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International Review of Law and Economics 30 (2010) 203–208

Contents lists available at ScienceDirect

International Review of Law and Economics

egal change and the social value of lawsuits

homas J. Miceliepartment of Economics, University of Connecticut, 341 Mansfield Road, Storrs, CT 06269-1063, United States

r t i c l e i n f o

rticle history:eceived 15 June 2009eceived in revised form 23 February 2010ccepted 2 April 2010

EL classification:4041

a b s t r a c t

This paper integrates the literatures on the social value of lawsuits, the evolution of the law, and judicialpreferences to evaluate the hypothesis that the law evolves toward efficiency. The setting is a simpleaccident model with costly litigation where the efficient law minimizes the sum of accident plus litigationcosts. The analysis shows that the law will not generally evolve completely toward any one rule, but willreach a steady state equilibrium in which the distribution of rules depends both on the selective litigationeffect and the nature of judicial bias. The analysis also links legal change with the social value of lawsuitsto allow an explicit evaluation of the lawmaking function of trials.

eywords:fficiency of the lawudicial decision makingegal change

© 2010 Elsevier Inc. All rights reserved.

recedentelection effectalue of lawsuits

. Introduction

This paper contributes to three distinct literatures that bear onhe efficiency of the legal process for resolving legal disputes. Therst strand concerns the social versus private value of lawsuits, an

ssue first studied by Shavell (1982).1 His main conclusion was thathe private value of suits, which depends solely on the plaintiff’sxpected gain at trial, will not generally coincide with their socialalue, which depends on their ability to induce injurers to invest infficient accident prevention. As a result, there may be either tooany or too few lawsuits from a social perspective. An important

ocial benefit of lawsuits not generally addressed by this literature,owever, is their lawmaking function.2 That is, to what extent canrials improve the efficiency of the law by periodically allowingudges to evaluate existing legal rules and replace them with morefficient ones?

This question is the subject of a separate strand of literaturehat began with Posner’s early conjecture that common law judgesctively promote efficiency. Posner’s logic was that, because com-

on law judges “cannot do much. . .to alter the slices of the pie that

arious groups in society receive, they might as well concentraten increasing its size” (Posner, 2003, p. 252). Dissatisfied with theeliance of this argument on the nature of judicial preferences, how-

E-mail address: Thomas.Miceli@uconn.edu.1 Also see Menell (1983), Kaplow (1986), Rose-Ackerman and Geistfeld (1987),

nd Shavell (1997, 1999).2 Most studies mention this benefit in passing, but do not examine it in detail.

144-8188/$ – see front matter © 2010 Elsevier Inc. All rights reserved.oi:10.1016/j.irle.2010.04.002

ever, Rubin (1977, 2005) and Priest (1977) identified market-like(invisible hand) forces that tend to propel the law toward efficiencywithout the conscious help of judges. The gist of these “evolutionarymodels” is that, because inefficient rules generally result in casesinvolving higher stakes, those rules are more likely to end up attrial where they can be adjudicated and, assuming that judges arenot biased against efficiency, eventually replaced by more efficientrules. This important insight is referred to as the “selective litigationhypothesis.”

The key element of the Rubin-Priest model is the litigationstakes—that is, the amount the parties to a dispute stand to gainor lose. In particular, legal change will favor the side with higherstakes. A slightly different approach focuses on the information con-tent of legal rules. Hylton (2006), building on earlier work by Priest(1980) and Priest and Klein (1984), showed that when the partiesto a dispute are asymmetrically informed about the merits of theircase, the law will tend to evolve in the direction of the party “whois both informed and has the stronger case” (Hylton, 2006, p. 48).In terms of the implications for efficiency, one would expect thatthis “information bias” would tend to improve the efficiency of the

law, though Hylton shows that the effect is not unambiguous.

A third strand of literature has sought to re-introduce judgesinto the lawmaking process by explicitly examining the nature ofjudicial preferences.3 The role of judges in actively shaping the law

3 See, for example, Higgins and Rubin (1980), Cohen (1991), Miceli and Cosgel(1994), and Posner (1995, chap. 3).

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04 T.J. Miceli / International Review of

s epitomized by Horowitz’s (1992) well-known hypothesis thathe emergence of the negligence rule in tort law was the result ofconscious effort by judges to subsidize economic development

especially railroads) at the onset of the industrial revolution. Sev-ral recent papers have sought to model the impact of judicialreference (or bias) on legal change. Whitman (2000), for example,iews judges as balancing the gain from imposing their personalreferences on the law against the reputational cost of reversal ifubsequent judges depart from their rulings. His results show thathe common law may oscillate between competing rules ratherhan settling on a single one, depending on the strength of judges’sersonal preferences over the law and how divergent their viewsre. In terms of efficiency, the problem with an oscillatory outcomes that it undermines the predictability of the common law.

In companion papers, Gennaioli and Shleifer (2007a,b) showhat if some fraction of judges are biased for one side or the other inlegal dispute, then, to the extent that they have the power (or the

nclination) to depart from precedent,4 they can affect the directionf legal change, possibly driving it away from efficiency.5 Fon andarisi (2003) similarly show that the existence of pro-plaintiff andro-defendant judges, when coupled with rational filing decisionsy plaintiffs, create a tendency for the law to evolve in a pro-plaintiffirection.6

The current paper borrows heavily from the characterization ofudicial bias in these papers, but it goes further to examine thenteraction between judicial bias and the Rubin-Priest selectiveitigation effect to derive the long run (steady state) equilibriumistribution of legal rules.7 The analysis substantially extends anarlier study by Miceli (2009) that also examined the interactionetween selective litigation and judicial bias. The major conclu-ions of that paper were that when judges are unbiased, the law willvolve toward efficiency according to the selective litigation effect,ut that judicial bias can overturn this conclusion if it is strongnough. The current paper extends these results in two impor-ant ways. First, it shows that the law will not generally evolveompletely toward any one rule, but will reach a steady state equi-ibrium under which the distribution of rules depends both on theelective litigation effect and the nature of judicial bias. Second,t links the model of legal change, as driven by selective litigationnd judicial bias, with the literature on the social value of lawsuits,hereby allowing an explicit evaluation of the lawmaking functionf trials.

The argument is developed as follows. Section 2 sets up a simplenilateral care accident model to serve as the basis for the analysis.ection 3 describes the nature of legal change within the context ofhat model and derives the distribution of legal rules in the steadytate equilibrium. Section 4 then uses comparative static analysis

o examine how a change in the nature of judicial bias affects thequilibrium distribution of legal rules. In particular, it shows thathere is both a direct effect that pushes the law in the directionavored by judges, but also an indirect effect through the impact

4 The authors distinguish between “overruling” precedent, and “distinguishing”new law from precedent. The difference is not important for present purposes.5 Zywicki (2003) notes that during the formative stages of the common law, thereas competition among courts (a supply-side effect), that presumably would haveeeded out biased or incompetent judges. Such a force, however, is largely absent

oday.6 Hylton (2006) includes a type of judicial bias in his model in the form of legal

rror. Random legal error is not the same thing as bias, however, in that error doesot systematically favor one side or the other in a legal dispute but simply increasesncertainty.7 Gennaioli and Shleifer (2007b) consider the impact of selective litigation in theirodel of overruling, but they treat it in a superficial way that does not allow a careful

xamination of its interaction with judicial bias in determining the direction of legalhange. In particular, they assume that the divergence of beliefs by litigants aboutrial (which is what precludes settlement) is unrelated to the nature of judicial bias.

nd Economics 30 (2010) 203–208

of judicial bias on the selection of disputes that reach trial, whichmay either counteract or reinforce the direct effect. Section 5 turnsto the link between the equilibrium distribution of legal rules andthe lawmaking function of trials in order to address the questionof whether the law evolves toward efficiency. Finally Section 6concludes.

2. The model

To provide an explicit basis for the lawmaking process, we con-sider a unilateral care accident model in which potential injurersand victims interact a fixed number of times (or with a fixed prob-ability) over a given time interval, where each interaction is a“potential accident.” In anticipation of each interaction, injurers(defendants) choose a level of care, x, that determines the prob-ability of an accident, p(x), per interaction (i.e. per unit of time),where p′ < 0, p′′ > 0. In the event of an accident, the victim (plaintiff)suffers a random loss, L, which we assume is uniformly distributedon [0, L̄] with a density of f (L) = 1/L̄ and an expected value of L̄/2.The plaintiff observes her loss, but the defendant does not, thoughhe knows the distribution of losses. If an accident occurs, the plain-tiff decides whether or not to file suit. If she files, the plaintiff anddefendant engage in pretrial bargaining which results in a settle-ment or a trial. We examine the pretrial period in reverse sequenceof time, beginning with the settlement decision.

2.1. The settlement decision

Given the defendant’s inability to observe the plaintiff’s specificlosses, he makes a take-it-or-leave-it offer S, which the plaintiffaccepts or rejects. If she accepts, the case ends. If she rejects, thecase goes to trial, where the plaintiff expects to win with probabilityw, which both parties observe.8 Thus, the expected value of trial toa plaintiff who has suffered a loss of L is

Vp(w) = wL − Cp, (1)

where Cp is the plaintiff’s cost of a trial.Given (1), a plaintiff of type L will accept the defendant’s settle-

ment offer of S if and only if S ≥ Vp(w), or if and only if

L ≤ S + Cp

w≡ L̂(w), (2)

where the critical value, L̂(w), is decreasing in w. Thus, for any givensettlement offer, the higher is the plaintiff’s probability of winningat trial, the less likely is a settlement.

Consider next the determination of the defendant’s optimal set-tlement offer, S*. Recall that the defendant is assumed not to beable to observe the particular loss of the plaintiff prior to trial, buthe knows w. Thus, he chooses S to minimize his expected costs.

8 The asymmetric information model employed here is originally due to Bebchuk(1984). Subsequent authors have pointed out that, within the context of this model,the type of cases that settle and the type that go to trial will depend on whetherthe plaintiff or the defendant has better information prior to trial. See, for example,Baird, Gertner, and Picker, (1994, pp. 260–261), Shavell (1996), and Spier (2007, pp.272–277). In the current model, however, the key parameter regarding the selectionof cases for trial is the plaintiff’s probability of victory at trial, w, which is knownby both parties. In this setting it can be shown that an increase in w will makea trial more likely regardless of which party has private information. (The resultcorresponds to the prediction that cases with higher stakes are more likely to go totrial, which is true regardless of the nature of the informational asymmetry.) Thus,the particular assumption regarding the nature of the private information does notaffect our key results.

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that a judge who disagrees with precedent overrules it. The mag-nitude of ˇ (which is independent of the particular rule in place)thus represents an index of the strength of precedent.12

T.J. Miceli / International Review of

pecifically, the defendant’s problem is to

inS

(L̂

L̄

)S +

∫ L̄

L̂(w)

[wL + Cd

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here Cd is the defendant’s trial cost. The first order conditionefining S* is given by

ˆ(w) = Cp + Cd

w(4)

ubstituting from (2) we obtain

∗ = Cd (5)

hus, the optimal settlement offer is simply equal to the defendant’srial costs. Substituting this into (2) yields the equilibrium thresholdor plaintiffs9:

ˆ ∗ (w) = Cp + Cd

w(6)

t follows that the probability of a trial, given an accident, is

T(w) = 1 − F(L̂ ∗ (w))

= 1 − Cp + Cd

wL̄

(7)

here ∂T/∂w > 0. Thus, given the occurrence of an accident, aigher plaintiff win rate increases the probability of a trial, all elsequal.

Finally, we assume that S* exceeds the filing costs of plaintiffswhich we take to be zero). Thus, all plaintiffs, whether or not theyxpect to go to trial, will file suit in the event of an accident.10

.2. The accident and trial rates

As noted above, the probability of an accident for eachnjurer–victim interaction is determined by the defendant’s choicef care. Define A*(w) to be the minimized costs of the defendanturing the settlement-trial stage. That is, A*(w) is the minimizedalue of (3). Thus, prior to each interaction, the defendant choosesto solve

inx

x + p(x)A ∗ (w) (8)

he resulting first order condition is

+ p′A ∗ (w) = 0 (9)

hich defines the optimal care level, x*(w). Differentiating (3), andpplying the Envelope Theorem, we find that

∂A∗∂w

= −f (Cp + Cd)

(∂L̂∗∂w

)+

∫ L̄

L̂∗LdF(L) > 0 (10)

hich implies that ∂x*/∂w > 0. A higher plaintiff win rate thusncreases the defendant’s expected costs from litigation, and hencencreases his incentive to take care. Finally, the accident rate,*(w) ≡ p(x*(w)), varies with w as follows:

∂p∗ ′(

∂x∗)

∂w= p

∂w< 0. (11)

n increase in w thus reduces the accident rate by enhancing theefendant’s incentive to take care.

9 We assume that (Cp + Cd)/w < L̄ so that some cases go to trial. Obviously if thisere not the case, legal change could not occur.

10 As a result, some cases whose expected value at trial is negative will succeed inbtaining a settlement (Bebchuk, 1988).

nd Economics 30 (2010) 203–208 205

The expected number of trials per injurer–victim interaction (i.e.per unit of time) can now be written as the product of the accidentand trial rates:

N(w) = p ∗ (w)T(w). (12)

Differentiating, we obtain

∂N

∂w= T

∂p∗∂w

+ p ∗ ∂T

∂w, (13)

which is ambiguous in sign. Whereas a higher plaintiff win ratereduces the accident rate by enhancing incentives, it increases thetrial rate by making trials more valuable to plaintiffs.

2.3. The evolution of legal rules

In order to investigate the evolution of legal rules through thelitigation process, and specifically, the proposition that the lawevolves toward efficiency, we first need to be explicit about therules for allocating liability in our simple accident model. To keepthe model simple, we consider only two rules: strict liability (SL)and no liability (NL).11 Strict liability will induce more care by injur-ers, which lowers the accident rate, but it also leads to lawsuits,which are costly. Thus, depending on which effect dominates interms of overall social costs, either rule may be efficient. At thispoint, however, we are only interested in what determines thedistribution of the two rules.

Suppose that, at any point in time (i.e. prior to any injurer–victiminteraction), both rules exist in the population of legal rules in somearbitrary proportion (Whitman, 2000). Suppose, for example, thatthe law is in a state of change, as was true of tort law during thenineteenth century (Horowitz, 1992), or products liability law dur-ing the twentieth century (Epstein, 1980). In particular, let � be theproportion of SL and 1−� the proportion of NL. (Alternatively, onemay think of � as the probability that SL is in place at any point intime.) We assume that each potential accident involves just oneof these rules, and that both the injurer and victim know withcertainty which type of rule applies to their particular interaction.

The possibility of legal evolution requires that laws change, butthis can only happen at trial. That is, cases that settle can haveno effect on the state of the law. When a case goes to trial, thejudge can either uphold the prevailing rule, which means findingfor the plaintiff if the rule is SL and finding for the defendant if therule is NL, or he can overrule the prevailing rule. Obviously, sincethere are only two rules, overruling means replacing SL with NL andvice versa. (Thus, we do not allow judges to fashion new or hybridrules like negligence.) We suppose that two factors affect a judge’sdecision in this regard: precedent and judicial bias.

A judge who follows precedent simply enforces the prevailingrule. Since strict adherence to precedent permits no legal change,we assume that precedent has some strength but is not completelybinding. Specifically, let ˇ be the probability that a judge who dis-agrees with a precedent follows it, while 1 − ˇ is the probability

11 A perfectly functioning negligence rule would potentially achieve the first bestoutcome in which injurers take optimal care and no suits are filed. Such a rule isnot particularly interesting in a model of legal change, however, since, once therule is hit upon, no further change would occur. Nor is it very realistic, since sometrials clearly do occur under negligence. See Hylton (1990) for such a model, wherenegligence differs from NL and SL only in terms of the probability of plaintiff victory.Specifically, the probability of plaintiff victory under negligence is greater than thatunder NL but less than that under SL.

12 It could also represent something about the distribution of judges regardingtheir respect for precedent (e.g. the proportion of activist judges versus strict con-

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As for judicial bias, we suppose that there are two types ofudges: pro-plaintiff (PP), and pro-defendant (PD) (Fon & Parisi,003; Gennaioli & Shleifer, 2007a,b). PP judges favor SL and willlways apply it when it is the prevailing precedent. In addition,hey will apply it with probability 1 − ˇ when it is not the precedent.onversely, PD judges favor NL, so they will always apply it when

t is the precedent, and will apply it with probability 1 − ˇ whent is not the precedent. Let ı represent the fraction of PD judgesi.e. those who favor NL), while the remaining fraction, 1 − ı, are PPthose who favor SL).

We can now calculate the win probabilities, wj, for plaintiffsnder each of the two rules (j = SL, NL). This involves calculatinghe probability that the court will apply SL, the pro-plaintiff rule.irst, if SL is the prevailing rule, it will automatically be applied byll PP judges and by those PD judges who follow precedent. Thus,e have

SL = (1 − ı) + ıˇ. (14)

In contrast, if NL is the prevailing rule, all PD judges will applyt, as well as those PP judges who follow precedent. Thus,

NL = (1 − ı)(1 − ˇ). (15)

Comparing (14) and (15), we find that wSL > wNL if and only if> 0, which we assume is true. Thus, as long as precedent has some

orce, SL results in a higher win probability for plaintiffs, reflectingts pro-plaintiff orientation. We also assume that ˇ < 1, for other-

ise, wNL = 0, in which case plaintiffs would never file suit underL, and the law, once it settled on NL, would never evolve away from

t, regardless of the efficiency of the law or the nature of judicialreferences.

Returning to the above settlement model, we can now state thathe probability of a trial given that a suit has been filed is highernder SL than under NL; that is, TSL > TNL. This follows from the facthat ∂T/∂w > 0. Intuitively, the higher win probability for plaintiffsnder SL makes trials more valuable, all else equal, thereby increas-

ng the probability that any given case will go to trial. Likewise,he accident model implies that defendant care is higher under SLx*SL > x*NL), and correspondingly, that the probability of an acci-ent is lower under SL (pSL* < pNL*). These conclusions follow fromhe fact that ∂A ∗ /∂w > 0. Intuitively, a higher win rate for plaintiffsncreases defendants’ expected cost, thus inducing them to investn greater care, which in turn results in fewer accidents.

The preceding implies that the expected number of trials,j = pj*Tj, may be larger or smaller under SL compared to NL.hereas SL results in fewer accidents, it leads to a higher probabil-

ty of trial given an accident. This is a crucial factor in determininghe evolution of the law since the number of trials under a par-icular rule determines the frequency with which that rule comesefore the court to be adjudicated.

. The determination of equilibrium

As time unfolds, the process of litigation will cause the distri-ution of legal rules to evolve as cases come before the court to bedjudicated. As noted above, judges have biases and are imperfectly

ound by precedent, so they will occasionally overturn laws basedn their preferences. In this section, we investigate this evolutionnd derive the resulting steady state equilibrium distribution of thewo rules.

tructionists). See Miceli and Cosgel (1994) and Whitman (2000). Also see Fon, Parisi,nd Depoorter (2005), who study the impact of accumulated judicial rulings on thetrength of precedent, producing what they call “judicial path dependence” in theaw.

nd Economics 30 (2010) 203–208

To proceed, suppose that there is some initial fraction of SL rules,�0, and suppose that litigation occurs over a fixed period of time asdescribed in the above model. We can then add up the number(proportion) of SL rules at the end of that period and see how itcompares to �0. Given our characterization of judicial behavior, SLcan emerge from the litigation process in four ways. First, if no acci-dents occur when SL is the prevailing rule, it will not be litigated andthus will remain in place. This occurs with probability �0(1 − pSL*).Second, if an accident does occur, the case may settle before reach-ing court. In this case, which occurs with probability �0pSL*(1 − TSL),the rule will also remain in place. Third, if an accident occurs underSL and the case goes to trial, the judge may uphold the rule. Thiswill happen either if the judge is pro-plaintiff (PP), or if the judgeis pro-defendant (PD) but chooses to follow precedent. The com-bined probability of these two outcomes is �0pSL*TSL[(1 − ı) + ıˇ].Finally, SL can emerge from an accident involving NL if the casemakes it to court and the judge overturns precedent (an eventthat will only occur if the judge is PP). The probability of this out-come is (1 − �0)pNL*TNL(1 − ı)(1 − ˇ). Summing these probabilitiesyields the proportion of SL at the start of the next cycle of litigation,denoted �1:

�1 = �0(1 − pSL∗) + �0pSL ∗ (1 − TSL) + �0pSL ∗ TSL[(1 − ı) + ıˇ]

+ (1 − �0)pNL ∗ TNL(1 − ı)(1 − ˇ) (16)

To derive the steady state equilibrium, set �1 = �0 = � in (16) andsolve for � to obtain

� = pNL ∗ TNL(1 − ı)pNL ∗ TNL(1 − ı) + pSL ∗ TSLı

= NNL(1 − ı)NNL(1 − ı) + NSLı

. (17)

We will refer to (17) as the “selection ratio.” Note that it dependson the relative number of trials that arise under each of the tworules, and the distribution of judicial bias. Interestingly, it does notdepend on the strength of precedent, ˇ. Thus, while the strengthof precedent affects the rate of legal change (i.e. the “stickiness” ofrules, or how long it takes to reach the steady state), it does notaffect the ultimate (long run) distribution of legal rules.

Several special cases emerge from (17), depending on the distri-bution of judicial bias. First, if ı = 0, then � = 1. Thus, if all judges arePP, then the law will eventually fully converge to SL. Conversely, ifı = 1 (all judges are PD), then � = 0; that is, the law will fully convergeto NL. Finally, if ı = 1/2, (17) becomes

� = NNL

NNL + NSL. (18)

In this case, judges are on average “unbiased.” Thus, the lawevolves according the “pure” selection effect. Note that the law willnot generally evolve fully toward either rule, but instead will settleat a steady state equilibrium in which the proportion of a given ruleequals the conditional probability that a case going to trial involvesthe other rule. Intuitively, the more often a rule comes to trial, themore chances it has to be overturned by a judge and replaced bythe other rule. Conversely, if a rule rarely comes to trial, it will haveless chance to be overturned.

The interpretation of the steady state equilibrium derived in thissection is that the common law will not generally converge to asingle rule but will instead embody multiple rules, reflecting the

divergent preferences of judges and the selection of cases for trial.In this sense, the outcome resembles the equilibrium described byWhitman (2000) in which multiple rules can persist.13

13 The equilibrium distribution of rules is a description of the overall state of thelegal system at a point in time, as seen by an outside observer. As a referee pointedout, however, this equilibrium does not have any relevance to individual participantsin the system (litigants), who are all assumed to know the particular rule in place intheir jurisdictions. In this sense, the equilibrium value of � is not like an equilibrium

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Moreover, a judiciary that is sufficiently biased against the efficientrule can drive the law away from efficiency in spite of a favorableselection effect (Fon & Parisi, 2003; Gennaioli & Shleifer, 2007a,b).17

T.J. Miceli / International Review of

. The impact of judicial bias on legal change

Given the preceding characterization of the steady state distri-ution of legal rules, it is of interest to determine how a change inhe bias of judges will affect that distribution. This involves doingcomparative static analysis of Eq. (17) with respect to ı, the frac-

ion of pro-defendant judges.14 The sign of the resulting derivatives given by

ign

(∂�

∂ı

)= sign

{−NNLNSL + ı(1 − ı)

[NSL

∂NNL

∂ı− NNL

∂NSL

∂ı

]}.

(19)

The two terms in braces represent two avenues by which judi-ial bias affects legal change. The first term is the direct effect ofn increase in the fraction of pro-defendant judges. It is negativeecause, holding the number of trials under the two rules fixed, an

ncrease in PD judges (those who favor NL) will naturally reducehe fraction of cases in which SL is chosen. In other words, the lawill tend to move in the direction favored by judges (the Horowitz

ffect).The second term in braces is the indirect effect of increasing ı.

t reflects the impact of a change in the distribution of judicial biasn the selection of disputes reaching trial. (Note in particular thathe term in square brackets represents the impact of ı on the pureelection ratio in (18).) It is ambiguous in sign because an increasen ı has opposing effects on the expected number of trials underoth rules. Specifically, ı affects Nj through the plaintiff win rate asollows:

∂Nj

∂ı= ∂Nj

∂wj

∂wj

∂ı, j = SL, NL (20)

here ∂Nj/∂w is ambiguous in sign by (13) (reflecting the opposingffects of w on the accident and trial rates), and ∂wj/∂ı = −(1 −) < 0 for both j = SL and NL by (14) and (15). One suspects that theirect effect will dominate in (19), in which case an increase in theraction of PD judges will have the expected effect of increasing therequency of NL in the population of legal rules. Still, the lesson fromhis section is that overall legal change is driven by a combinationf judicial bias and selective litigation.

. Efficiency of the law

The analysis to this point has examined how judicial bias andelection litigation combine to determine the equilibrium distribu-ion of legal rules, irrespective of the efficiency of those rules. A finalssue concerns the question of whether the above model supportshe hypothesis that the law evolves toward efficiency. Note firsthat in the trivial case where all judges are efficiency-seeking (“Pos-erian”), the model predicts that the law will converge to efficiencyecause the efficiency bias of judges will eventually dominate theelection effect (provided, of course, that the inefficient law is occa-ionally litigated). Specifically, if SL is efficient, then all judges willavor that rule (i.e. ı = 0), and, according to (17), SL will eventuallye the only rule in the population (i.e. � = 1). Likewise, if NL is effi-

ient, all judges will favor it and so it will eventually take over theopulation (i.e. ı = 1 and thus � = 0).

The more interesting question, however, is whether the law willvolve in the direction of efficiency without the help of judges, as

rice that all participants respond to. Still, the model is a useful way of describingow an aggregate index of the legal system emerges from individual optimizingehavior.14 I thank a referee for suggesting the analysis in this section.

nd Economics 30 (2010) 203–208 207

conjectured by Rubin and Priest. To evaluate this argument in themost favorable setting, we assume that judges are unbiased (i.e.ı = 1/2).

To begin, note that efficiency in the current model consists ofminimizing overall accident costs, which include the cost of injurercare, the victim’s damages, and litigation costs. Returning to theabove accident model, we write social costs under rule j (j = SL, NL)as follows:

SCj = xj ∗ +pj ∗ [E(L) + Tj(Cp + Cd)]= xj ∗ +pj ∗ E(L) + Nj(Cp + Cd).

(21)

Strict liability is therefore more efficient than no liability if and onlyif SCSL < SCNL, or if and only if

xSL ∗ −xNL∗ < (pNL ∗ −pSL∗)E(L) + (NNL − NSL)(Cp + Cd), (22)

which is just a generalization of Shavell’s (1982) condition for tri-als to be socially valuable.15 To interpret this condition, recall fromthe above accident model that xSL* > xNL* and pNL* > pSL*, or that SLresults in greater injurer care and hence a lower accident rate. Thus,the left-hand side and the first term on the right-hand side of (22)are both positive. Together, these two terms constitute the stan-dard Hand test for determining whether care is efficient (Hylton,1990). Based on these terms alone, we would conclude that SL isthe more efficient rule due to its superior incentive effects.16 Pos-sibly offsetting this, however, is the impact of litigation costs, ascaptured by the second term on the right-hand side.

The selective litigation effect promotes efficiency in this modelin two ways. The first is through the marginal benefit of care (thefirst term on the right-hand side of (22)). Note that an increase inthis term enhances the efficiency of SL (because care is more pro-ductive), and also increases the number of disputes arising underNL as compared to SL. As a result, the proportion of SL in the popu-lation of rules as defined by (18) will also tend to increase, holdingthe settlement rate fixed.

The second way that selective litigation promotes efficiency isthrough the litigation cost term (the second term on the right-handside of (22)). Note that the sign of this term may be positive or neg-ative, depending on which rule results in more trials. If this termis positive, NL results in more trials, which, in the absence of judi-cial bias, implies that SL will be the dominant rule in the steadystate equilibrium (i.e. � > 1/2). Conversely, if this term is negative,SL results in more trials, which implies that NL will be the domi-nant rule in equilibrium (i.e. � < 1/2). The selection effect thereforeworks in the right direction for efficiency. In particular, the rule thatentails higher litigation costs is less likely to be efficient accordingto (22), while at the same time the higher litigation rate for that rulewill tend to reduce its frequency in the population of legal rules.

Finally, it should be recalled that selection generally will not beable to completely eliminate the less efficient rule in the steadystate unless the judiciary is fully biased toward the efficient rule.

15 Of course, in his simple model, there are no trials under NL and hence no injurercare.

16 Since injurers take less than efficient care under both SL and NL, the rule thatinduces more care (SL) is closer to the efficient outcome.

17 An earlier version of this paper showed that the conclusions in this sectionremain broadly true when the accident model is extended to allow injurer careto affect the victim’s damages as well as the probability of an accident, and whenboth injurer and victim care matter for accident risk.

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Spier, K. (2007). Litigation. In A. M. Polinsky, & S. Shavell (Eds.), Handbook of law and

08 T.J. Miceli / International Review of

. Conclusion

This paper has developed an equilibrium model of legal changeo assess the claim that the common law process has an inherentendency to evolve toward efficiency. The paper contributes to theiterature on the social value of lawsuits, evolutionary models ofegal change, and models of judicial decision making. The goals ofhe paper were, first, to derive the steady state equilibrium distri-ution of legal rules, and second, to identify the relative impactsf selective litigation, judicial bias, and precedent on the resultingistribution of legal rules. The main conclusion is that there existstendency for the law to evolve in the direction of efficiency basedntirely on the self-interested efforts of litigants, but that effect willot generally result in complete elimination of inefficient laws inhe steady state. Moreover, judicial bias can either enhance or offsethis effect, possibly leading the law toward or away from efficiency.

eferences

aird, D., Gertner, R., & Picker, R. (1994). Game theory and the law. Cambridge, MA:Harvard Univ. Press.

ebchuk, L. (1984). Litigation and settlement under imperfect information. RandJournal of Economics, 15, 404–415.

ebchuk, L. (1988). Suing solely to extract a settlement offer. Journal of Legal Studies,17, 437–450.

ohen, M. (1991). Explaining judicial behavior, or what’s constitutional about thesentencing commission? Journal of Law, Economics, and Organization, 7, 183–199.

pstein, R. (1980). Modern products liability law. Westport, CT: Quorum Books.on, V., & Parisi, F. (2003). Litigation and the evolution of legal remedies: A dynamic

model. Public Choice, 116, 419–433.on, V., Parisi, F., & Depoorter, B. (2005). Litigation, judicial path dependence, and

legal change. European Journal of Law and Economics, 20, 43–56.ennaioli, N., & Shleifer, A. (2007a). The evolution of the common law. Journal of

Political Economy, 115, 43–68.ennaioli, N., & Shleifer, A. (2007b). Overruling and the instability of law. Journal of

Comparative Economics, 35, 309–328.iggins, R., & Rubin, P. (1980). Judicial discretion. Journal of Legal Studies, 9, 129–138.

nd Economics 30 (2010) 203–208

Horowitz, M. (1992). The transformation of American law, 1780–1860. New York:Oxford Univ. Press.

Hylton, K. (1990). The influence of litigation costs on deterrence under strict liabilityand under negligence. International Review of Law and Economics, 10, 161–171.

Hylton, K. (2006). Information, litigation, and common law evolution. American Lawand Economics Review, 8, 33–61.

Kaplow, L. (1986). Private versus social costs in bringing suits. Journal of Legal Studies,15, 371–385.

Menell, P. (1983). A note on private versus social incentives to sue in a costly legalsystem. Journal of Legal Studies, 12, 41–52.

Miceli, T. (2009). Legal change: Selective litigation, judicial bias, and precedent.Journal of Legal Studies, 38, 157–168.

Miceli, T., & Cosgel, M. (1994). Reputation and judicial decision-making. Journal ofEconomic Behavior and Organization, 23, 31–51.

Posner, R. (1995). Overcoming law. Cambridge, MA: Harvard Univ. Press.Posner, R. (2003). Economic analysis of law (6th edition). New York: Aspen Publishers.Priest, G. (1977). The common law process and the selection of efficient rules. Journal

of Legal Studies, 6, 65–82.Priest, G. (1980). Selective characteristics of litigation. Journal of Legal Studies, 9,

399–421.Priest, G., & Klein, B. (1984). The selection of disputes for litigation. Journal of Legal

Studies, 13, 1–55.Rose-Ackerman, S., & Geistfeld, M. (1987). The divergence between social and private

incentives to sue: A comment on Shavell, Menell, and Kaplow. Journal of LegalStudies, 16, 483–491.

Rubin, P. (1977). Why is the common law efficient? Journal of Legal Studies, 6, 51–63.Rubin, P. (2005). Why is the common law efficient? In F. Parisi, & C. Rowley (Eds.),

The origins of law and economics (pp. 383–395). Cheltenham, UK: Edward Elgar.Shavell, S. (1982). The social versus the private incentive to bring suit in a costly

legal system. Journal of Legal Studies, 11, 333–339.Shavell, S. (1996). Any frequency of plaintiff victory is possible. Journal of Legal

Studies, 25, 493–501.Shavell, S. (1997). The fundamental divergence between the private and the social

motive to use the legal system. Journal of Legal Studies, 26, 575–612.Shavell, S. (1999). The level of litigation: Private versus social optimality of suit and

of settlement. International Review of Law and Economics, 19, 99–115.

economics (pp. 259–342). Amsterdam: North Holland.Whitman, D. (2000). Evolution of the common law and the emergence of compro-

mise. Journal of Legal Studies, 29, 753–781.Zywicki, T. (2003). The rise and fall of efficiency in the common law: A supply-side

analysis. Northwestern University Law Review, 97, 1551–1563.