damages is evidence that judges do not simply focus on higher numbers in assessing pain and suffering. They seem more 19

20 influenced by the component of damages, medical costs, most associated with pain and suffering. In further exploring this result, the importance of both individual damages categories and injury level support using regression analysis to account for more than one influence on pain and suffering damages. While Figures 2 and 3 separate the influences by injury level, our detailed data, as summarized in Table 2, supply many other possible influences on pain and suffering damages. We therefore report results based on the regression models described in Part III.C above. As Table 2 indicates, we have a plethora (over 60) of possible explanatory variables to consider using in regression models. The variables of primary interest are those associated with measurable damages, such as medical expenses, and the dummy variables that qualitatively code for the nature of the injury. We have more additional possible explanatory variables than may be reasonable to use given the desirability of parsimonious models. Aside from the variables of prime theoretical interest, we employed Least Angle Regression (LARS) (Efron et al. 2004), a model selection method that improves on traditional stepwise methods, to assist with variable selection. Table 5 reports five regression models. Models (1) and (2) are the baseline regression models with all observations and variables beyond those of prime interest as informed by LARS. Models (3) (6) include only car accident cases and LARS was separately used on the car accident cases to help select additional variables. Models (3) and (4) include variables regarding the defendant but omit variables regarding future lost salary, to preserve the number of observations. Permanent future lost salary awards in cases with nonmissing covariates were present in only 54 cases. Models (2) and (4) include the sum of pecuniary nonmedical expenses as an additional explanatory variable. Model (5) includes three variables that are the major components of future lost salary. Model (6) differs from Model (5) in that the former uses one variable that captures the amount of future lost salaries to replace the three component variables. Model (7) includes only medical malpractice cases and only variables of prime interest were used due to the small sample size. Table 5 s models indicate that medical expenses are highly statistically significantly associated with pain and suffering damages (p<0.001 in all but one models). The expenses are strongly associated with pain and suffering damages in all models. For Model (1), after adjusting for the log transformations, a 1% increase in medical expenses is associated with a 0.28% increase in pain and suffering damages. In Model (2), which includes nonmedical pecuniary expenses as an explanatory variable, the increase associated with a 1% increase in medical expenses is 0.25%. The smallest influence is in Model (6), in which a 1% increase in medical expenses is associated with a 0.18% increase in pain and suffering damages. Unlike medical expenses, nonmedical pecuniary damages are inconsistent and small in their association with pain and suffering damages. An association at the 95% level of significance only emerges in Model (4). There a 1% increase in nonmedical expenses is associated with a 0.05% increase in pain and suffering damages compared to the 0.25% increase associated with medical expenses. Based on Figure 3 s second row of graphs, this variable is most strongly associated with 20

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