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

• Published date: 01 March 2017
• DOI: http://doi.org/10.1111/jels.12145
• Date: 01 March 2017

Pain and Suffering Damages in Personal

Injury Cases: An Empirical Study

Yun-chien Chang,* Theodore Eisenberg, Tsung Hsien Li, and

Martin T. Wells

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 dataset 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 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

Address correspondence to Prof. Yun-chien Chang, Institutum Iurisprudentiae, Academia Sinica, 128 Academia

Road, Section 2, Taipei City 11529, Taiwan; email: kleiber@sinica.edu.tw. Chang is Associate Research Professor

and Director of Center for Empirical Legal Studies, Institutum Iurisprudentiae, Academia Sinica; Eisenberg is

the late Henry Allen Mark Professor of Law and Adjunct Professor of Statistical Science, Cornell University; Li is

Adjunct Assistant Professor of Criminology, National Chung Cheng University, Taiwan; Wells is Charles A.

Alexander Professor of Statistical Sciences, Cornell University.

We thank for comments Yehuda Adar, Ronen Avraham, Oren Bar-Gill, Arianne Renan Barzilay, Omri

Ben-Shahar, Alexandre Biard, Bernie Black, Jianlin Chen, Ruoying Chen, Shari Diamond, Elliott Fan, Michal Gal,

Fernando Gomez, Alice Guerra, Gregory Keating, Valerie Hans, Jim Hines, Jr., Han-wei Ho, William Hubbard,

Ehud Kamar, Gregory Keating, Sandy Kedar, Omer Kimhi, Daniel Klerman, Hui-Wen Koo, Shay Lavie, Alex Lee,

Ming-Jen Lin, Xifen Lin, Jin-Tan Liu, John MacDonald, Allen Miller, Chengxin Peng, Ariel Porat, Amnon Reich-

man, Daria Roithmayr, Issi Rosen-Zvi, Emily Ryo, Avi Tabbach, Neil Vidmar, Wolfgang Weigel, Mark Weinstein,

Judge Andrew J. Wistrich, Abby Wood, Tsong-Min Wu, Jonathan Yovel, 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 Universit~a della Svizerra Italiana; the 2014 American Law and

Economics Association Annual Meetings held at the University of Chicago; 2014 Asian Law and Economics Asso-

ciation Annual Meeting at National Taiwan University; 2014 European Association of Law and Economics at

Aix-en-Provence, France; Law and Social Science Workshop at USC Law School; Law and Economics Workshop

at Tel Aviv University, Faculty Workshop at Haifa University Faculty of Law; Economic History Workshop at

National Taiwan University Department of Economics; Economics Workshop at National Taipei University

Department of Economics, and National Cheng Kung University Department of Economics; and at lectures at

Joseph von Sonnenfels Center for the Study of Public Law and Economics at University of Vienna, Austria; Hong

Kong University Faculty of Law. We also thank the judges at the Taipei District Court and Judicial Yuan, Taiwan,

who provided valuable feedbacks to this project. Yueh Hsun Yang, Charline Jao, Alice Kuo, Hilary Tsai, and

Christine Yuan provided research assistance.

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Journal of Empirical Legal Studies

Volume 14, Issue 1, 199–237, March 2017

and suffering fraction of total damages in Taiwan. Judges and juries consistently produce

coherent patterns of noneconomic damages.

I. Introduction

Pain and suffering and other noneconomic damages awarded by courts have generated

much normative and policy debate in the United States (see, e.g., Bovbjerg et al. 1988;

Croley & Hanson 1995; Geistfeld 1995, 2005; McCaffery et al. 1995; Viscusi 1996,

2007:120; Diamond et al. 1998; Vidmar et al. 1998; Niemeyer 2004; Avraham 2005, 2006;

Rabin 2005; Sharkey 2005; Sugarman 2006; Ubel & Loewenstein 2008). Concerns about

the unpredictability of damages have led to controversial caps on noneconomic dam-

ages,

1

such as the California Medical Injury Compensation Reform Act (MICRA) of

1975,

2

and to caps on punitive damages in many states (Miceli & Stone 2013:114–15).

Statutes capping damages have generated much litigation under U.S. state constitutions

(Love 2012). Whether pain and suffering damages and other noneconomic awards are

too capricious is also an important question in European legal systems (Karapanou &

Visscher 2010a; Flatscher-Th€

oni et al. 2013, 2014). In Taiwan, doctors have long con-

tended that the medical malpractice law, which can lead to millions of Taiwan dollars

(NTD) in pain and suffering damages, has caused the younger generation of doctors to

choose high-profit and low-risk specialties, such as plastic surgery and dentistry, rather

than surgery. The highest judicial authority in Taiwan, the Judicial Yuan, has commis-

sioned a leading tort scholar to develop a regression model to help judges determine

the amount of pain and suffering damages. In short, the stakes of assessing whether

pain and suffering damages are reasonable and predictable are high.

From the law and economics perspective, a prerequisite for the torts system to

achieve optimal deterrence is setting damages at expected losses (if not the actual

losses) of victims (Shavell 2004:240–43). Nonetheless, even when willingness to pay/

accept is taken as the benchmark for quantifying pain and suffering, it is still difficult

for judges to set expected losses accurately (for the difficulty of assessing the value of

life, cf. generally Sunstein 2014:85–136). As Shavell (2004:242) notes, in the case of non-

pecuniary losses, the better approach is using simple tables or formulas to assess pain

and suffering damages to save administrative costs. Indeed, Ramseyer’s (2015:10–34)

study on the Japanese torts system shows that because the Japanese Supreme Court uses

publicly available tables to assess pain and suffering damages and court-published

1

For instance, 31 states have adopted caps on noneconomic damages or total damages in medical malpractice

lawsuits (Paik et al. 2016). Pain and suffering damages also are an instance of unbounded damages, which gener-

ate positively skewed award distributions (Kahneman et al. 1998; Guthrie et al. 2000), which in turn lead to

reform proposals (e.g., Kahneman et al. 1998).

2

Cal. Civ. Code § 3333.2 (West 1997 & Supp. 2013). MICRA limits damages for noneconomic losses in actions for

professional negligence against health-care providers to $250,000.

200 Chang et al.

handbooks to determine comparative negligence, most parties involved in traffic acci-

dents settled. To strike a balance between optimal deterrence and saving administrative

costs, making pain and suffering damages predictable and reasonable is arguably

second-best, as Ramseyer (2015) suggests.

While most people would agree that $1 dollar or $1 trillion for pain and suffering

damages are unreasonable, in most real-world cases, it is hard to make persuasive argu-

ments that the court-adjudicated awards are reasonable or not. Unless a barometer can

be developed to measure and compare pain and suffering and a reliable formula can be

used to inform decisionmakers how much money is sufficient to ease pains, assessing

reasonable pain and suffering damages is an impossible mission.

Consequently, policymakers should focus on the predictability of pain and suffer-

ing damages. Predictability does not ensure optimal deterrence, but unpredictability

dooms optimal deterrence. Predictability also facilitates settlements. Unpredictability

increases health insurance premiums that further make certain efficient actions unsus-

tainable (Bovbjerg et al. 1988:908; Geistfeld 1995:786; Avraham 2006:95–97). Damages

based on tables or formulas are generally predictable, but not all jurisdictions have fol-

lowed this scheme—for countries such as Taiwan and the United States, it is worth

exploring whether discretionary pain and suffering awards connect to measurable

factors.

There are two types of predictability: statistical and legal. Statistical significance of

key variables and high goodness of fit make pain and suffering damages predictable in a

statistical sense. Yet to be predictable in a legally relevant way, the key variables have to

be easily measured by parties before litigation and closely related to the legal issue. For

instance, medical expenses and levels of injury are arguably good proxies for pain and

suffering, and they are easily ascertainable by the two parties without judicial adjudica-

tion. Below we demonstrate that pain and suffering damages in Taiwan are to a large

extent statistically and legally predictable. Granted, the R-squares of our OLS models

are not close to 1, and a few variables, such as plaintiffs’ comparative negligence, have

counterintuitive signs and statistical significance. These types of variables make pain and

suffering damages statistically predictable but perhaps less legally predictable, as com-

parative negligence is difficult to ascertain by the two parties and its effect would sur-

prise them.

Connections between pain and suffering damages and objective factors have been

infrequently studied, probably because detailed data rarely are available.

3

That is, wheth-

er pain and suffering damages are statistically predictable is understudied. Prior empiri-

cal investigations of pain and suffering damages utilize datasets from insurance

companies (Viscusi 1988), insurance regulators (Kritzer et al. 2014), U.S. state court

datasets (Hans & Reyna 2011), court cases (Cohen & Miller 2003; Leiter et al. 2012;

Flatscher-Th€oni et al. 2013, 2014), or combinations of sources (Kritzer et al. 2014). With

3

Sharkey (2005:448--49) 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.

201Pain and Suffering Damages in Personal Injury Cases