BAR-ILAN UNIVERSITY
LAW SCHOOL
(Israel)
Bar-Ilan University Public Law and Legal Theory
Working Paper No. 11-09
09, 2008
Yuval Feldman
Doron Teichman
© Yuval Feldman
Doron Teichman , 2009. All Rights Reserved.
This paper can be downloaded without charge from the
Social Science Research Network Electronic Paper Collection:
http://ssrn.com/abstract=1274854
DRAFT
*
Assistant Professor Bar Ilan University and Assistant Professor the Hebrew University of Jerusalem. For
helpful comments we thank Alon Harel, Richard McAdams, Jeff Rachlinski, Avishalom Tor and
participants of the conference on empirical legal studies at the Hebrew University of Jerusalem. Financial
support for this study was provided by GIF and the Handler Foundation.
Imagine you are offered to play a game at the casino for a cost of one dollar.
According to the rules of the game you must first throw a die and then flip a coin. If you
guessed both events correctly, you win ten dollars. Like a good rational player you turn to
calculate the odds of winning the game, and multiply the probability of the die landing on
your guess (1/6) by the probability of guessing the coin toss correctly (1/2). You then
reach the conclusion that there is a one in twelve chance to win the game. Turning to cost
benefit analysis you realize that the expected benefit from the game (1/12*$10) is smaller
than its cost ($1), and therefore decline the offer to play.
The previous example demonstrates how legal economists treat the decisions of
potential wrongdoers. Namely, within the economic framework the law sets prices for
different activities in the form of legal payments (e.g., fines, damages, etc.). Potential
wrongdoers weight the costs the legal system imposes on them and the benefits from the
activity; and decide to engage in these activities if they create a net benefit for them. One
of the central insights of traditional deterrence theory is that legal payments are, in many
cases, probabilistic. The initial formalization of the theory was introduced by Becker in
his seminal article on crime control.1 As Becker pointed out, what potential criminals
face is the expected sanction, and not just the sanction that is actually imposed on a small
subset of them, and therefore policymakers designing an optimal deterrence regime need
to pay attention to the combination of actual sanctions and the probability of imposing
them. Ever since Becker pointed out the importance of probabilities with respect to policy
design, an abundance of legal literature explored the validity of his model’s positive
assumptions, and the desirability of his policy implications.2 For example, many have
criticized the Becker model for treating changes in the size of the sanction and in the
probability of detection as identical, and argued that potential criminals are more
sensitive to changes in the probability of detection than changes in the size of sanctions.3
Others, on the other hand, have endorsed the Becker model, and suggested to incorporate
its insights into procedural and substantive aspects of private law.4
1
See Gary S. Becker, Crime and Punishment: An Economic Approach, 76 J. POL. ECON. 169, 176 79
(1968) (presenting an analysis of the supply of criminal offenses given the probability of conviction, length
of punishment, and other variables). For later contributions see Isaac Ehrlich, Crime, Punishment, and the
Market for Offenses, 10 J. ECON. PERSP. 43 (1996); STEVEN SHAVELL, FOUNDATIONS OF ECONOMIC
ANALYSIS OF LAW 473 514 (2004).
2
In the text we focus on the critic of the positive aspects of the Becker model, as those are of relevance to
this empirical project. For a normative critic of the model see, e.g., Paul H. Robinson & John Darley, The
Role of Deterrence in the Formulation of Criminal Law Rules: At Its Worst When Doing Its Best, 91 GEO.
L. J. 949 (2003) (arguing that sanctions should be distributed along the lines of just desert rather than
deterrence theory)..
3
See, e.g., Harold G. Grasmick & George J. Bryjak, The Deterrent Effect of Perceived Severity of
Punishment, 59 SOC. FORCES 471 (1980) (reviewing and analyzing the literature on the topic).
4
See David Rosenberg & Steven Shavell, A Simple Proposal to Halve Litigation Costs,
91 VA. L. REV. 1721 (2005) (procedural proposal based on the model); A. Mitchell Polinsky & Steven
One should note, however, that the probability of imposing sanctions is not
determined by a single probabilistic event. Rather, it is determined by a series of
sequential events such as being caught by the police, being charged by the prosecution
and being convicted by a court in accordance to the different procedural rules of the legal
system. From an economic perspective this detail is a minor complexity, and can be
resolved by the tools of expected utility theory. Thus, potential wrongdoers are assumed
to treat the different types of legal probabilities as equal, and simply multiply them in
order to derive the probability of being sanctioned much like the player at the casino.
Exploring the way individuals treat probabilities in general, and legal probabilities
specifically, however, has not been a monopoly of economists. Cognitive psychologists
have studied in great detail different aspects of decision making under conditions of
uncertainty.5 Building on these contributions, legal scholars from the behavioral law and
economics movement have developed theories regarding decision making in uncertain
legal situations.6 For instance, Rachlinski has examined civil litigation in light of prospect
theory, and demonstrated that traditional economic models of litigation that assume
litigants make rational decisions with respect to uncertain situations do not provide an
accurate account of litigation.7
Yet as a general matter the behavioral legal literature dealing with probabilities
has ignored the constitutive role law can make with respect to peoples’ decisions. In other
words, the focus of analysis was on whether different legal situations match the settings
of documented behavioral biases. For instance, after cognitive psychologists taught us
that individuals treat risks associated with gains and risks associated with losses
differently,8 this insight can be applied to legal situations that involve both gains and
losses in order to adjust the predictions of economic models in those situations.9 Thus, it
is the match between the setting created by the law and the pre existing behavioral bias,
which triggered the divergence from the rational choice model, and not the content of law
itself that affected peoples’ behavior.
In a recent study we explored the possibility that the way in which the law labels
payments affects the way people perceive the situation, and the way in which they are
Shavell, Punitive Damages: An Economic Analysis, 111 HARV. L. REV. 869 (1998) (calculating the size of
punitive damages based on the model).
5
The leading early example of a behavioral decision theory model of choice is Kahneman and Tversky's
prospect theory. See Daniel Kahneman & Amos Tversky, Prospect Theory: An Analysis of Decision Under
Risk, 47 ECONOMETRICA 263, 268 69 (1979). For later contributions see, JUDGMENT UNDER
UNCERTAINTY: HEURISTICS AND BIASES (Daniel Kahneman, Paul Slovic & Amos Tversky eds., 1982).
6
For an influential collection of articles in the field see BEHAVIORAL LAW AND ECONOMICS (Cass R.
Sunstein ed., 2000).
7 See Jeffrey J. Rachlinski, Gains, Losses, and the Psychology of Litigation, 70 S. CAL. L. REV. 113 (1996).
For additional studies see Ehud Guttel & Alon Harel, Uncertainty Revisited: Legal Prediction and Legal
Postdiction, ___ MICH. L. REV. ___ (forthcoming 2008).
8
See, e.g., Kahneman & Tversky, supra note 5 at 279.
9
See, e.g., Rachlinski, supra note 7 (presenting the difference between plaintiffs’ decisions that are seen as
gains and defendants’ decisions that are seen as loses).
expected to behave.10 We demonstrated that payments of equal size that the law
structures differently with respect to the timing of the payment (before or after the
wrongful act) and the identity of the recipient (payment to the state or payment to the
victim) have different effects on behavior. More specifically, our results showed that
legal payments function as a continuum with respect to their affects on incentives. At one
end of this continuum lie ex ante payments made to individuals. These payments are
close in structure to a price, and are therefore perceived by people as legitimate. At the
other end of the continuum lie ex post payments made to the state. These payments are
close in structure to the paradigmatic punishment, and are therefore perceived as less
legitimate by people.
In this study we turn to examine differences between different types of legal
probabilities. More specifically, we wish to compare two sources of uncertainty that the
law creates regularly. The first is legal uncertainty.11 Legal rules are inherently uncertain.
This uncertainty can be a result of the limitations of the language, or as a result of
ambiguous legal terms such as “reasonable” and “good faith” that depend on a
probabilistic ex post determination of an adjudicator. The second is enforcement
uncertainty. Legal liability tends to be probabilistic as a result of difficulties associated
with detecting wrongdoers, and assigning legal liability to them in accordance to the
different procedural rules the law sets forth.
From the perspective of rational choice theory the difference between legal
probabilities is much like the difference associated with throwing a die and flipping a
coin in our initial example: there simply is no difference. The expected sanction if
legality is certain and detection is 50% is identical to the expected sanction if detection is
certain and the probability of illegality is 50%. We, on the other hand, conjecture that
much like the case of legal payments, legal probabilities are not fungible from the
perspective of decision makers. Forces such as social norms and the expressive power of
the law coupled with internal aspects of human reasoning might cause people to perceive
different legal probabilities as distinct. More specifically, we assume that uncertainty
with respect to the content of the law leaves people the option of perceiving their acts as
legal, and therefore worthy (or at least not blame worthy).12 On the other hand, in
situations in which illegality is clear, and the sole source of uncertainty is enforcement,
people will be forced to view the behavior itself as wrongful. Thus, we expect to find less
willingness to engage in regulated activities when the source of uncertainty is the
enforcement of a clear law.
10
Yuval Feldman & Doron Teichman, Are All Legal Dollars Created Equal?, 102 NW. U. L. REV. 223
(2008).
11
In the legal literature the accepted terminology describing uncertainty with respect to the content of law
is ambiguity. We intentionally chose not use this terminology since in the cognitive psychology literature
there is a distinction between uncertain situations in which decision makers are aware of the probabilities of
the different contingencies, and ambiguous situations in which decision makers are not aware of the
probabilities. From this perspective our study is a study of decision making under uncertainty and not
ambiguity.
12
For an empirical demonstration of the role of motivated reasoning in the interpretation of uncertain legal
standards see Yuval Feldman & Alon Harel, Social Norms, Self/Interest and Ambiguity of Legal Norms: An
Experimental Analysis of the Rule Vs. Standard Dilemma, 4(1) REV. LAW & ECON. (2008) (Article 6).
To test these predictions, we designed a series of between subjects experimental
surveys that measured and compared participants’ attitudes toward compliance in
conditions of uncertainty. In the scenarios given to participants, their chances of being
sanctioned were identical; the dimension that was manipulated was related to whether the
source of uncertainty was in the legality of the behavior or in the likelihood of
enforcement.13 Overall these studies confirmed our main hypothesis that people will
comply less, when the source of uncertainty is in the law itself, in comparison to
situations where the source of uncertainty is in enforcement but the illegality is clear.
Given the argument that suggests that there are major differences in attitudes toward the
law between Israelis and Americans,14 we conducted one of the studies in the United
States and two of the studies in Israel. Our results in this regard did not detect a
significant difference between the two groups of people.
This Article is organized as follows: In part II we describe the background for the
study. We review the traditional literature dealing with legal probabilities and flesh out
some of its drawbacks. We then present several bodies of literature that point out the
potential differences between different types of legal probabilities. Building on these
studies, we will suggest several hypotheses as to the differences between legal
probabilities in different settings. Part II describes the design of the experiments and their
results. In Part III we discuss our results, explore the potential policy implications, and
deal with some of the limitations of this study. Finally, in Part IV we briefly conclude.
Legal economists, for the most part, view law as a social tool that creates a menu
of prices for harmful behaviors that should be regulated.15 Thus, the “seminal insight” of
the law and economics movement was that the tools of price theory can be employed in
order to predict the way different legal rules will influence peoples’ behavior.16 Based on
this insight, legal economists modeled the incentives created by an array of legal
13
Further dimensions were added in the second and third studies, and explanations about them will appear
in sections III D. and III E. infra.
14
On cross cultural studies generally see Smith, P. B., Peterson, M. F., & Schwartz, S. H., Cultural Values,
Sources of Guidance, and their Relevance to Managerial Behavior: A 47/Nation Study, 33 J. CROSS
CULTURAL PSYCHOLOGY 188 (2002). For discussion of the Israeli society see Yagil, D. & Rattner, A.,
Between Commandments and Laws: Religiosity, Political Ideology and Legal Obedience in Israel, 38
CRIM. L. & SOC. CHANGE 185 (2002). For a review of studies that compare the role of the rule of law in
Israel and in the US and some new data on differences between Americans and Israelis, in a related
dimension of informal enforcement of rule breaking see Yuval Feldman & Orly Lobel, Behavioral versus
Institutional Antecedents of Decentralized Enforcement: An Experimental Approach, ___ Regulation &
Governance ___ (forthcoming 2008).
15
See, e.g., GUIDO CALABRESI, THE COSTS OF ACCIDENTS: A LEGAL AND ECONOMIC ANALYSIS (1970); For
alternative views of law expressed by legal economists see Robert D. Cooter,. Prices and Sanctions, 84
COLUM. L. REV. 1523 (1984).
16
Russell B. Korobkin & Thomas S. Ulen, Law and Behavioral Science: Removing the Rationality
Assumption from Law and Economics, 88 CAL. L. REV. 1051, 1054 (2000) (discussing the rational choice
model proposed by the law and economics movement).
payments. Expectation damages were viewed as the price of breach of contract,17 tort
compensation as the price set for engaging in risky behavior,18 and criminal punishments
as the price criminals must pay if they choose to commit crimes.19
Yet from the outset, law and economics scholars realized that unlike prices for
goods in the marketplace, legal prices are in many cases probabilistic. For example, when
a driver speeds on the highway he will have to pay the legal price for speeding (e.g. the
fine) only in those rare cases in which a police officer actually catches him and writes
him a ticket. Recognizing this, economic models of deterrence starting from Becker’s
seminal paper on crime and punishment did not focus on the sanctions applied to
wrongdoers alone. Rather, they focused on the expected sanction wrongdoers face, which
is calculated by multiplying the size of the sanction by the probability that it will actually
be inflicted on the wrongdoer.
The expected sanction is a complex term that is comprised of several factors.
While, the probability detection draws in many cases most of the attention, a closer view
at the term reveals that aside from detection there are many other probabilities that stand
in the way of sanctioning wrongdoers. After the police detect a wrongdoer, the
prosecution must decide to press charges against him. Different considerations such as
the case load might cause the prosecution not to file charges.20 Similarly, once the
prosecution decides to press charges, the wrongdoer must still be convicted in court
before a sanction can be imposed. Court proceedings can create an array of reasons for
the prosecution to fail to secure a conviction even for a guilty defendant. One group of
such reasons can relate to difficulties to prove the wrongful act at the level of certainty
required by law. Issues such as witness credibility, the ability to produce documents, and
so forth inherently introduce uncertainty into the legal process, and bring about a
probability of conviction for the guilty that is lower than one.
Our focus in this study is on uncertainty created by the law itself. Law is
inherently uncertain. This uncertainty is a result of two main sources. First, uncertainty
can be a result of the limitation of the language to capture every potential occurrence. For
example, it might be unclear whether a law that forbids “vehicles” from entering into the
17
See, e.g., Steven Shavell, Damage Measures for Breach of Contract, 11 BELL J. ECON. 466, 468–69
(1980); Steven Shavell, The Design of Contracts and Remedies for Breach, 99 Q. J. ECON. 121, 122 (1984)
(modeling breach decisions as a function of the cost of performance and the cost set for breach by the legal
system).
18
See, e.g., WILLIAM M. LANDES & RICHARD A. POSNER, THE ECONOMIC STRUCTURE OF TORT LAW
(1987) (modeling the decisions of individuals as to the level of care they take as a function of the liability
they incur through the tort system).
19
See, e.g., Becker, supra note 1 at 176 79 (presenting an analysis of the supply of criminal offenses given
the probability of conviction, length of punishment, and other variables). Later contributions continued this
line of thought and modeled the different substitution effects between legal prices. See Neal Kumar Katyal,
Deterrence’s Difficulty, 95 MICH. L. REV. 2385 (1997) (analyzing substitution between types of crimes);
Doron Teichman, The Market for Criminal Justice: Federalism, Crime Control and Jurisdictional
Competition, 103 MICH. L. REV. 1831 (2005) (analyzing substitution between geographic areas).
20
On the role of prosecutorial discretion in the United State’s criminal justice system see Robert L. Misner,
Recasting Prosecutorial Discretion, 86 J. CRIM. L. & CRIMINOLOGY 717, 728 59 (1996).
park applies to bicycles, roller skates or even toy automobiles.21 Thus, bicycle drivers that
need to decide whether to drive through the park, face uncertainty as to the legal
ramifications of their choice. Second, the law includes an array of standards that depend
on an ex post evaluation of the actors acts in order to impose legal liability. Terms such
as “negligence” in tort law, “good faith” in the contractual setting and “fair use” in the
context of copyright law all create uncertainty with respect to the legal consequences of
an act. Hence, for example, an artist deciding whether to incorporate copyrighted work
into his own work can only reach an educated assumption as to the possibility of legal
liability.
While legal economists recognize the different probabilistic aspects of legal
prices, they treat the different probabilities as fungible from the perspective of potential
wrongdoers. For example, in an influential article that explored the effects of uncertain
legal standards on deterrence theory, Craswell and Calfee explicitly assume that all legal
probabilities are fungible.22 Furthermore, to the extent they are willing at acknowledge
that different probabilities might be treated differently by potential wrongdoers, their
exclusive treatment of the issue focuses on the distinct monetary consequences of
potential contingencies.23 In a more recent paper, Logue examined the design of an
optimal deterrence policy given the ambiguity associated with tax law.24 As Logue points
out, tax law is inherently probabilistic due to its uncertainty.25 This uncertainty can be
described as a continuum: At one end of it lie positions that are clearly illegal (e.g. the
probability of illegality is 100%), while at its other end lie positions that are clearly legal
(e.g. the probability of illegality is 0%). Between these two extremes lies the vast body of
tax law in which the probability of illegality is positive, yet not certain. In his model
Logue assumes that tax payers are rational in accordance with traditional deterrence
models.26 Thus, he assumes that they treat the probabilities associated with detection and
with ambiguity as fungible.
The behavioral legal literature has dealt with different questions associated with
legal probabilities and decision making in the deterrence model extensively. For the most
part, these studies turn to existing studies in the area of cognitive psychology, and explore
how different biases documented in these studies affect the evaluation of different legal
regimes. For example, in a recent study Guttel and Harel examined the legal implications
of the different way people perceive uncertainty relating to the past and uncertainty
relating to the future.27 They first point out the robust psychological literature that
demonstrates that people tend to prefer to take risks with respect to events that will take
21
Alluding to Hart’s famous example in H. L. A. Hart, Positivism and the Separation of Law from Morals,
71 HARV. L. REV. 593, 607 (1958).
22
Richard Craswell & John E. Calfee, Deterrence and Uncertain Legal Standards, 2 J. L. ECON. & ORG.
279, 283 (1986).
23
Id. at note 10.
24
Kyle Logue, Optimal Tax Compliance and Penalties When the Law is Uncertain, 27 VA. TAX REV. 241
(2007).
25
Id. at 251 57.
26
Id. at 244 45.
27
Guttel & Harel, supra note 7.
place in the future and not in the past.28 That done, they turn to review the legal
implications of these findings.29 For instance, they point out that deterrence can be
enhanced by a simple move like determining the identity of the people the tax authority
will audit at the beginning of the tax year rather than at its end.30 In another study closely
related to our project Harel and Segal employ insights from cognitive psychology in
order to compare the way potential criminals treat uncertainty with respect to the size of
sanctions and uncertainty with respect to the probability of detection.31 These insights
lead Harel and Segal to argue that increasing the certainty with respect to the size of
sanctions while decreasing the certainty with respect to the probability of detection may
enhance deterrence.32 This finding allows them to examine an array of legal questions
ranging from the prohibition against retroactive punishment to the structure of the federal
sentencing guidelines.33
While existing studies took the behavioral characteristics of people as given, and
applied them to different legal settings, our approach is different. We view law as an
integral part of decision making, and as a device that in of its own can affect behavior.
Thus, our analysis starts from law, and examines whether the legal characteristic of a
probability affect the way individuals perceive it, and the way they are expected to
behave. We hypothesize that it matters to people whether the source of uncertainty with
respect to a legal payment is lack of enforcement by the police, a large case load on the
local prosecutor, or uncertainty in the law itself. We now turn to review several bodies of
literature that led us to reject the traditional “fungible probabilities” assumption, and
present the competing “non fungible probabilities” hypothesis.
A major body of both theoretical and empirical literature that challenges the view
that legal payments simply reflect prices is the scholarship emphasizing the expressive
value of law. 34 Expressive theories of law consist of an array of distinct claims, including
theories of lawmaking, claims about the connection between the law and social norms,
and positive predictions as to the way different legal expressions affect behavior. In the
context of regulation and sanctioning the basic claim of expressive theories is that a legal
28
Id. at ___ (to be completed after publication).
Id. at ___ (to be completed after publication).
30
Id. at ___ (to be completed after publication).
31
See Alon Harel & Uzi Segal, Criminal Law and Behavioral Law and Economics: Observations on the
Neglected Role of Uncertainty in Deterring Crime, 1 2 AM. L. ECON. REV. 276 (1999).
32
Id. at 294 306.
33
Id. at 306 9.
34
For some prominent examples of this literature see, e.g., Richard H. Pildes & Elizabeth S. Anderson,
Slinging Arrows at Democracy: Social Choice Theory, Value Pluralism, and Democratic Politics, 90
COLUM. L. REV. 2121 (1990); Cass R. Sunstein, On the Expressive Function of Law, 144 U. PA. L. REV.
2021 (1996); Dan M. Kahan, What Do Alternative Sanctions Mean?, 63 U. CHI. L. REV. 591 (1996). For a
critical view see, e.g., Matthew D. Adler, Expressive Theories of Law: A Skeptical Overview, 148 U. PA. L.
REV. 1363 (2000). For empirical studies of the expressive function of the law see Iris Bohnet & Robert D.
Cooter, Experimental Analysis of Expressive Law and Economics, (2000) (Working Paper, UC Berkeley);
and Richard H. McAdams & Janice Nadler, Testing the Focal Point Theory of Legal Compliance:
Expressive Influence in an Experimental Hawk/Dove Game, 2 J. EMPIRICAL LEGAL STUD. 87 (2005).
29
prohibition of an act in itself gives people to act in accordance with the law. Thus, even a
legal rule that is not backed by a sanction is expected to affect peoples’ behavior.35
In the context of our study, to the extent that legal prohibitions carry an
expressive power that independently influences people, two theoretical mechanisms can
explain different behavioral effects of uncertainty in law and uncertainty in enforcement.
First, focusing on enforcement, the expressive power is less affected by the likelihood of
enforcement, as it is less sensitive to sanctions in comparison to the deterring function of
the law.36 Thus, even if the multiplication of probabilities is identical from an
instrumental perspective, from an expressive perspective the question of legality carries
greater meaning, and therefore uncertainty with respect to enforcement is expected to
have a relatively lower effect on the regulated behavior. In other words, given that the
expressive effect is not related solely to the likelihood of conviction but rather to the
message conveyed by the law, uncertainty regarding the illegality of an act carries greater
importance than uncertainty regarding detection. Second, focusing on legal clarity, the
expressive power is more sensitive to the clarity of the law, since part of it stems from the
clear message the law can convey. According to many of the studies that explore the
mechanisms that underlie the expressive function of the law, its power comes from its
ability to communicate a message about morality, social norm or scientific truth.37 Hence,
as the legal norm becomes vague it is reasonable to assume that its expressive effect will
be diminished, and therefore uncertainty with respect to the law is expected to have a
relatively higher effect on the regulated behavior.
A second strand of literature is the socio legal literature dealing with motivations
for legal compliance.38 The classical deterrence perspective focuses on external
motivation and fear of sanction.39 The opposite perspective suggests that much of the
motivation to obey the law is related to internalized values and moral reasoning.40 With
the recognition of the importance of social controls,41 legal scholars have increased their
35
For an empirical demonstration of this point see McAdams & Nadler id.
To be sure, this argument should be qualified, as no enforcement or harsh enforcement may in fact carry
an expressive message. See Frank Zimring & Gordon Hawkins, The Legal Threat as an Instrument of
Social Change, 27 J. SOC. ISSUES 33, 89 (1971) (discussing the interrelations between formal deterrence).
For a discussion of the effect of deterrence on the development of moral commitment see H.L.A HART,
LAW, LIBERTY AND MORALITY 58 (1963).
37
For a review of these theories see Yuval Feldman, The Expressive Function of the Trade Secret Law:
Legality, Cost, Intrinsic Motivation and Consensus, __ J. EMPIRICAL LEGAL STUD. __ (forthcoming 2008).
38
See, e.g., Peter May, Compliance Motivations: Affirmative and Negative Bases, 38 Law & Soc'y Rev. 41
(2003).
39
Mark Silberman, Toward A Theory of Criminal Deterrence, 41 AM. SOC. REV. 442 (1976); FRANK
ZIMRING & GORDON HAWKINGS, DETERRENCE: THE LEGAL THREAT IN CRIME CONTROL (1973).
40
Charles. R. Tittle & Alan. R. Rowe, Moral Appeal, Sanction Threat, and Deviance: An Experimental
Test, 20 SOC. PROBS. 488 (1973); Tom. R. Tyler & John. M. Darley, Building a Law/Abiding Society:
Taking Public Views about Morality and the Legitimacy of Legal Authorities into Account when
Formulating Substantive Law, 28 HOFSTRA L. REV. 707, (2000); John. M. Darley, K. M. Carlsmith &
Paul. Robinson, The Ex Ante Function of the Criminal Law, LAW & SOC’Y REV.35, 165 (2001).
41
Robert. F. Meier, & Weldon. T. Johnson, Deterrence as Social Control: The Legal and Extralegal
Production of Conformity, 42 AM. SOC. REV. 292 304 (1977).
36
research span to include shaming sanctions.42 Within, this literature, a similar distinction
between external and internal motivation exists with respect to shame and guilt as a
motivating factor of behavior.43 Shame relates to external sanctioning inflicted by fellow
members of the community. Guilt, on the other hand, relates to an internal process
through which the individual feels negative emotions as a result of disobeying the law.44.
Since guilt feelings are built upon an internalization process, they are expected to be less
sensitive to the probability of detection than feelings of shame. In other words, when
people internalize the legal norm they suffer disutility from disobeying it, not
withstanding whether or not they were caught. Thus, when motivation to comply stems
from feelings of guilt we expect to find greater willingness to disobey the law when the
uncertainty is created by the law rather than enforcement problems.45 However, when
motivation to comply stems from feelings of shame, the source of legal uncertainty is less
critical as the likelihood of getting caught defines the expected cost for the individual.
An additional body of psychological and economic literature that we find relevant
to our study is that dealing motivated reasoning.46 According to this literature, decision
makers attempt to make choices that they perceive as such that can be later justified to a
dispassionate observer.47 In other words, people want to avoid a dissonance between how
they behave and how they think they ought to behave. Thus, they develop an array of
internal reasoning tools that allow them justify their acts, and avoid categorizing them as
immoral or dishonest.48 As Mazar, Amir and Ariely note in an example that comes close
to our study: “people who pass by a gas station will not only be influenced by the
expected amount of cash they stand to gain from robbing the place, the probability of
being caught, and the magnitude of punishment if caught, but it would also matter how
the act of robbing the store might make them perceive themselves.”49
42
For some representative examples of this literature see, e.g., Toni M. Massaro, Shame, Culture, and
American Criminal Law, 89 MICH. L. REV. 1880 (1991); Dan M. Kahan & Eric A. Posner, Shaming White/
Collar Criminals: A Proposal for Reform of the Federal Sentencing Guidelines, 42 J. LAW & ECON. 365
(1999).; James Q. Whitman, What Is Wrong with Inflicting Shame Sanctions?, 107 YALE L. J. 1055 (1998);
Doron Teichman, Sex, Shame, and the Law: An Economic Perspective on Megan’s Laws, 42 HARV. J. LEG.
355 (2005); and Alon Harel & Alon Klement, The Economics of Stigma: Why More Detection of Crime
May Result in Less Stigmatization, 36 J. LEGAL STUD. 355 (2007).
43
For an analytical discussion of the distinction among these different feelings see, e.g., June Price
Tangney et. al, Are Shame, Guilt and Embarrassment Distinct Emotions?, 70 J. PERSONALITY & SOC.
PSYCH. 1256 (1996). For an analysis of the role of shame and guilt in the specific context of tax compliance
see B. Erard & J.S. Feinstein , The Role of Moral Sentiments and Audit Perceptions in tax Compliance, 49
PUB. FINANCE 70 (1994).
44
For one of the leading law and economic perspective on internalized values see Robert Cooter, Do Good
Laws Make Good Citizens? An Economic Analysis of Internalized Norms, 86 VA. L. Rev. 1577 (2000).
45
In the third study that we conduct in this paper, we compare the interaction between legal uncertainty and
whether the motivation to comply is internal or external. See infra part III E.
46
For a review of this literature see Ziva Kunda, The Case for Motivated Reasoning, 108 PSYCH. BULL. 480
(1990).
47
Id. at 493.
48
See Nina Mazar & Dan Ariely, Dishonesty in Everyday Life and its Policy Implications, J. PUB. POL’Y &
MARKETING 1, 10 11 (analyzing “self deception”).
49
Nina Mazar, On Amir & Dan Ariely, The Dishonesty of Honest People: A Theory of Self/Concept
Maintenance (unpublished manuscript on file with authors).
Psychologists have not explored the connection between legal uncertainty and
motivated reasoning. Nonetheless, they have studied different aspects associated with
uncertainty and this behavioral phenomenon. Schweitzer and Hsee demonstrated that in a
negotiations setting in which the costs and benefits of the parties were held constant, the
parties decision to disclose private information to the opposing side was influenced by
what they term as the “elasticity” of the private information.50 For example, in one study
they examined the willingness of parties to disclose harmful private information when
negotiating the sale of a car. In this study sellers were informed that the odometer of the
car being sold had been disconnected, and that the buying party would believe them if
they told him that the actual mileage was 60,000.51 Sellers were then divided into two
groups: the first was told that the actual mileage was between 74,000 and 76,000, and the
second was told that the mileage was between 60,000 and 90,000 (with equal
probabilities within the range for each group).52 Note that according to traditional rational
choice models sellers are expected (a) to tell the other party that the mileage is only
60,000; and (b) not to differ between the two control groups. Yet Schweitzer and Hsee
report that the parties tended to disclose higher values than 60,000, and, more importantly
for our purposes, that the average mileage claimed by the first group was significantly
higher than the average claimed by the second group.53 These results demonstrate the
importance of motivated reasoning and self serving justifications in a probabilistic
setting. Members of the first group could not represent to the opposing party a mileage
figure bellow 74,000 without knowing for certain that they are deceiving him. Members
of the second group, on the other hand, could claim that the mileage was only 60,000
while convincing themselves that stating this figure was not a misrepresentation. In a
legal context, Feldman and Harel showed that when faced with uncertain legal standards,
participants’ tendency to choose an interpretation that fit their self interest grew as the
expected benefits from non compliance rose.54 The authors viewed this result as an
indication for interpretation driven by motivated reasoning, where participants used
uncertainty to a greater extent when temptation to shirk was stronger.
The existence of a self serving bias towards interpreting behavior as moral could
cause a distinction between enforcement uncertainty and legal uncertainty. Enforcement
draws on external motivations, and therefore is not susceptible to a self serving bias. The
law, on the other hand, is tied to the internal desire of people to perceive their behavior as
worthy. The existence of uncertainty with respect to the content of the law can allow
people to discount their internal fear of behaving in an inappropriate fashion, since
behaving in such a way can be internally justified as an honest mistake with respect to the
nature of the act, and not seen as part of an inappropriate cost benefit analysis. Thus, we
are again drawn to assume that people will tend to demonstrate a higher propensity to
50
M. E. Schweitzer & C. K. Hsee, Stretching the Truth: Elastic Justification and Motivated
Communication of Uncertain Information, 25 J. RISK & UNCERTAINTY 185 (2002).
51
Id. at 189 92.
52
Id.
53
Id. at 190. More specifically, the average of the first group was 70,764 and the average of the second
group was only 68,354.
54
Feldman & Harel, supra note 12.
participate in the regulated activity when uncertainty originates from the content of the
law itself.
A. Participants and Design
To test our propositions, we conducted an experimental survey study, using
situational vignettes in a between subject design on a student population in both the
United States and Israel. A total of 422 students at Bar Ilan University,55 the Hebrew
University of Jerusalem56 and Tulane University57 were sampled.
The questionnaires depicted a legal dilemma that participants were asked to
evaluate. More specifically, respondents were instructed to imagine that they were
factory managers who need to decide whether to produce a chemical that might pollute a
nearby lake. The experimental manipulation was conducted by randomly dividing the
sample to equal sub groups and making controlled changes to the descriptions of the
dilemma. After reading the description of the dilemma, participants were asked about
their individual evaluation of the dilemma, perceived norm and intention to behave. In
addition, we measured participants’ perceived social norms regarding the polluting
behavior and their willingness to pay for abstaining from polluting.
B. Factors
1. The Manipulated Factors
The first study had two experimental groups, while the second and third studies
employed a 2X2 design. The first manipulated factor – source of uncertainty had two
levels (uncertainty in law vs. uncertainty in enforcement), and was used in all three
studies. Enforcement uncertainty was described to participants as a situation where it is
clear that the law prohibits pouring the chemical into the lake, however there is a low
chance (10%) that the authorities will be able to detect the identity of the polluting
factory. Thus, participants were told that the overall likelihood of prosecution is 10%.
Legal uncertainty was described to participants as a situation where it is clear that if the
chemical will be poured into the lake, it will be detected by the authorities. However, it is
not clear that the pouring of the chemical is illegal since the chemical is relatively new
and its legal status has not been determined yet. In this situation, too, the participants
were told that the overall likelihood of prosecution is 10%.
In the second study, an additional manipulated factor the type of the sanction
was used. This factor had two levels, criminal sanction and civil sanction. In the criminal
sanction group, participants read about a situation where the enforcement was done by
the state and was criminal. In the civil sanction group, the scenario described a situation,
55
Study II was conducted in Bar Ilan University and included 159 students.
Study III was conducted in the Hebrew University of Jerusalem and included 194 students
57
Study I was conducted in Tulane University and included 69 students.
56
where the enforcement was done by a private party and the payment was paid as damages
rather than as a fine.
In the third and final study, the second manipulated factor was replaced with a
different two level factor the existence of a rational for the law. In one level, the law
that prohibited pollution was given an explanation – the potential death to fishes in the
lake. In the second group, participant were told that there was no extra legal rational for
the law, as in this specific lake, there were no fish from the kind sensitive to the chemical.
2.
Dependent Variables
The dependent variables in the study were self reported and were measured on a
Likert scale of (1 10).58 The first two items were related to social and moral desirability of
incompliance. Perceived morality was examined by asking participants whether
producing the fertilizer in the described legal situation is morally unacceptable (1
acceptable, 10 unacceptable). Perceived social desirability was examined by asking
participants and whether producing the fertilizer in the described legal situation is
socially desirable (1 desirable, 10 undesirable).
The next two items were related to the perceived prevalence of compliance.
Industry wide incompliance was measured by asking participants what percentage of
factories in the country would choose to produce the fertilizer in the described setting (1,
10%, 10 – 100%). Managerial incompliance was measured by asking participants
whether they agree with a statement that “most managers would decide to produce the
fertilizer in the given legal situation?” (1, agree, 10 disagree).
The last three items were related to participants’ hypothetical future behavior.
Likelihood of compliance was measured by asking participants whether they agree with
the statement that “If possible I will try not to produce the fertilizer in the given legal
situation.” Willingness to pay for compliance was measured by asking participants
whether they would agree with the statement “Even if I receive a high amount of money,
I will not produce the fertilizer in the given legal situation” (1 disgree, 10 agree). Finally,
participants were asked a yes/ no question to measure their intention to violate the law –
“At the end of the day, would you produce the fertilizer?”
C. Study I: Legal Uncertainty vs. Uncertain Enforcement
We begin with a simple benchmark case in which we compare uncertainty created
by probabilistic enforcement and uncertainty created by legal ambiguity. To examine the
effect of the type of legal situation on participants’ attitudes toward the misconduct, a
one way multivariate analyses of variance (MANOVA) was conducted, and the sub
groups were compared with respect to the dependent variables of the study (attitudes
toward the misconduct, perceived prevalence of the misconduct and personal inclination
58
Dependent variable refers to the variables that are explained by the model.
to perform the misconduct).59 Following a significant effect,60 a series of univariate one
way ANOVAs were conducted in order to examine the source of the variance.61 A chi
square test (χ2) was then performed to examine the independence between the yes/no
question about the engagement in the misconduct and the legal situation.62 In Table 1 we
report the mean scores and standard deviations for perceived attitudes and reactions
toward the misconduct as a function of the legal situation.63
Table 1: Mean Scores and Standard Deviations (in parentheses) for Perceived Attitudes and Reactions
towards the Misconduct as a Function of the Legal Situation64
Legal uncertainty
(n=28)
Dependent Variable
!"
Perceived Morality
Perceived Social Desirability
!#$! %! #!%&'!($!
Industry wide Incompliance
Managerial Incompliance
!#")(&' !*&% )#
Likelihood of Compliance
Willingness to Pay
Intention to Violate the Law
59
Legal Situation
Enforcement uncertainty
(n=41)
5.96 (2.97)
6.46 (2.55)
7.90 (2.54)
6.56 (2.67)
4.11 (2.45)
3.39 (1.57)
4.63 (2.45)
4.88 (2.37)
6.93 (2.85)
5.89 (3.09)
1.57 (.50)
8.12 (2.27)
6.98 (2.76)
1.83 (.38)
MANOVA is a procedure that examines the explained variance in a series of dependent variables, by a
series of independent variables. The advantage of this procedure is that it enables to identify both an
interaction between the independent variables as well as other associations between the dependent
variables.
60
Significance in statistics refers to the odds that a certain result was created by chance. In the context of
this paper, every time a difference or a result is presented as Significant, it means that there is less than 5%
likelihood that this difference was coincidental. The 5% level of significance is a common threshold used
in statistical analysis. In some cases where the result was stronger we added p < .01 to imply that the
likelihood of a chance driven result was lower than 1%.
61
ANOVA is a very common statistical technique, which aims to identify the sources of variance among
participants. In contrast to MANOVA, in ANOVA, there is only one dependent variable. In our design, the
purpose of the statistical analysis is to examine whether the experimental groups are different from each
other. The procedure allows us to tell how much of the difference between participants could be attributed
to the assignment to the different sub groups. In plain words, the statistical analyses will tell us how much
of the differences in the responses of participants could be explained by the framing of the legal
probability.
62
A chi Square procedure is used to examine whether a certain distribution of events is random or could be
explained by a certain model. It is used in this study to test the dependence between the distribution of the
dichotomous dependent variable of 'intention to violate' (Yes/No) and the source of uncertainty in all three
studies.
63
Standard Deviation (SD) is a common concept used to measure the distribution of a variable around the
average.
64
All first six items were rated on a 10 point Likert type scale. The Intention to violate the law was rated
by two categories: 1 (yes), 2 (no). In the order of variables in the table, higher mean values indicate more
negative attitudes toward the misconduct, lower perceived prevalence of the misconduct and lower
inclination to perform the misconduct.
Multivariate analysis of variance for the attitudes and reactions toward the
misconduct indicated that overall, the subgroups significantly differed.65 A univariate
analyses of variance indicated that a significant difference was detected for four of the
seven variables: Perceived Morality,66 Managerial Incompliance,67 Likelihood of
Compliance,68 and the Intention to Violate the Law.69 These tests reveal that for all of
these measures, means were higher in the uncertainty in enforcement subgroup than in
the uncertainty in law subgroup. Therefore, in accordance with the hypothesis, the
inclination to violate the law was found to be higher for the group faced with uncertainty
in law than in the group faced with uncertainty in enforcement. The subgroups did not
differ significantly on the other variables presented in the table (all p's>.05).
Finally, in Table 2 we report the frequency distribution of the participants as a
function of the engagement in the misconduct and the legal situation.
Table 2: The Distribution of Participants as a Function of the Engagement in the Misconduct and the Legal
Situation
Intention to violate the
law
YES
NO
Legal Situation
Uncertainty in Law
Uncertainty in
Enforcement
12
7
16
34
The chi square (χ2) test indicated a significant dependence between the variables χ2 (1,
N=69) = 4.33, p<.05. In accordance with the hypothesis, in the legal uncertainty sub
group, the proportion of participants showing an inclination to violate the law (42.9%)
was significantly higher than in the uncertain enforcement sub group (17.1%).
D. Study II: Legal Probabilities in Civil and Criminal Settings
In our first experiment we confirmed our basic hypothesis that legal probabilities
are not fungible, and demonstrated the difference between uncertainty associated with
enforcement and uncertainty associated with the content of law. This led us to examine
the boundaries of this effect and the extent to which it would be repeated in other legal
settings. Identifying the areas where people prefer legal uncertainty over uncertain
enforcement could help us both understand the theoretical mechanisms that underlie it,
and give policymakers tools to use this gap more effectively.
A basic distinction between legal regimes is the distinction between civil and
criminal regulation. While civil regulation generally involves litigation between a private
party harmed by the acts of another private party, criminal regimes are based on the act of
the state that brings a legal action against one of its subject. A large body of theoretical
65
Multivariate F(7,61)=3.18, p<.01, η2=.27
F(1,67)=8.43, p<.01, η2=.11
67
F(1,67)=8.45, p<.01, η2=.11
68
F(1,67)=3.72, p<.05, η2=.05
69
F(1,67)=5.85, p<.01, η2=.08
66
literature has dealt with the unique social meaning of criminal sanctions, and their distinct
power to internalize norms and regulate behavior. In a series of influential articles
Robinson and Darley explored these issues, and argued that criminal law reflects a set of
internalized norms.70 In addition, past empirical studies examined the different incentives
created by tagging a legal payment as either civil or criminal.71 These studies showed that
individuals are less willing to engage in simple cost benefit analysis once a legal sanction
is labeled as criminal.72 Given these characteristics of criminal sanctions, one can expect
that the content of the law plays a larger role in that context. Thus, we hypothesized that
the effect of legal uncertainty will be greater in a criminal setting, when compared with a
similar civil setting.
To examine the effects of the type of the sanction and the type of legal uncertainty
on the dependant variables, a two way multivariate analyses of covariance
(MANCOVA), sanction’s type (Criminal/ Civil) X legal probability (Uncertainty in
Enforcement / Uncertainty in Law) was conducted. Separate one way ANCOVA's for
each of the sanction's types comparing the means of the legal situation subgroups were
also conducted.73 Because of continuity considerations, a chi square test (χ2) was then
performed to examine the independence between the Intention to Violate the Law
(Yes/No) and whether the sanction was civil or criminal.
The two way MANCOVA for the general measures of the study indicated that
overall, the Uncertainty in Law subgroup significantly differed from the Uncertainty in
Enforcement subgroup.74 It also indicated that the sanction's type effect was not
statistically significant (p's >.05). Finally the MANCOVA showed a significant
interaction effect between the sanction’s type and the legal situation.75 The univariate
tests indicated that a significant difference between the legal situation subgroups was
detected for four of the seven variables: Perceived Morality,76 Perceived Social
Desirability,77 Willingness to Pay for Compliance,78 and the Intention to Violate the Law
(Yes/No).79 These tests reveal that for all of these variables, means were higher in the
uncertainty in enforcement subgroup than in the uncertainty in law subgroup. Therefore,
as expected, the inclination to violate the law was found to be higher for the group faced
70
Paul H. Robinson & John Darley, The Utility of Desert, 91 NW. U. L. REV. 453 (1997); Paul H.
Robinson & John Darley, Objectivist vs. Subjectivist Views of Criminality: A Study in the Role of Role of
Science in Criminal Law Theory, 18 OXFORD J. LEGAL STUD. 409 (1998); and Robinson & Darley, supra
note 2.
71
See, e.g., Feldman & Teichman, supra note 10.
72
Id.
73
Gender and the level of religiosity, were included as covariates in the analyses, and they were employed
to reduce their value as competing explanations for the participants' outcomes. MANCOVA and ANCOVA
are similar procedures to MANOVA and ANOVA respectably. The major difference is that in MANCOVA
and ANCOVA the influence of a supplementary independent variable covariate – can be controlled and
accounted for. In this context the demographic factors were treated as covariates to control for their
influence.
74
Multivariate F(3,143)=4.81, p<.01, η2=.09
75
Multivariate F(3,143)=3.08, p<.05, η2=.06
76
F(1,144)=9.78, p<.01, η2=.06
77
F(1,144)=15.39, p<.001, η2=.10
78
F(1,144)=8.55, p<.01, η2=.06
79
F(1,144)=4.53, p<.05, η2=.03
with uncertainty in law than in the group faced with uncertainty in enforcement. No
significant differences were detected between the Civil Sanction and the Criminal
Sanction subgroups for all of the variables tested in the study (all p's >.05).
Most importantly, the univariate tests also indicated a significant interaction effect
for three of the seven variables:80 Likelihood of Compliance81, Willingness to Pay for
Compliance82 and the Intention to Violate the Law.83 A marginal significant interaction
effect was detected for Perceived Social Desirability.84
To understand the source of the variance a separate ANCOVA’s for each of the
sanction's subgroup was conducted. The analysis indicated that for the Criminal sanction
condition, significant differences were detected between the Legal situation subgroups
for five of the seven variables: Perceived Morality, Perceived Social Desirability,
Likelihood of Compliance, Willingness to Pay for Compliance, and the Intention to
Violate the Law (Yes/No). In the Civil sanction condition, a significant difference was
detected between the Legal situation subgroups only for one of the seven variables:
Perceived Morality.
In Table 3 we report the mean scores for perceived attitudes and reactions toward
the misconduct as a function of the sanction's type and the legal situation. In addition the
table presents the results of the sub group analysis conducted separately for the criminal
and civil conditions.
Table 3: Mean Scores and Standard Deviations (in parentheses) for Perceived Attitudes and Reactions
toward the Misconduct as a Function of the Sanction's Type and the Legal Situation85
Dependent Variable
!"
Perceived Morality
!/&'
& )(
Uncertainty in Law
Uncertainty in
Enforcement
Difference test
Perceived Social
Desirability
Uncertainty in Law
Uncertainty in
Enforcement
80
&($ )(+" ,-!
% ' (N=77)
# . (&' (N=73)
7.68 (2.11)
7.54 (2.27)
8.57 (1.87)
8.71 (1.98)
F(1,73)=4.25, p<.05,
η2=.05
7.27 (2.22)
F(1,69)=5.24, p<.05,
η2=.07
6.90 (2.45)
7.97 (2.29)
8.91 (1.62)
The meaning of an interaction between the type of sanction and the source of uncertainty is that the
differences that were found between the averages in the variables of Likelihood of Compliance,
Willingness to Pay for Compliance and the Intention to Violate the Law, in the two uncertainty conditions
were moderated by the type of uncertainty.
81
F(1,144)=5.58, p<.05, η2=.04
82
F(1,144)=7.33, p<.05, η2=.05
83
F(1,144)=6.15, p<.05, η2=.04
84
F(1,144)=3.02, p=.08, η2=.02
85
All first six items were rated on a 10 point Likert type scale. The Intention to violate the law (Yes/No))
was rated by two categories: 1 (yes), 2 (no). In the order of variables in the table, higher mean values
indicate more negative attitudes toward the incompliance, lower perceived prevalence of incompliance and
lower inclination to violate the law.
#!%&'!($!
Industry wide
Incompliance
Managerial
Incompliance
Difference test
F(1,73)=2.38, p>.05,
η2=.03
F(1,69)=16.30, p<.001,
η2=.19
Uncertainty in Law
3.27 (1.59)
3.41 (1.92)
Uncertainty in
Enforcement
Difference test
3.05 (1.53)
3.53 (1.54)
F(1,73)=.34, p>.05,
η2=.00
3.86 (2.71)
F(1,69)=.10, p>.05,
η2=.00
3.59 (2.31)
4.57 (2.98)
3.88 (2.64)
F(1,73)=1.25, p>.05,
η2=.02
F(1,69)=.25, p>.05,
η2=.00
Uncertainty in Law
7.51 (2.56)
7.04 (2.36)
Uncertainty in
Enforcement
Difference test
7.10 (2.63)
8.50 (1.76)
F(1,73)=.36, p>.05,
η2=.00
6.57 (2.92)
F(1,69)=8.62, p<.01,
η2=.11
5.40 (2.77)
6.60 (2.96)
7.94 (2.25)
F(1,73)=.03, p>.05,
η2=.00
1.73 (.45)
F(1,69)=17.69, p<.001,
η2=.20
1.61 (.49)
1.70 (.46)
1.94 (.24)
F(1,73)=.04, p>.05,
η2=.00
F(1,69)=11.93, p<.001,
η2=.15
Uncertainty in Law
Uncertainty in
Enforcement
Difference test
!#")(&' #!&$ )("
Likelihood of
Compliance
Willingness to Pay
Uncertainty in Law
Uncertainty in
Enforcement
Difference test
Intention to Violate the
Law
Uncertainty in Law
Uncertainty in
Enforcement
Difference test
Table 4 reports the frequency distribution of the participants as a function of the
engagement in the misconduct and the legal situation for civil sanction vs. criminal
sanction.
Table 4: The Distribution of Participants as a Function of the Engagement in the Misconduct and the Legal
Situation for Civil Sanction vs. Criminal Sanction
Sanction's Type
Civil Sanction
Criminal Sanction
Intention to violate the
law
YES
NO
YES
NO
Uncertainty in
Law
13
27
15
27
Legal Situation
Uncertainty
Enforcement
12
30
3
32
in
The chi square (χ2) test indicated that for the Civil Sanction, there was no dependency
between the variables χ2 (1, N=82) = .02, p>.05. On the other hand, for the Criminal
Sanction, a significant dependency between the variables emerged χ2 (1, N=77) = 6.41,
p<.01. In accordance with the hypothesis, only for the Criminal Sanction, a significant
difference was found between the legal situation sub groups in their intention to violate
the law. In the Uncertainty in Law sub group, the proportion of participants showing an
inclination to violate the law (35.7%) was significantly higher than in the Uncertainty in
Enforcement sub group (8.6%).
E. Study III: Legal Probabilities and the Causation of Harm
In our third and final study we turned to explore how altering the factual aspects
of the situation can affect the way in which people perceive legal probabilities. More
specifically, we explored whether the causation of harm to others affects the way in
which people perceive legal probabilities. Exploring this question is a more complex and
challenging task, since one can present two competing hypothesis as to the role of legal
uncertainty in this regard.
One hypothesis stems from the process of motivated reasoning. As we have seen,
one of the psychological forces driving the differences between enforcement uncertainty
and legal uncertainty is the ability of people to employ self serving motivated reasoning
that justifies their choices of action. Yet, this way of reasoning is limited by the factual
setting in which it is conducted. For example, while one might be able to justify to
himself stealing a pencil worth 10¢ form a friend (e.g., everyone does it, etc.), he will
find it difficult to justify stealing 10¢ from the friend’s wallet.86 Similarly, the effect of
the legal prohibition may depend on the degree to which the law itself affects people’s
judgment of the morality of the act. If people have a clear judgment of the wrongfulness
of the act notwithstanding the law, then the effect of legal uncertainty is expected to be
diminished. For example, even if (hypothetically) there is some legal uncertainty whether
intentionally killing another man is covered by the criminal code, one would expect this
uncertainty to have little effect on people’s behavior since they view the act as wrongful
irrespective of the law’s content. If, on the other hand, people do not view the regulated
act as inherently wrong, then they will find it easier to engage in motivated reasoning
once legal uncertainty is introduced. For instance, legal uncertainty with respect to a
technical aspect of the tax code might draw people to utilize it in order to minimize their
tax liability, if they see nothing inherently illegitimate with minimizing their tax
payments.
The competing hypothesis, which stems from the vast literature on instrumental
motivations for legal compliance, suggests that the role of legal uncertainty may be less
significant in situations that carry limited moral meaning.87 As the compliance literature
points out, people do not obey the law merely because of the fear of sanctions. Rather, it
is the view of law as a moral authority that causes people to willfully obey it. Thus, if the
law deals with a morally charged situation (e.g., stealing money from a friend), then the
existence of uncertainty with respect to its content is expected to affect the decisions of
individuals significantly, since people may infer moral vagueness from the abstinence of
86
87
See Mazar, Amir & Ariely, supra note 49.
See supra notes 39 41 for some of the classical studies on instrumental motivation to comply.
legal uncertainty. If, on the other hand, the law deals with technical prohibitions that do
not seem to hold specific moral value, then the role of legal uncertainty is expected to be
diminished, since people do not view the content of law in such situations as a guide to
their behavior.
The same analysis conducted for study II was conducted in study III. A two way
MANCOVA for the general measures of the study indicated that overall, the Uncertainty
in Law subgroup significantly differed from the Uncertainty in Enforcement subgroup.88
It also indicated that the No Environmental Damage subgroup significantly differed from
the Environmental Damage subgroup,89 however there was no significant interaction
effect between the variables (p>.05). The univariate tests indicated that a significant
difference between the legal situation subgroups was detected for two of the variables:
Perceived Social Desirability90 and Managerial Incompliance.91 A marginal significant
effect was detected for the Industry wide Incompliance.92 These tests reveal that for these
three variables, means were higher in the Uncertainty in Enforcement subgroup than in
the Uncertainty in Law subgroup. As expected, incompliance was found to be higher for
the group faced with legal uncertainty than in the group faced with enforcement
uncertainty.
The univariate tests also indicated that a significant difference between the
environmental context subgroups was detected for five of the variables: Perceived
Morality93, Perceived Social Desirability94, Likelihood of Compliance 95, Willingness to
Pay96 and the Intention to Violate the Law.97 These tests reveal that for all of these
variables, means were higher in the Environmental Damage subgroup than in the No
Environmental Damage subgroup.
Following the same approach used in study II, and given that our prediction was
that the source of uncertainty will have the same effect in both conditions, we conducted
a separate ANCOVA for each of the environmental contexts. The split file analysis
indicated that for the Environmental Damage context significant differences were
detected between the Legal Situation subgroups for two of the variables: Perceived Social
Desirability and Managerial Incompliance. A marginal significant effect for the Legal
situation was found for the Industry Wide Incompliance rate. In the no damage condition,
no significant differences were detected between the Legal Situation subgroups for all of
the variables tested in the study (all p's >.05)
88
Multivariate F(3,181)=4.28, p<.01, η2=.07
Multivariate F(3,181)=10.79, p<.001, η2=.15
90
F(1,177)=8.4, p<.01, η2=.04
91
F(1,177)=9.85, p<.001, η2=.05
92
F(1,177)=3.43, p=.066, η2=.02
93
F(1,177)=30.00, p<.001, η2=.14
94
F(1,177)=18.70, p<.001, η2=.10
95
F(1,177)=20.06, p<.001, η2=.10
96
F(1,177)=11.06, p<.001, η2=.06
97
F(1,177)=13.13, p<.001, η2=.07
89
In Table 5 we report the mean scores for perceived attitudes and reactions toward
the misconduct as a function of the environmental context and the legal situation. In
addition, the table presents the results of the sub group analysis conducted separately for
the environmental context conditions.
Table 5: Mean Scores and Standard Deviations (in parentheses) for Perceived Attitudes and Reactions
toward the Misconduct as a Function of the Environmental context and the Legal Situation98
Dependent Variable
!"
Perceived Morality
!/&'
& )(
Uncertainty in Law
Uncertainty in
Enforcement
Difference test
Perceived Social
Desirability
6.61 (2.81)
8.55 (1.63)
F (1,86)=.03, p>.05,
η2=.00
5.98 (2.38)
F (1,89)=.28, p>.05,
η2=.00
7.62 (1.80)
7.04 (2.72)
8.48 (1.44)
F (1,86)=3.16, p>.05,
η2=.03
F (1,89)=5.84, p<.05,
η2=.06
Uncertainty in Law
3.11 (1.95)
3.40 (1.83)
Uncertainty in
Enforcement
Difference test
3.41 (2.17)
4.06 (1.85)
F (1,86)=.61, p>.05,
η2=.03
3.43 (2.66)
F (1,89)=3.55, p=.06,
η2=.04
3.27 (2.40)
4.43 (3.19)
4.56 (2.68)
F (1,86)=2.87, p>.05,
η2=.03
F (1,89)=7.58, p<.01,
η2=.08
Uncertainty in Law
5.96 (2.58)
7.93 (2.26)
Uncertainty in
Enforcement
Difference test
6.68 (2.85)
8.12 (2.05)
F (1,86)=.72, p>.05,
η2=.01
4.87 (2.57)
F (1,89)=.08, p>.05,
η2=.00
6.64 (2.96)
5.29 (3.12)
6.77 (2.71)
F (1,86)=.12, p>.05,
η2=.00
1.50 (.50)
F (1,89)=.00, p>.05,
η2=.00
1.73 (.48)
Uncertainty in Law
Uncertainty in
Enforcement
Difference test
#!%&'!($!
Industry wide
Incompliance
Managerial
Incompliance
Uncertainty in Law
Uncertainty in
Enforcement
Difference test
!#")(&' #!&$ )("
Likelihood of
Compliance
Willingness to Pay
Uncertainty in Law
Uncertainty in
Enforcement
Difference test
Intention to Violate the
98
(% #)(.!( &' $)( !0
) &.&/! (N=90)
&.&/! (N=93)
6.28 (2.60)
8.33 (1.76)
Uncertainty in Law
All first six items were rated on a 10 point Likert type scale. The Intention to violate the law (Yes/No)
was rated by two categories: 1 (yes), 2 (no). In the order of variables in the table, higher mean values
indicate more negative attitudes toward the misconduct, lower perceived prevalence of the misconduct and
lower inclination to perform the misconduct.
Law
Uncertainty in
Enforcement
Difference test
1.57 (.50)
1.85 (.36)
F (1,86)=.10, p>.05,
η2=.00
F (1,89)=1.89, p>.05,
η2=.02
The chi square (χ2) test indicated that for the No Environmental Damage context, there
was lack for dependency between the variables χ2 (1, N=95) = .27, p>.05. On the other
hand, for the Environmental Damage context, a significant dependence between the
variables emerged χ2 (1, N=99) = 2.68, p<.05. In accordance with the hypothesis, only for
the Environmental Damage context, a significant difference was found between the legal
situation sub groups in their intention to violate the law. In the Uncertainty in Law sub
group, the proportion of participants intending to violate the law (30.0%) was
significantly higher than in the Uncertainty in Enforcement sub group (14.3%).
A. General Discussion
Our goal in this Article was to explore the ways in which distinct legal
probabilities affect human behavior. In a series of three experiments we showed that the
source of legal uncertainty affects the way people perceive situations and the way they
are expected to behave. While our three experiments clearly cannot offer a full account of
the meaning of all types of legal probabilities in every conceivable situation, they do
allow for two general conclusions to be drawn from them. First, our main finding is that
people treat uncertain enforcement and uncertain law differently. Unlike uncertain
enforcement that simply reflects a reduction in the expected sanction; uncertain law
carries a deeper meaning in the eyes of people, and offers them a justification for
behaving in a way that fits their self interest. Thus, uncertainty with respect to law is
expected to raise incompliance to a larger degree than uncertain enforcement will.
Second, the behavioral effects of legal probabilities depend to a large degree on both the
legal and factual settings in which they are situated in. Issues such as the type of legal
regime and the nature of the activity being regulated may all generate different affects
with respect to probabilistic legal regimes.
There are several ways in which the behavioral patterns we documented can be
interpreted. One interpretation is that we have managed to present empirical evidence of
the expressive power of the law. Subjects in the different experiments did not view legal
sanctions as a mere price they must pay in order to engage in harmful activities. Rather,
the preference for legal uncertainty suggests that the act of legally prohibiting a certain
conduct holds independent expressive value that does not depend on the price tag that the
law attaches to the prohibition.
In this regard, studies two and three offer more subtle insights as to the expressive
power of the law. The second study suggested that the non instrumental function of law
is greater when the legal payment is defined as a criminal sanction rather than as civil
payment. This difference between the criminal and civil contexts, demonstrated an
additional refinement in the expressive function of criminal law, and the greater
importance of legal certainty in the criminal context. The findings of our third study shed
new light on the limits of the expressive power of the law. As was evident in that study,
not every legal prohibition carries with it the expressive power of the law. Rather, the
expressive value is created to a larger degree with respect to those situations in which the
law functions within morally charged situations. On the other hand, when a legal
prohibition is technical in nature, the ability of the law to generate an expressive value is
more limited.
A second interpretation of our findings is that the law lends itself to a process of
motivated reasoning by the people subject to it. In this regard, the emphasis is not on the
prohibitive nature of law, but rather on the legitimizing effect of behaving in accordance
with it. Ex ante legal uncertainty creates a path through which people can justify their
choices in their own eyes by focusing their attention on the possibility that their acts will
eventually be determined to be legal. Such effect might be exacerbated by the optimism
bias since individuals might systematically overestimate their ability to convince the legal
authorities that their interpretation of the law will be proved to be right.99 Uncertainty
with respect to enforcement, on the other hand, does not carry with it the potential for self
justification as people view it as a simple reduction to the price they must pay for
behaving in an undesirable way.
B. Policy Implications
Thus far we have focused on the theoretical and abstract implications of our
findings. We now turn to explore the implications of our results with respect to more
concrete policy issues. The first, and perhaps most obvious, is the discussion over the
tradeoff between uncertain law and uncertain enforcement as policy tools aimed at
enhancing compliance. While this question is general in nature, it has drawn the most
attention in the tax compliance literature.100 For example, in an influential article
Scotchmer and Slemrod designed a stylized model in order to derive the optimal level of
legal uncertainty in the tax system.101 Consistent with traditional economic models, they
implicitly assumed that the behavioral effects created by uncertain enforcement and
uncertain law are identical. This assumption coupled with the assumption of risk aversion
allowed them to argue that increasing legal uncertainty will increase reported income and
raise tax revenues.102 Furthermore, since reducing legal uncertainty creates many costs
99
See, e.g., Avishalom Tor, The Fable of Entry: Bounded Rationality, Market Discipline, and Legal Policy,
101 MICH. L. REV. 482 (2002) (reviewing the potential distractive effect of over confidence on peoples’
behavior).
100
The policy debate was formally framed in Suzanne Scotchmer & Joel Slemrod, Randomness in Tax
Enforcement, 38 J. PUB. ECON. 17 (1989). For later economic treatment of the issue see, e.g., James Alm,
Betty Jackson & Michael McKee, Institutional Uncertainty and Tax Payer Compliance, 82 AM. ECON.
REV. 1018 (1992); James Andreoni, Brian Erard & Jonathan Feinstein, Tax Compliance, 36 J. ECON.
LITERATURE 818, 852 53 (1998). For a recent reference to this debate within the legal literature see Logue,
supra note 24 at 250 51.
101
Scotchmer & Slemrod, id.
102
Id. at 19 24.
(e.g., specifying the code, training auditors, etc.), Scotchmer and Slemrod argued that the
optimal tax regime might be designed such that it will include relatively high legal
uncertainty coupled with low audit rates.103
Our findings, however, suggest that these claims need to be re examined and
refined. A large body of literature has dealt with the question why do people pay taxes.104
While the traditional deterrence model for compliance certainly holds ground in the tax
context, much of the observed tax compliance cannot be explained by deterrence given
the extraordinarily low audit rates.105 Rather, it is explained by the willingness of people
to contribute to the society in which they live once required by law to do so.106 Yet as we
have seen, legal uncertainty might erode some of these nonlegal incentives to pay taxes.
As a result the use of legal uncertainty as a revenue enhancing policy tool might turn out
to be counterproductive, and drive people to report lower incomes since they will be able
to justify this act to themselves. Thus, the importance of a clear tax code might be much
greater than currently perceived by economists.
More generally, our findings can function as a behavioral explanation for the
centrality of the principle of legality in criminal jurisprudence.107 The principle is perhaps
the most basic tenant of criminal law, and stands for the proposition that subjects of the
criminal justice system must be warned in a precise and clear way of all criminal
prohibitions.108 In the United States the principle may be applied through the vagueness
doctrine, which requires that a “crime definition be meaningfully precise or at least that
it not be meaninglessly indefinite.”109 There are several justifications for the principle of
legality. One group of justifications take an institutional approach to the issue, and argue
that criminal prohibitions should only be created by the branch of government that is
politically accountable to the people. A second group of justifications focuses on
potential criminals, and argues that is unfair to punish people who were not given fair
warning prior to committing the wrongful act.
While we do not aim to quarrel with any of these justifications, our findings
suggest an additional behavioral explanation for the doctrine, and for its focus on
criminal prohibitions. As we have seen, uncertainty creates an ideal setting for people
who value themselves to be law abiding people to justify in their own eyes not complying
with the law. Furthermore, our findings showed that legal uncertainty is especially
counter productive in the criminal setting, in which people look to the law for guidance.
103
Id. at 25 26.
For an experimental exploration of the different incentives to pay taxes see James Alm, Gary H.
McClelland & William D. Schulze, Why Do People Pay Taxes?, 48 J. PUB. ECON. 21 (1998).
105
Id. at 21 22.
106
Tax scholars have long since been aware to the rich motivations to pay taxes and have attempted to
design tax regimes that will utilize these motivations efficiently. For a recent example see Alex
Raskolnikov, Beyond Deterrence: Targeting Tax Enforcement with a Penalty Default (Working Paper
Presented at the 2008 meeting of the American Law and Economics Association, on file with authors).
107
See H. PACKER, THE LIMITS OF THE CRIMINAL SANCTION 79 80 (1968) (viewing the principle as ‘the
first principle’ of the criminal law).
108
See generally, John Calvin Jeffries, Jr., Legality, Vagueness, and the Construction of Penal Statutes, 71
VA. L. REV. 189, 210 (1985).
109
Id. at 196.
104
Thus, vague criminal prohibitions may undermine the self enforcing aspects of criminal
law and diminish compliance. Yet specifying criminal laws might be costly for
politicians, either because of the time and effort required in order to achieve specificity,
or because of the political costs associated with creating a prohibition. Hence, it is
especially important to motivate legislatures to create clear criminal prohibitions that
limit the amount of legal uncertainty by employing judicial review over the level of this
uncertainty, and striking down prohibitions that are not sufficiently specified. Moreover,
the focus of the doctrine on criminal prohibitions is expected to motivate legislatures to
focus their marginal effort to specifying criminal legislation rather than civil legislation,
which is desirable given the larger expressive power of the law in that area.
A second policy debate that our study is closely tied to is the one regarding the
desirable balance between rules and standards in the legal system. Legal norms can be
placed on a continuum of specificity. At one end of this continuum lie standards, which
include open ended terms such as “reasonable care” and “good faith.” The application of
these terms is conducted by an adjudicator who applies them to the specific fact pattern
of each case. Rules, on the other hand, are much more specific in nature. They include
detailed provisions that attempt to anticipate in advance different fact patterns, and leave
little room for discretion of the adjudicator.110
Rules and standards differ with respect to the level of uncertainty they generate
for potential wrongdoers. Standards are inherently vague, since they rely on ex post
adjudication that is difficult to predict ex ante. Rules, on the other hand, create more
certainty, since a potential wrongdoer can evaluate his acts in light of the detailed
provisions of the rule, and know with relative predictability whether his act fits the fact
pattern covered by it. For example, think of the decision an employer needs to make with
respect to installing a new safety measure at the workplace. If safety issues are governed
by a negligence standard, the employer can only estimate ex ante what is the probability
that not installing the measure will be deemed as negligence by a court. If, however, the
regime is based on rules specified in a safety code, the employer faces less uncertainty as
to his obligations under the law.
Legal economists view the choice between rules and standards as one that is
governed by cost benefit considerations.111 In this regard they take account of costs such
as the costs of legislating a rule ex ante, the costs of acquiring information on the law,
and the costs of enforcing the law ex post.112 Generally, the conclusion of this analysis is
that as the frequency of an activity increases, it becomes more desirable to adopt rules
since the relatively higher cost associated with creating them ex ante, is justified by their
110
For further discussion of the behavioral mechanisms that underlie how individuals interpret standards
see Feldman & Harel, supra note 12 at section 3.1.
111
The two main contributions in this regard are Isaac Ehrlich & Richard A. Posner, An Economic Analysis
of Legal Rulemaking, 3 J. LEGAL STUD. 257 (1974); and Louis Kaplow, Rules versus Standards: An
Economic Analysis, 42 DUKE L.J. 557 (1992).
112
Kaplow, id. at 568 70.
frequent use ex post.113 In rare cases, on the other hand, one can rely on ex post
adjudication and save the costs of extensive legislation.114
Our analysis sheds new light on this issue, and suggests an additional difference
between rules and standards that should be incorporated into the analysis. As we have
seen, the introduction of legal uncertainty may give rise to an internal process through
which individuals convince themselves that they are acting in accordance with the
uncertain standard. Thus, setting bright line rules may be more desirable than previously
perceived, as such rules can eliminate motivated reasoning on behalf of decision makers,
and draw them to conduct a more objective analysis of the situation.
As a related matter, our findings in this regard offer an additional explanation for
the puzzle: why do we observe systematic violations of legal standards.115 From an
economic perspective, the expected level of violations of standards that were designed
optimally is zero, since from the standpoint of potential wrongdoers it is irrational to
violate the legal standard. For example, a well functioning negligence regime is expected
to give people incentives to always take optimal care.116 Nonetheless, there is ample
evidence that people behave negligently quite often.117
Traditional explanations for the existence of violations of standards focus on two
main dimensions.118 The first are problems associated with the legal system. To the
extent that the legal system is not designed in an optimal fashion (e.g., the legal standard
is set at a wrong level, enforcement is uncertain, damages are too low, etc.) then one
would expect to observe rational parties choosing to deviate from the legal standard. The
second are deviations from the rational choice model. If people are subject to an array of
cognitive biases that affect their decisions, then these biases might cause them to violate
the legal standard even though that is not the best course of action from their
perspective.119
While all of these explanations remain valid, a complimenting explanation
suggested by our findings is that the uncertainty created by standards such as negligence
draws people to violate them. Rules cause people to face a clear dilemma between
obeying and disobeying the law. Standards, on the other hand, allow parties to view their
choices ex ante as such that will be determined by an adjudicator ex post to be non
negligent, and therefore legal. This “window of legality” draws people to behave in a way
that is not in accordance with the standard.
113
Id. at 577.
Id.
115
See, e.g., Mark F. Grady, Why Are People Negligent? Technology, Nondurable Precautions, and the
Medical Malpractice Explosion, 82 NW. U. L. REV. 293, 294 (1988) (noting the puzzle).
116
See e.g., A. M. POLINSKY, AN INTRODUCTION TO LAW AND ECONOMICS 70 71 (1983); WILLIAM LANDES
& RICHARD POSNER, THE ECONOMIC STRUCTURE OF TORT LAW 72 73 (1987).
117
Id.
118
See, e.g., Steven Croley, Vicarious Liability in Tort: On the Sources and Limits of Employee
Reasonableness, 69 S. CAL. L. R. 1705, 1726 30 (1996) (reviewing the issue).
119
Id. at 1724 n. 70.
114
A third body of literature that our study lends itself to is that dealing with legal
advice. Legal advice is information that individuals buy from lawyers as to content of the
law. In our framework this implies that once purchasing legal advice is possible,
individuals can choose to reduce legal uncertainty with respect to their potential liability
by investing resources in buying advice.120 For example, a lawyer might be able to
provide his clients with advice as to the meaning of the negligence standard in a certain
setting, the application of a statute to a contemplated behavior, or the tax liability
generated by a certain transaction.
Legal economists have long since modeled the incentives of individuals to acquire
legal advice, and the social value of this advice.121 Generally, these models are an
extension of economic models of the value of information to decision makers.122
According to this framework, individuals acquire legal advice only if its expected value
exceeds its costs. The expected value of legal advice is calculated by multiplying the
probability that the advice will lead the party to alter her behavior by the benefit gained
from the altered behavior.123 For example, if a factory owner can save $3,000 by pouring
a chemical into a lake, and the fine for this act is $5,000; then she will choose to pour the
chemical as long as she believes that the probability of illegality is bellow 60% since the
expected sanction (0.6*5,000=3,000) is smaller than the gain from the act. Now assume
that the subjective valuation of illegality of the factory owner is 40%. Under these
conditions it will be beneficial for her to invest up to $800 in legal advice that might
inform her about the illegality of pouring the chemical into the lake, since there is a 40%
chance that the advice will inform her that the act is in fact illegal and save her a net cost
of $2,000 ($5,000 fine minus of the $3,000 saved costs), and a 60% chance that the
advice will be worthless since it will inform her about the legality of the act and not alter
her behavior.124
While economic models of legal advice capture many of the incentives
individuals have in acquiring legal information, our findings suggest that they do not tell
the full story of this market. Economic models explicitly assume that the probability of
detection and the probability of illegality have identical affects on the incentives of
decision makers.125 Our analysis, on the other hand, suggests that there is something
different about legal advice. As we have seen, decision makers clinch to legal uncertainty
in a process of motivated reasoning. Thus, the incentive to acquire legal advice might be
lower than that predicted by current models, since decision makers know that a clear
120
To be sure, legal advice can relate to other aspects of people’s decisions to engage in regulated activities
such as the magnitude of liability. In this study we focused solely on uncertainty relating to liability and
therefore we limit the analysis to this point alone.
121
For an early contribution to this literature see Steven Shavell, Legal Advice About Contemplated Acts:
The Decision to Obtain Advice, its Social Desirability, and Protection of Confidentiality, 17 J. LEGAL
STUD. 123 (1988) (hereinafter: Shavell, Contemplated Acts). For a later review of the literature see Steven
Shavell, Legal Advice, in THE NEW PALGRAVE DICTIONARY OF ECONOMICS AND THE LAW 516 (Peter
Newman ed., Vol. 2, 1998).
122
See, e.g., HOWARD RAIFFA, DECISION ANALYSIS (1968).
123
Shavell, Contemplated Acts supra note 121 at 127.
124
Id. at 127 28.
125
Id. at 128 (uncertainty with respect to tax law and audit rates are assumed to be fungible).
answer from a legal expert as to the illegality of their act will prevent them from
rationalizing their acts in their own eyes. In other words, people might chose to remain
strategically uniformed with respect to the law. Moreover, our results suggest that even if
the expected legal sanction is identical, the value of legal advice might be different in a
criminal and a civil context since people are especially susceptible to utilize legal
uncertainty in the criminal context.
Note that our result also suggest that in some cases the incentive to seek legal
advice might be to enhance uncertainty rather than reduce it. According to this view,
legal advice can create uncertainty where no such uncertainty existed before hand. For
example, a lawyer might be able to employ a creative interpretation yet completely
unrealistic of the law according to which a certain transaction is not taxable. In such
situations, our findings imply that beyond the potential instrumental value of such
uncertainty associated with the possibility to launch a reliance defense,126 it also has a
non instrumental value by diminishing the expressive power of the law and allowing
individuals to feel as if they are complying with the norm.
Finally, the results of our third experiment can be used to guide policymakers in
which settings they should focus their efforts to specify and clarify the law. As we have
seen, the role of clarity is of relatively greater importance in settings that are morally
charged. Thus, while one might speculate that there is no need for legal specificity in
such situations since the moral intuitions of people will guide them notwithstanding the
content of the law, our findings suggest that it is precisely in these areas that introducing
uncertainty to the law might reduce compliance by either eroding the expressive power of
the law or allowing people to engage in motivated reasoning. On the other hand, in areas
that are less morally charged people view the law in a more instrumental way, and the
role of specifying the law is diminished since its expressive function is more limited. As a
result, in those areas there is less of a difference between the effects of uncertainty in law
and uncertainty in enforcement. Hence, in these areas policymakers might choose to
focus attention on designing efficient enforcement regimes.
C. Limitations and Future Research
In this final sub section, we evaluate the potential criticisms to this project. We
outline the limitations of our results, and sketch out additional research that could help
deal with these limitations.
First, one should recognize the general limitations of the methodology we used in
this study. Measured items are attitude scales. Given the extensive literature on the
complexity of the attitude behavior relationship,127 one ought to be careful not to over
state these findings, especially in the context of the expressive aspects of participants’
126
Relying in legal advice might create a legal defense depending on the circumstances of the situation. For
an updated review see Zathrina Perez, Eric Cochran and Christopher Sousa, Twenty/Third Survey of White
Collar Crime, 45 AM. CRIM. L. REV. 923, 969 70 (2008).
127
See, e.g., Yuval Feldman, Attitudes and Behavior, in ENCYCLOPEDIA OF LAW & SOCIETY: AMERICAN
AND GLOBAL PERSPECTIVES (2007).
behavior. After all, it is relatively easy to express different values when there is no price
tag attached to the expression. Thus, since participants in our study did not face real
monetary incentives, their answers might be biased towards overstating the expressive
power of the law. Future research should attempt overcome this problem by combing
monetary incentives, which might balance the fact that instrumental perspective of the
law is more prone to be affected by the method of attitude questionnaire. That said, it
should also be recognized that numerous studies have documented the validity of using
intention as a proxy for behavior.128 Thus, we expect that the current pattern of findings
should be replicated using other methodologies.
Second, the transformation of uncertainties in both law and enforcement into the
specific numbers that we used, limit our ability to argue for a general difference between
legal uncertainty and enforcement uncertainty. It might be the case that in different
probabilities these two uncertainties will behave differently. One explanation for this
hypothesis stems from the process of motivated reasoning. As we saw, motivated
reasoning is constrained by the situation in which it is conducted. One can speculate that
as the probability of illegality rises, the ability of people to justify to themselves behavior
that does no accord with the expected legal norm to diminish. If that is the case,
controlling for the size of the uncertainty is expected to interact with the willingness to
engage in harm generating behavior. Thus, future research should replicate the same
study, but with different levels of uncertainty.
Third, while in the second experiment, which examined the interaction between
the type of sanction and the source of uncertainty, a significant interaction emerged, this
was not the case with respect to the third experiment in which we examined the effect of
the factual setting. This might be explained by the fact there are two competing
theoretical mechanisms in this setting that drive towards opposing directions. Thus, while
the relatively weaker effect might have been expected, the weakness of the current
pattern should be recognized. Clearly, without an interaction, the differences that
emerged in the sub group analysis between the two conditions should not be overstated.
Here too, future research should replicate this study with minor modification of existence
of social motivation and likely guilt from violating the law.
Fourth, the sample that we used in this study consists exclusively of law students
whose reactions to legal uncertainty might not represent those of the general population.
For example, law students might be more risk seeking with respect to legal uncertainty
than the general population since they view it as a natural phenomenon they are familiar
with. From this perspective we expect to see a larger willingness to exploit legal
uncertainty among law students. On the other hand, the law might hold greater expressive
power in the eyes of law students, since they tend to care more about their own image as
law abiding people. From this perspective we expect to see a smaller willingness to act
not in accordance with an uncertain legal norm among law students. Thus, it will be both
interesting and useful to rerun our experiments on subjects without a legal education, and
128
E.g., Icek Ajzen, From Intentions to Actions: A Theory of Planned Behavior, in ACTION CONTROL:
FROM COGNITION TO BEHAVIOR 11, 14 18 (Julius Kuhl & Jürgen Beckman eds., 1985).
examine whether they perceive different sources of legal uncertainty differently from our
sample.
A separate set of questions that we leave for future research is the source of legal
uncertainty. In our study the sole source of uncertainty was the language of the law.
Nonetheless, as we noted there are additional sources of legal uncertainty, such as that
created by legal standards.129 Similarly, there might be a distinct social meaning to
different players in the legal system making probabilistic decisions. For example, the
effect of a 10% chance that a prosecutor will choose not to bring charges due to a large
case load might be different from the effect of a 10% that a jury will decide to acquit a
defendant.130
We began this paper with by describing the traditional economic theory regarding
probabilistic sanctioning regimes. According to this theory potential wrongdoers treat
different types of legal probabilities much like a gambler treats a series of bets at the
casino – they simply multiply them as if they were fungible in order to derive the
expected sanction. Using a series of experiments we demonstrated that legal probabilities
should not be treated as fungible. Rather, an array of factors relating to the source of
uncertainty and the setting in which it is located, cause people to treat different legal
probabilities distinctly. These distinctions, in turn, generate behavioral predictions that
differ from traditional deterrence models, and shed new light on an array of policy
debates.
The general picture rising from our results is a complex network of relationships
between law, social norms and internal motivations. These nuances and complexities are
currently not a part of deterrence models employed by legal economists. Nonetheless, it
should be noted that our goal in this study, and others related to it, is not simply to
criticize or undermine these models. Rather, it is to create a richer and ultimately more
accurate model of law and human behavior. Incorporating our empirical findings into
existing models could eventually assist policymakers utilize the different legal tools at
their disposal in an optimal fashion.
129
See Feldman & Harel, supra note 12.
Note that while the question we pose in the text could be of analytical interest, it will be extremely
difficult to measure empirically. A decision of a prosecutor not to press charges eliminates the need for a
trial. Since the ordeal of a trial might deter people independently of the sanction imposed (if imposed) at its
end, comparing the two probabilities could prove to be a thorny task.
130