Florian Baumann takes an important step forward in the economics of deterrence and group crime in “Should Leniency for Collective Acts Be Extended to Individual Crimes?” The answer to the question is a simple yes, but the answer requires a careful treatment of deterrence in a forward-looking model of both group and individual crime. To provide such a treatment, Baumann adds individual crime to the analysis of ordered leniency for group crime in Landeo and Spier (2018), who find deterrence is maximized when authorities offer leniency for self-reported crime on a first-come, first-served basis. However, if the leniency scheme is not extended to individual crime, deterrence may be weakened or reversed. Intuitively, members of a group can use individual crime as a commitment device to avoid self-reporting. If authorities tend to detect both group and individual crime simultaneously, the additional penalty for the latter reduces the efficacy of an ordered leniency scheme for the former. The deterrent effect of the leniency scheme is reinstated, and even enhanced, through its extension to individual crime. In this comment, I argue for why the implications of this work are deeper than the formal setting of the model may suggest. First, sociology and criminology widely treat crime as a group phenomenon. In fact, one of the few commonly accepted “criminological facts” acknowledges that themajority of criminal acts are committed bymultiple offenders (McGloin et al. 2008). In its preoccupationwith deterrence,
TimFriehe raises a fundamental issue. Should themisconduct ofmoral authorities be punished differently, perhaps more harshly, than the misconduct of followers? It would seemnatural to bemore severewith rolemodels because of the spillover effects of their conduct. The article shows that this reasoning is not necessarily correct. Individuals can engage in an action providing a private benefit b and causing an external harm of amount h. In the standard law enforcement model, deterrence derives from the threat of a legal sanction s. Here behavior also depends onmoral and conformity concerns. There are two types of individuals: A (authority) and F (follower). An individual of either type (i = A, F) suffers an “abstract moral cost” li from committing the act and amoral costrih as a fraction of the harm the individual causes. In addition, a type-F individual suffers a “conformity cost” hb̂A, where b̂A is the benefit threshold for a type-A individual to engage in the activity. The higher b̂A is, the less likely it is
Previous articleNext article FreeComment on “Six Dimensions of Criminal Procedure”Siona ListokinSiona Listokin Search for more articles by this author Full TextPDF Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreGeorgakopoulos and Sullivan’s article “Six Dimensions of Criminal Procedure” contributes to an oft-asked question about courts and judges: Why do justices rule the way they do? Their novel work seeks to describe courts through the judicial tendencies of justice coalitions, eschewing the simplistic unidimensional liberal-conservative model for dynamic multidimensional scaling. This article, along with its predecessors, “Illustrating Swing Votes I: Indiana Supreme Court” and “Illustrating Swing Votes II: United States Supreme Court” (Georgakopoulos and Sullivan 2020a, 2020b), provides ample proof of concept, yet it leaves a number of unanswered questions about the applicability and usefulness of the method.1. How Many Dimensions?Much of the academic and media analysis of court decisions (and in particular, Supreme Court decisions) model the court using the median voter theorem: justices exist on a spectrum from the political left to right, and the median justice has an elevated swing vote characterization.1 Prior work has shown this framing to be inaccurate: courts do not necessarily have a predominate swing voter, and justices at the extremes of the unidimensional spectrum sometimes serve as swing voters.Clearly, then, the median voter theorem does not suffice to comprehensively describe judicial tendencies. Scholars have responded in recent years by suggesting multidimensional scaling to model justice preferences; rather than the left-right divide, justices’ decisions can be mapped onto preferences over civil rights, judicial power, police discretion, and (almost) countless other categories (Clark 2019; Fischman 2015). When done carefully, this mapping can illuminate previously unnoticed coalitional tendencies. For example, the authors note that in their mapping of Indiana Supreme Court split decisions on criminal procedure, the issue of police discretion appears surprisingly rarely despite its assumed centrality in cases with disagreements over intrusive police conduct. This pattern (or lack of pattern) may be hard to discern if one justice is marked as the political center and all decisions are surveyed in that lens.If one dimension misses important coalitions and tendencies, though, how many dimensions are tractable and useful for describing courts? Georgakopoulos and Sullivan are themselves heavily invested in this question. Prior work showed that the extreme case of mapping justices completely, by every rule, produces unusable, noisy results and is not viable. Thus their focus in this article is on the reasonable middle ground, an intermediate multidimensional scaling that uses the authors’ discretion for a particular court and area of law. Here, they focus on rulings on criminal procedure and offer six tendency dimensions, including closure of process, need for defendant’s consents and warnings, governmental and trial bias, police discretion versus warrants, trust in juries, and retroactivity of defenses.The resulting map is copied for reference (see fig. 1). The visual representation is quite clever and well suited to this framing method, and it is a contribution in its own right. Georgakopoulos and Sullivan note that mapping the five-justice court along six dimensions of criminal procedure produces a signal-to-noise ratio of three to one, meaning a quarter of split decision criminal procedure cases in the sample do not fit. These cases have a different coalition of justices/swing voter along the predetermined dimensions, or do not fit into the dimensions well.Figure 1. The circle of all possible dissenting teams and their tendencies about criminal procedure.View Large ImageDownload PowerPointIt is unclear how to evaluate these results. Georgakopoulos and Sullivan provide the following assessments within the article: “[Result] gives cautious optimism about describing the work of courts with locational models of this level of generality,” and “[result] revealed some order, perhaps more than expected. The 3:1 signal-to-noise ratio is not unacceptably low—neither is it strikingly high.” This is not a case of inflated language from overenthusiastic authors, and Georgakopoulos and Sullivan should be commended for their levelheaded appraisal.And yet, the original issue remains over the choice of dimensions. Multidimensional scaling can describe court tendencies more accurately than unidimensional models, but the description will be more complex and will be accompanied by a healthy dose of unexplained variation. In this example, the complexity is high. The model uses six dimensions to describe just one area of the law (criminal procedure), and it is easy to imagine framing courts along 20 or more facets if the author is interested in a broader range of subjects.The trade-off between tractability and completeness is a feature of all models, and future work in this vein will ultimately be judged by the insight that results from authors’ dimension choices. For this proof-of-concept study, though, it would have been useful to offer a different set of dimensions for comparison. This would provide the opportunity to evaluate competing models’ perceptiveness and signal-to-noise ratios.The above discussion highlights that the pivotal choice of dimensions is more art than science. Georgakopoulos and Sullivan are exacting in describing how each of the six dimensions fit the cases that fall into their respective categories. However, the article provides very little insight into the process of dimension choice. Did the authors independently evaluate the cases and come to this decision? Were there competing taxonomies? How might future authors design the classification process? Georgakopoulos and Sullivan note that future analysis could use text analysis to determine dimensionality but do not provide additional guidance as to how.2. ApplicabilitySome of these issues will be resolved as scholars increasingly frame court decisions with multiple dimensions. Concerns over applicability, however, are not easily resolved with familiarity. Georgakopoulos and Sullivan use their deep knowledge of the Indiana Supreme Court to their advantage in this study, and the court is particularly well suited to multidimensional scaling. The state supreme court is composed of five justices, thereby limiting the number of potential coalitions within minority pairs and swing voter (though note that there are multiple possibilities even with the smaller court). In addition, the Indiana Supreme Court was exceptionally stable for a period, leading to a sizable sample of 65 split decisions on criminal procedure between 1999 and 2010.The author’s impressive sample highlights a weakness of the dynamic scaling. Although compositional stability is not required for these models, it simplifies the process greatly. Multidimensionality requires computational depth to be meaningful, by definition. Georgakopoulos and Sullivan note this constraint within their article and conclude with a hope for more stable court compositions to aid this type of analysis.The promise of multidimensional scaling is thus tied in part to its applicability to a range of courts and across time. This inward focus on the courts illuminates a potential folly, however. No analysis of court decisions should be completed in isolation, without consideration of history, culture, and politics. In analyzing how justices make decisions, modeling along more than one dimension should illuminate connections with other institutions rather than disregard them. Other authors within this literature, like Clark (2019) and Fischman (2015), use their dimensional mapping to evaluate the courts’ interactions with other branches of government, special interests, and cultural shifts. Georgakopoulos and Sullivan’s series of articles offers an in-depth look at the potential and pitfalls of multidimensional models for court decisions. Ultimately, its usefulness will depend on our understanding of the world outside the court as well.Notes*George Mason University. Email: [email protected].1 See, e.g., Blasecki (1990); Enns and Wohlfarth (2013); Schmidt and Yalof (2004).ReferencesBlasecki, Janet L. 1990. “Justice Lewis F. Powell: Swing Voter or Staunch Conservative?” Journal of Politics 52 (2): 530–47.First citation in articleLinkGoogle ScholarClark, Tom. 2019. The Supreme Court: An Analytic History of Constitutional Decision Making. Cambridge: Cambridge University Press.First citation in articleGoogle ScholarEnns, Peter K., and Patrick C. Wohlfarth. 2013. “The Swing Justice.” Journal of Politics 75 (4): 1089–107.First citation in articleLinkGoogle ScholarFischman, Joshua Β. 2015. “Do the Justices Vote Like Policymakers? Evidence from Scaling the Supreme Court with Interest Groups.” Journal of Legal Studies 44:269–93.First citation in articleLinkGoogle ScholarGeorgakopoulos, Nicholas L., and Frank Sullivan Jr. 2020a. “Illustrating Swing Votes I: Indiana Supreme Court.” Indiana Law Review 53:95–134.First citation in articleGoogle ScholarGeorgakopoulos, Nicholas L. and Frank Sullivan Jr. 2020b. “Illustrating Swing Votes II: United States Supreme Court.” Indiana Law Review 53:135–62.First citation in articleGoogle ScholarSchmidt, Patrick D., and David A. Yalof. 2004. “The ‘Swing Voter’ Revisited: Justice Anthony Kennedy and the First Amendment Right of Free Speech.” Political Research Quarterly 57 (2): 209–17.First citation in articleCrossrefGoogle Scholar Previous articleNext article DetailsFiguresReferencesCited by Supreme Court Economic Review Volume 282020 Sponsored by the Antonin Scalia Law School, George Mason University Article DOIhttps://doi.org/10.1086/709739 Views: 247 HistoryPublished online September 23, 2020 © 2020 by the University of Chicago. All rights reserved.Crossref reports no articles citing this article.
This review of the criminal deterrence literature focuses on the questions that are largely missing from many recent excellent and comprehensive reviews of that literature and even from the literature itself. By "missing" I mean, first, questions that criminal deterrence scholars have ignored either completely or to a large extent. These questions range from fundamental (the distributional analysis of the criminal justice system) to those hidden in plain sight (economic analysis of misdemeanors), to those that are well-known yet mostly overlooked (the role of positive incentives, offender's mental state, and celerity of punishment). Second, I use "missing" to refer to the areas where substantial relevant knowledge exists but is largely disregarded within the criminal deterrence research program. The empirical analysis of environmental and tax compliance is a stark example. Finally, I stretch "missing" to describe topics that have been both studied and reviewed but where substantial challenges remain. These include the theoretical explanation for the role of offense history, the proper accounting for the offender's gains, the estimation of the costs of various crimes, and the cost-benefit analysis of crime-reduction policies. Among the literature's missing pieces, several stand out both on their own and because they combine to produce a highly unfortunate result. First, although the empirical side of the literature focuses almost exclusively on street crime, the literature makes only a minor effort to estimate the cost of crime and essentially no effort to estimate the cost of white-collar offenses. This adds to the impression—not supported by the available evidence—that street crime is a great social problem while white-collar crime is a minor one. Second, the literature fails to treat misdemeanors and misdemeanor enforcement as an independent subject of study. This failure contributes to the notion—also unjustified—that 13 million or so misdemeanor charges a year and countless millions of stops, frisks, and interrogations that lead to no charges—all heavily skewed by race and class—are also not a major social problem. Third, the literature is only starting to develop a benefit-cost analysis of various crime-reducing strategies. The analysis considers almost exclusively measures reflected in the optimal deterrence model. This creates an impression—almost surely false—that deterrence is the only means of reducing future crime. Finally, the literature ignores distributional analysis altogether, even though the burdens of crime and the criminal justice system vary dramatically, predictably, and disturbingly by race and income. By disregarding this variation, the literature may be reinforcing it. For all these reasons, the criminal deterrence literature may well be contributing to the overwhelming, singular focus of American society and law enforcement on the forceful deterrence of street crime. Addressing the missing pieces would enrich the literature, expand its appeal and policy relevance, and enable academics to contribute to the effort of setting the US criminal justice system on the path of long overdue structural reforms.
In this study, I statistically analyze the deterrent effect of capital punishment in Japan. I first introduce three relatively lesser-known prior studies. The studies have several common limitations: first, in sample size; second, in the econometric methodology (serial correlation, multicollinearity, simultaneity bias, and nonstationary data); and, third, in variable selection. I conduct new analyses to address these problems. In this study, the vector error correction model is adopted to analyze data from 1948 to 2018 with a sample size twice as large as the one used in prior studies. I include both the death sentence rate and the execution rate, analyze homicide and robbery-homicide separately, and use the conviction rate and the life sentence rate to measure the marginal effect of capital punishment. I find that neither the death sentence rate nor the execution rate has a statistically significant effect on the homicide and robbery-homicide rates, whereas the life sentence rate has a significant negative effect on the robbery-homicide rate.
I incorporate individual crime into the analysis of ordered leniency by Landeo and Spier (2020) and show that the proposed policy for collective crime becomes less effective and may induce additional individual acts. Unconditional rebates on fines for self-reported individual crimes restore the original effectiveness of ordered leniency for collective crimes. Conditioning fine rebates for individual crimes on the eligibility for leniency for collective crime further increases deterrence for both collective and individual acts.
Evidence production at trial, the accumulation of patents in a technological race, and lobbying are contests that often involve strategic choices over a discrete set of options. The literature has primarily focused on games with continuous effort choices. We fill this gap by studying a rent-seeking game with discrete effort choices and, for a significant class of games, derive a transformation rule that allows one to find the equilibrium of the discrete game from the equilibrium of the continuous game, which is much simpler to identify. We also discuss the limits of this approach and how well the continuous game approximates the discrete one.
Issues of spatial competition play a key role in many antitrust matters in terms of both defining relevant markets and evaluating competitive effects. One area where this is particularly important is competition among retail outlets such as gas stations and supermarkets. Although detailed data for conducting empirical analyses are available in many retail industries, it is often the case that practitioners must define markets, at least preliminarily, under limited information. In this article, we develop techniques for aiding in defining markets involving spatial competition under limited information. The methodology assumes that consumers make choices within a discrete area rather than assuming those choices are determined by strict calculations of distance to a given retail location.
Previous articleNext article FreeComment on “Accuracy of Verdicts under Different Jury Sizes and Voting Rules”Nuno GaroupaNuno Garoupa Search for more articles by this author Full TextPDF Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMore1. IntroductionThere is an important economic literature on explaining jury behavior. Nevertheless, two of the most important and relevant features—number of jury members and voting rules to reach a verdict—have been explored quite separately. The important contribution by Parisi, Guerra, and Luppi is to put both features together in a single model. The fundamental message of the article is that jury size and voting rules are inversely related—small juries should have unanimous voting rules, whereas large juries are better served with nonunanimous voting rules.My comments refer to two distinct aspects: on one hand, the mathematical modeling and possible relaxation of assumptions; on the other hand, potential contextualization of the fundamental result, in terms of institutional variety and the more general literature on juries.2. Modeling OptionsSimplifying assumptions are a necessary step to allow tractable mathematical analysis. In that respect, the most important result of the article (proposition 4.3) is neat and elegant. Still, there are a few considerations that merit discussion and possibly justify a future extension of the article to more complex mathematical models.Jury heterogeneity is required for any insightful exploration. If jury members are homogenous, then decisions would always be unanimous (no matter the formal voting rule), and the number of individuals would not be a very relevant variable. Everyone is the same regardless. Consequently, the authors introduce heterogeneity by assuming that individual members of the jury observe a signal that reflects culpability, but that signal is not necessarily the same for everyone.As they state, each juror has a probability π, between zero and one, of receiving a strong signal of incriminating evidence, and a probability of 1 – π of receiving a weak signal of incriminating evidence. The significant implication is that the probability π is the same for all jurors, from 1 to N. This is equivalent to saying that the N signals are statistically independent: the signal that each of the N – 1 jurors has observed does not affect the signal that the Nth juror will observe.An alternative assumption is to allow π to vary across jurors. In other words, juror k (with k going from 1 to N) has a probability πk, between zero and one, of receiving a strong signal of incriminating evidence, and a probability of 1 – πk of receiving a weak signal of incriminating evidence. The obvious cost of opting for this alternative assumption is that the probability that mN jurors receive a strong signal is inevitably a more complex mathematical formulation, not really changing the notation exposed on the main text of the article, but definitely requiring additional proofs.Still, the alternative assumption allows a few additional insights. One is possible strategic interactions (a point acknowledged by the authors on footnote 17). If a few jurors exercise natural leadership in the deliberation process, the probability πk can easily capture the complex process in a simple parameter.A different consideration is possible dissimilarities in preferences, any form of individual bias, or behavioral limitations. The authors introduce jurors’ heterogeneity by virtue of asymmetric information. However, in a way, jurors are purely randomly different in the original model (it is just a matter of the signal they observe). It could be that the same incriminating evidence produces different assessments because of preferences or any other mechanism that constrains or shapes jurors’ thinking, including different understandings of the law. Such a source of heterogeneity can be easily reflected in the probability πk.3. ContextualizingThere is a tradition of 12 jurors and unanimous voting rules since early in the common law (Vidmar 2000). It is unlikely that there are economic or rational choice justifications to explain the exact number 12 (unless the choice of 12 apostles is also justifiable by economic considerations or rational choice theories). However, by means of simulation and choice of interesting parameter values, the authors could consider the possibility of discussing how far 12 is from an optimal number, given different voting rules. Equivalently, in the specifics of the model, the US debate over vanishing jury trials could be construed as a shift from 12 to 1 juror (in this case, a judge). A simulation of the model could easily tell the reader how that could affect the different probabilities of wrongful acquittal and wrongful conviction.Such an exercise could actually be relevant for further legal analysis. The authors refer to specific US experience with juries. However, if we take the more general perspective in the common law tradition, there are many additional variations. In criminal litigation in England and Wales, qualified or supermajority voting rules have been observed. Also, juries with less than 12 members, including cases with 11 or 10, have been widely documented. In civil litigation, the number of jury members went down from the traditional 12 often since the eighteenth century, depending on British colonies or regions of the common law world (Vidmar 2000). Unanimity has traditionally not been required in civil cases. The case of Scotland in criminal litigation is yet another well-known variation: 15 jurors, simple majority rule, and three possible outcomes (not proven being the originality there).The model can easily explain some of these features. We can just assume that the stakes are higher in criminal litigation than in civil litigation to justify why unanimous voting is likely to be more important in the former than in the latter. We can easily apply proposition 4.3 to justify why 15 jurors are more consistent with simply majority rules (in Scotland), whereas 12 jurors are usually subject to unanimous voting (in the traditional common law). Nevertheless, the development of a simulation exercise might tease out the different interactions that could be helpful for the comparative debate over the role of juries on criminal and civil litigation.As juries have expanded recently into different jurisdictions around the world (Hans 2017), the applications of the article are more and more important. Consider the saiban-in system in Japan (since March 2009): six laypersons sit with three professional judges. It is a very different institutional setting than the one the authors have in mind. However, if we allow the source of heterogeneity to be reflected by the probability πk, we can actually model current controversies in comparative law—for example, the extent to which the three professional judges dominate the six laypersons and how voting rules should be adjusted. Just consider a qualified majority subject to veto by the three professional judges (even against a majority of six laypersons).Summing up, in my view, the article has the potential to have more ambitious policy implications than the authors originally considered. It is possible that some of these more ambitious policy implications require a more complex mathematical formulation (as suggested, by allowing π to vary across individuals) or the introduction of simulation methods.4. ConclusionsThe article explains the trade-off between number of jury members and voting rules. The driving assumption is the existence of asymmetric information (culpability is not perfectly observable by jurors) and heterogeneity introduced by a signal of strong versus weak incriminating evidence. Although relaxing some simplifying assumptions could easily extend the policy implications of the article, the fundamental result is an important contribution to the economics of criminal litigation.On a more general note, the application of pure rational choice theory to jury behavior should not neglect new insights stemming from behavioral law and economics (Teichman and Zamir 2014). The choice of number of jury members and voting rules is likely to reflect heuristic biases and interact with potential cognitive limitations. Inevitably, a more comprehensive analysis should not shy away from combining approaches to model jury behavior.Notes*George Mason University. Email: [email protected].ReferencesHans, Valerie P. 2017. “Trial by Jury: Story of a Legal Transplant.” Law and Society Review 51:471–99.First citation in articleCrossrefGoogle ScholarTeichman, Doron, and Eyal Zamir. 2014. “Judicial Decision-Making: A Behavioral Perspective.” In The Oxford Handbook of Behavioral Economics and the Law, edited by Eyal Zamir and Doron Teichman, 664–702. Oxford: Oxford University Press.First citation in articleGoogle ScholarVidmar, Neil. 2000. “A Historical and Comparative Perspective on the Common Law Jury.” In World Jury Systems, edited by Neil Vidmar, 1–52. Oxford: Oxford University Press.First citation in articleCrossrefGoogle Scholar Previous articleNext article DetailsFiguresReferencesCited by Supreme Court Economic Review Volume 282020 Sponsored by the Antonin Scalia Law School, George Mason University Article DOIhttps://doi.org/10.1086/709735 Views: 234 HistoryPublished online September 18, 2020 © 2020 by the University of Chicago. All rights reserved.Crossref reports no articles citing this article.
Previous articleNext article FreeThe Influence of Conformity and Moral Concerns on the Level of Optimal Sanctions: Some Comparative-Statics ResultsTim FrieheTim FriehePDFPDF PLUSAbstractFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreAbstractWidespread evidence indicates that social and moral concerns are relevant for potential offenders’ choices regarding norm violation. This article examines a stylization of conformity and moral concerns in a very simple optimal law enforcement framework to explore how these influences shape socially optimal sanction levels. I derive some comparative-statics results and explain that findings depend critically on the extent to which expected sanctions are socially costly.1. IntroductionAccumulated evidence from both the field and the laboratory demonstrates that people often align their attitudes, beliefs, and behaviors with those of the people around them, either partially or fully (e.g., Chen et al. 2010; Cialdini, Reno, and Kallgren 1990; Frey and Meier 2004; Krupka and Weber 2009). Such tendencies to conform may be explained via factors such as community sanctions (Akerlof 1980), social signaling (Bernheim 1994), and the information conveyed by others’ choices (Bikhchandani, Hirshleifer, and Welch 1992). Conformity potentially influences behavior in many important domains of life. Kahan (1997) argues that social influence is important for individuals’ decisions to commit crime and, for example, Falk and Fischbacher (2002) present experimental data suggesting that agents are indeed more likely to violate norms when they expect others to do so.This article considers a simple setup with two potential offenders, only one of whom has conformity concerns (i.e., perceives a cost from offending when the other individual is unlikely to offend).1 The rationale and interest for this simple unidirectional framework lie in the observation that some individuals act as moral authorities for others, which makes it interesting to consider whether we want to treat such moral authorities differently in terms of optimal law enforcement. For example, Portman (2019) argues that celebrities such as actors and athletes are increasingly seen as providing a moral compass to many people. Importantly, related is the discussion about whether celebrities receive preferential treatment in America’s justice system (e.g., Glater 2005).I explore how socially optimal sanctions change when such conformity concerns are relevant. In addition to conformity concerns and the traditional expected sanction, I consider two additional deterrents, namely, abstract moral costs and moral costs as a share of social harm, seeking to understand how such aspects affect socially optimal sanctions, whether the distinction is relevant for socially optimal sanctions, and whether the presence of conformity concerns bears on their role for deterrence. Morality traits may already influence actual sanctioning decisions because they will factor into a legal decision maker’s sanction assessment when considering the defendant’s character and attitude in light of a likelihood of reoffending (Keagle 2019), for example.One may argue that moral authorities’ conduct has greater social importance than that of less influential individuals because their choices have not only direct social repercussions stemming from their own choices and actions but also spillover effects on others’ choices. One possible narrative in this context may say that moral authorities’ violations legitimize violating the norm in the eyes of onlookers, thereby inducing subsequent violations. This argumentation may support the expectation that moral authorities who violate norms should receive harsher punishment because they are causing not only a direct social harm from the violation but also an indirect social harm from the deterioration of the perception of the norm.Within the limits of my simple framework, I find that introducing conformity concerns may lower or increase socially optimal sanction levels. Importantly, my results do not generally support the expectation that moral authorities should receive harsher sanctions. The ranking may be reversed, for example, when sanctions are socially costless to impose or when we suppose that moral authorities are—in line with their social status—characterized by greater moral concerns. On a different note, my results also suggest that distinguishing between abstract moral costs and moral costs stemming from the partial internalization of harm is important because socially optimal sanctions may respond differently to variations in the importance of these two influences. Overall, I find that the extent to which sanctioning offenders causes social costs is an important driver of our comparative-statics results.1.1. Related LiteratureThe standard account of individuals’ decisions regarding criminal involvement assumes that they are independent of each other (e.g., Becker 1968; Polinsky and Shavell 2007). However, contributions taking interdependencies among potential offenders into account exist in the rich literature on optimal law enforcement. For example, Bar-Gill and Harel (2001), Ferrer (2010), and Jost (2001) explore the implications of having the crime rate influence the expected sanction due to congested enforcement resources, inter alia. Funk (2005), for example, assumes that moral costs decrease in the crime rate and explains how social norms may bring about multiple equilibria. Garoupa (2003) similarly specifies a cost of violating against the social norm of “don’t rob” that is decreasing in the number of robbers. In contrast to the preceding literature, this article seeks to describe how socially optimal sanctions should respond to variations in the conformity concerns or other moral considerations.The present contribution builds on the large literature on the optimal public enforcement of law (e.g., Polinsky and Shavell 2007). In this strand of the literature, contributions try to map optimal enforcement efforts and sanctions to changing circumstances. For example, Polinsky and Shavell (1992) consider the scenario in which the imposition of fines is socially costly and explain how, in such a case, the optimal fine differs from the optimal fine known from the standard setup. Along similar lines, Polinsky (2006) characterizes optimal sanctions and auditing when wealth is costly to observe. In the present article, I provide an intuition about how optimal sanctions should qualitatively reflect individuals’ social and moral concerns.1.2. Plan of the ArticleThe rest of the article is organized as follows. In section 2, I describe the model. The equilibrium analysis is contained in section 3, including the heart of the present study, that is, my comparative-statics results. I conclude in section 4.2. The ModelFor simplicity, I consider the simplest structure possible, consisting of two potential offenders only. Each individual decides about whether to commit a given criminal act that creates a social harm amounting to h. The potential benefits from crime come from the set [0, B] and are represented by a draw from a uniform distribution function, F(b)=b/B.2 I follow the literature by assuming that the maximal criminal benefit B is sufficiently high to make some offenses socially worthwhile (e.g., Polinsky and Shavell 2007), which in my setup means that B exceeds the social harm h and the abstract moral costs internalized by individuals.I am interested in socially optimal law enforcement and distinguish a sanction level relevant for the moral authority from that level relevant for the follower who seeks conformity. If individual i chooses to offend, that individual will be detected with probability p and penalized by a sanction si, i=A, F, where A denotes authority and F denotes follower. Actually imposing a sanction amounting to si implies a social cost of ηsi. I consider the scenarios in which the sanction is a socially costless transfer (i.e., that η=0) and the case in which the sanction is socially costly (i.e., η>0, where η, η<η¯<1/2, is the social cost from punishment not internalized by the individual). I consider the detection probability as a fixed parameter to simplify my argumentation.Undertaking the offense implies incurring not only the expected sanction but also additional costs. First, I assume that the follower seeks conformity with the choices of the moral authority (see, e.g., the evidence in Diekmann, Przepiorka, and Rauhut [2015]). Individual A is not subject to similar conformity concerns. To represent individual F’s conformity concerns in a straightforward manner, I model a cost that individual F incurs when F offends that amounts to θb^A, where b^A is the critical benefit level of individual A and θ∈(0,Θ), where Θ<1/2. This means that an offending individual F incurs a higher cost when the authority is less likely to engage in the criminal act. Next, I consider the possibility that there is an abstract moral cost μi≥0 that individual i incurs when engaging in the criminal act. For example, in the literature on lying, it is commonly assumed that lying individuals bear a moral cost that is unrelated to the possible social harm of the specific lie (e.g., Abeler, Nosenzo, and Raymond 2019). Gordon (1989), for instance, uses a similar assumption in the context of tax evasion. Finally, I allow individuals to internalize a share σi∈[0,σ¯) of the social harm created, where σ¯<1. Such incorporation is backed by the empirical evidence on altruism (e.g., Fehr and Schmidt 2006). Therefrom, I obtain h˜i=h(1−σi) as the harm that individual i does not internalize.In stage 1, the policy maker commits to sanction levels (sA, sF). In stage 2, nature draws the criminal benefit b from the uniform distribution on [0, B] for both agents. The realization for individual A is independent of that for individual F. Each individual is unaware of the other’s criminal benefit. Next, in stage 3, potential offenders simultaneously choose whether or not to offend.3. The Analysis3.1. Equilibrium Characterization3.1.1. Stage 3: OffendingIn stage 3, potential offenders compare their realization of the criminal benefit to their total expected costs from offending. Individual A’s total expected costs include the expected sanction, psA≥0, the abstract moral costs, μA≥0, and the internalized social harm, σAh≥0. Individual F’s total expected costs include not only the expected sanction, psF≥0, the moral costs, μF≥0, and the internalized social harm, σFh≥0, but also the conformity costs, θb^A≥0.As is standard, I assume an outside option yielding a payoff of zero. I thus obtain critical benefit levels for individual A and individual F amounting to(1)b^A(sA)=psA+μA+σAh(2)b^F(sF,sA)=psF+μF+σFh+θb^A(sA)=psF+μF+σFh+θ(psA+μA+σAh).The probability ex ante that individual i will offend then results asΩi=1−b^iB,as I assume a uniform distribution for criminal benefits. The statement in equation (2) shows that the deterrence of individual A, the moral authority, complements the deterrence of individual F, the follower. It may thus be argued that changing the deterrence of individual A has a “double dividend” in the sense that it lowers the probability that individual A will be involved in a criminal undertaking but at the same time also deters individual F from offending (see, e.g., Funk [2005] for a related argument concerning social norms). This interdependence may fuel the expectation that creating deterrence for moral authorities should be relatively more important than creating deterrence for individuals whose behavior has no similar influence on other agents in the society.3.1.2. Stage 1: Sanction LevelsThe policy variables are determined in stage 1. As is standard (e.g., Polinsky and Shavell 2007), I assume that the social planner is seeking to maximize a utilitarian welfare function, using the sanction levels sA and sF. When subscribing to this approach in formulating welfare, I incorporate the costs individuals A and F incur when they offend. Whereas individual i internalizes only share σi of social harm, total social harm is relevant for welfare. The simple framework with only two potential offenders that I consider in this article yields the social planner’s problem asmaxsA≥0,sF≥0W=WA+WF,whereWA(sA)=1B∫b^AB(b−h−μA−ηpsA)db,WF(sF,sA)=1B∫b^FB(b−h−μF−ηpsF−θb^A)db.Assuming interior solutions for this problem throughout this article, I state the first-order conditions as(3)∂W∂sA=∂WA∂sA+∂WF∂sA=0(4)∂W∂sF=∂WF∂sF=0,highlighting the fact that the sanction applied to the moral authority is relevant for the welfare obtained from both individual A and individual F, whereas the sanction applied to the follower is relevant only for the welfare obtained from individual F.3The partial effect∂Wi∂si=p(h˜i+(η−1)psiB−ηΩi)contains the benefit from marginally higher deterrence (resulting from the difference between what the social planner and the offender internalize in terms of social harm and sanctioning costs), and the marginal increase is sanctioning costs. The partial effect∂WF∂sA=pθ(h˜F+(η−1)psFB−ΩF)shows that the sanction applied to the authority has effects on the welfare that can be obtained from the follower that are similar to what can be achieved using the sanction sF. Increasing sA marginally increases b^F by θp, which may be desirable when the follower’s deterrence is not at the first-best level. However, because a marginally higher b^A raises the follower’s overall nonpecuniary costs should the follower engage in the offense, there is also a marginal cost associated with the marginal increase in terms of its effect on individual F. It is noteworthy that this marginal cost is not weighted by the parameter η, as this implies one key distinction relative to how the welfare that can be obtained from individual F changes with the sanction for the follower (i.e., ∂WF/∂sF).The first-order conditions define socially optimal sanction levels. When seeking to understand whether the optimal level for one individual depends on the level applied to the other individual, one may turn to the “best-response” functions sA*(sF) and sF*(sA) resulting from the first-order conditions when seen in isolation and find thatdsi*dsj=−∂2WF∂sA∂sF∂2W∂si2=−ηθpB∂2W∂si2>0,i, j=A, F, i≠j, meaning that there is an interdependence as mentioned if ηθ>0, thus requiring both conformity concerns and the social costliness of sanctions. Figure 1 illustrates “best-response” functions as an example, based on the assumptions μi=0.1, σA=0.2>0.1=σF, p=1/3, h=9, and B=15. These assumptions are maintained in other illustrations unless otherwise noted.Figure 1. “Best-response” functions when η=1/4 and μA=μF while σA>σF.View Large ImageDownload PowerPointThe equilibrium levels simultaneously solve both first-order conditions and are denoted sAO and sFO. Turning to comparative-statics effects, I am interested in how the optimal sanction levels change when a parameter changes; that is, I am concerned about(5)dsAOdϒ=1H(∂2W∂sF∂ϒ∂2W∂sF∂sA−∂2W∂sA∂ϒ∂2W∂sF2)and(6)dsFOdϒ=1H(∂2W∂sA∂ϒ∂2W∂sF∂sA−∂2W∂sF∂ϒ∂2W∂sA2),where H denotes the Hessian matrix and ϒ stands for any of our exogenous parameters σi, μi, or θ. The sufficient second-order conditions, ∂2W/∂si2<0 and H>0, are fulfilled. In the parentheses, the first (second) term represents the indirect (direct) effect of the parameter change. As explained previously, we have that ∂2W/∂sF∂sA is nonzero only if ηθ is nonzero. This means that indirect effects will be irrelevant if ηθ=0. Having derived these observations, I present my findings starting with the case of socially costless sanctions.3.2. Predictions According to Costliness of Sanctions3.2.1. Socially Costless SanctionsWhen sanctions are socially costless to impose (as is commonly assumed in the often studied case of monetary fines), the socially optimal sanction for the follower induces individual F to perfectly internalize the remaining share of social harm h˜F, corrected for the level of the detection probability p, which reminds us of the socially optimal fine in the standard framework (e.g., Polinsky and Shavell 2007). The follower is thus deterred optimally, which means that the marginal effect ∂WF/∂sA includes only the direct effect on individual F’s costs when undertaking the offense. This additional influence of an increase in individual A’s sanction signifies that the socially optimal sanction for the authority is not set at the level that would induce the moral authority to perfectly internalize the remaining share of social harm h˜A because there exists a positive marginal cost even if sanctions are socially costless. I thus find that the follower’s conformity concerns induce a downward adjustment of the sanction addressed at the moral authority.Referring to equations (5) and (6), we note that the respective first terms are equal to zero because ∂2W/∂sA∂sF is equal to zero. There are thus no feedback effects stemming from possible changes in the level of the other sanction. Moreover, with η=0, the partial effect ∂WF/∂sF is independent of the parameters pertaining to individual A (as they enter via ΩF). As a result, when considering parameter variations, I obtain a change in the level of the socially optimal sanction for the follower only when σF changes. In the presence of conformity concerns, the socially optimal level sanction for the authority responds to all variables except σF, where the latter result is due to the fact that σF cancels out in ∂WF/∂sA. In contrast, without conformity concerns, sAO would vary only with σA.Proposition 1. Assume that sanctions are socially costless (i.e., η=0). (1) When σA=σF, the socially optimal sanction for the moral authority is smaller than that for the follower (sAO0.1=μF while σA=σF=0.1 and (B) μA=μF=0.1 while σA=0.15>0.1=σF.View Large ImageDownload PowerPointThe finding that the socially optimal sanction for the authority falls short of that for the follower may be surprising at first. However, in the present circumstance in which optimal deterrence of the follower can be achieved at no marginal cost, it is clear that there is no positive role to the influence of the authority’s expected sanction in the decision making of the follower. Indeed, the policy maker would prefer a scenario without conformity concerns by the follower and then adjust both sanction levels to h˜i/p. This seriously questions the common “double dividend” hunch. On a different note, it is noteworthy that the two different ways of representing pure moral considerations, σi and μi, have very different comparative-static results, particularly in the presence of conformity concerns.3.2.2. Socially Costly SanctionsWe now consider the scenario in which η>0, which is relevant when imprisonment is the applicable kind of sanction, for example. With positive social costs of implementing the expected sanction psi, individual F is not optimally deterred such that the influence of the authority’s expected sanction in the decision-making of the follower may be beneficial.For the derivation of comparative-statics results, we have to incorporate both direct and indirect effects because ∂2W/∂sA∂sF>0 when η>0. Consider, for example, a marginal increase in the share of harm internalized by individual F. The direct effect on sAO is zero as ∂2W/∂sA∂σF is zero. However, because the direct effect on sFO is negative and because sanction levels are strategic substitutes, we obtain that the socially optimal sanction for the moral authority decreases with σF. As a result, the interdependence created via conformity costs and socially costly sanctions makes even seemingly straightforward comparative-statics regarding σF interesting to explore. I summarize some unambiguous results in proposition 2:Proposition 2. Assume that sanctions are socially costly (i.e., η>0). (1.a) A marginal increase in σi decreases both sAO and sFO. (1.b) A marginal increase in μi increases both sAO and sFO.Proof. See the appendix. QEDI am primarily interested in the role of the follower’s conformity concerns. In this respect, I find that(9)∂2W∂sA∂θ=−pB−h−μF−ηpsF−2θ(μA+hσA+psA)B(10)∂2W∂sF∂θ=pη(μA+hσA+psA)B,where the first term is negative at small θ, which implies a negative direct effect on the socially optimal sanction of the authority. With ∂W/∂sF=0 and η<1, we must have that ∂WF/∂sA<0, which is important for the negative direct effect. In contrast, the second term is positive, which implies a positive direct effect on the socially optimal sanction of the follower. The higher level of θ, ceteris paribus, lowers the marginal costs of raising sF. Using numerical examples, we find that a marginal increase in the follower’s conformity concerns produces a U-shape regarding sAO and an increasing pattern for sFO (see fig. 3).Figure 3. Socially optimal sanctions as a function of conformity concerns when η=1/4 and (A) μA=2.1>0.1=μF while σA=σF=0.1 and (B) μA=μF=0.1 while σA=0.15>0.1=σF.View Large ImageDownload PowerPointThese results again highlight that the socially optimal sanction addressed at the moral authority is not necessarily higher than that directed at the follower without social influence. In fact, if we consider the case in which individuals A and F are symmetric in terms of moral costs, the numerical example from figure 3 produces sAO1For the case when η>0, the first-order conditions may be stated as follows:(11)h+(η−1)σAh+(2η−1)psA+ημA−ηB+θ(h+ηpsF+μF+θ(μA+σAh+psA)−B)=0(12)h+(η−1)σFh+(2η−1)psF+ημF−ηB+ηθ(μA+σAh+psA)=0From these conditions follow the equilibrium sanction levels as(13)sAO=1χ(h((η−1)2σAθ2−(2η−1)(1+(η−1)σA)−(1−ησF)(η−1)θ)−B(θ+η(1−η(2−θ)−2θ))−μA(η(2η−1)−(η−1)2θ2))+μF(η−1)2θ)(14)sFO=1χ(h((1−ησA)ηθ+(η−1)(1−σF)θ2−(2η−1)(1+(η−1)σF))−Bη(1−η(2−θ))−μAη(η−1)θ−μFη(2η−1))whereχ=p(θ2−1−η(4(η−1)+(2−η)θ2))is negative when η=0 or η>0 given our restrictions on θ and η.4Using the explicit statements for the sanction levels, I obtain the following partial derivatives:• a marginal increase in the share of harm that individual A internalizes yields a decrease in both socially optimal sanction levels:(15)∂sAO∂σA=h(1−η)(1−2η−θ2(1−η))χ<0(16)∂sFO∂σA=hη2θχ<0• a marginal increase in the share of harm that individual F internalizes yields a decrease in both socially optimal sanction levels:(17)∂sAO∂σF=hη(1−η)θχ<0(18)∂sFO∂σF=h(1−η)(1−2η−θ2)χ<0• a marginal increase in the fixed moral costs of individual A yields an increase in both socially optimal sanction levels:(19)∂sAO∂μA=−η(1−2η)−(η−1)2θ2χ>0(20)∂sFO∂μA=η(η−1)θχ>0• a marginal increase in the fixed moral costs of individual F yields an increase in both socially optimal sanction levels:(21)∂sAO∂μF=−(η−1)2θχ>0(22)∂sFO∂μF=−η(1−2η)χ>0Notes*MACIE, University of Marburg; Am Plan 2, 35037 Marburg, Germany. CESifo, Munich, Germany. Email: [email protected]. I gratefully acknowledge the comments received from Nicholas L. Georgakopoulos, Jeremy Mott, Cat Lam Pham, and an anonymous reviewer. Moreover, I wish to express my gratitude to the editor, Murat Mungan, for organizing the event.1 My model deals with normative conformity. Potential offenders are aware of the social harm imposed such that the other’s criminal tendency is not serving as a signal for the harmfulness of the act, for example.2 Garoupa (1999), e.g., also considers a uniform distribution for criminal benefits.3 The second derivatives are ∂2W/∂sA2=(2η−1+θ2)p2/B and ∂2W/∂sF2=(2η−1)p2/B and thus negative if η<1/2. The condition ∂2W/∂sA2∂2W/∂sF2>(∂2W/∂sA∂sF)2 is also fulfilled.4 The explicit solutions were derived using Mathematica.ReferencesAbeler, J., D. Nosenzo, and C. Raymond. 2019. “Preferences for Truth-Telling.” Econometrica 87:1115–53.First citation in articleCrossrefGoogle ScholarAkerlof, G. A. 1980. “A Theory of Social Custom, of Which Unemployment May Be One Consequence.” Quarterly Journal of Economics 94:749–75.First citation in articleCrossrefGoogle ScholarBar-Gill, O., and A. Harel. 2001. “Crime Rates and Expected Sanctions: The Economics of Deterrence Revisited.” Journal of Law and Economics 30:485–501.First citation in articleGoogle ScholarBecker, Gary S. 1968. “Crime and Punishment: An Economic Approach.” Journal of Political Economy 76:169–217.First citation in articleLinkGoogle ScholarBernheim, B. D. 1994. “A Theory of Conformity.” Journal of Political Economy 102:841–77.First citation in articleLinkGoogle ScholarBikhchandani, S., D. Hirshleifer, and I. Welch. 1992. “A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades.” Journal of Political Economy 100:992–1026.First citation in articleLinkGoogle ScholarChen, Y., F. M. Harper, J. Konstan, and X. L. Sherry. 2010. “Social Comparisons and Contributions to Online Communities: A Field Experiment on MovieLens.” American Economic Review 100:1358–98.First citation in articleCrossrefGoogle ScholarCialdini, R. B, R. R. Reno, and C. A. Kallgren. 1990. “A Focus Theory of Normative Conduct: Recycling the Concept of Norms to Reduce Littering in Public Places.” Journal of Personality and Social Psychology 58:1015–26.First citation in articleCrossrefGoogle ScholarDiekmann, A., W. Przepiorka, and H. Rauhut. 2015. “Lifting the Veil of Ignorance: An Experiment on the Contagiousness of Norm Violations.” Rationality and Society 27:309–33.First citation in articleCrossrefGoogle ScholarFalk, A., and U. Fischbacher. 2002. “‘Crime’ in the Lab—Detecting Social Interaction.” European Economic Review 46:859–69.First citation in articleCrossrefGoogle ScholarFehr, E., and K. Schmidt. 2006. “The Economics of Fairness, Reciprocity, and Altruism—Experimental Evidence and New Theories.” In Handbook on the Economics of Giving, edited by S. C. Kolm and J. M. Ythier. Amsterdam: Elsevier.First citation in articleGoogle ScholarFerrer, R. 2010. “Breaking the Law When Others Do Too: A Model of Law Enforcement with Neighborhood Externalities.” European Economic Review 54:163–80.First citation in articleCrossrefGoogle ScholarFrey, B. S., and S. Meier. 2004. “Social Comparisons and Pro-Social Behavior: Testing ‘Conditional Cooperation’ in a Field Experiment.” American Economic Review 94:1717–22.First citation in articleCrossrefGoogle ScholarFunk, Patricia. 2005. “Governmental Action, Social Norms, and Criminal Behavior.” Journal of Institutional and Theoretical Economics 161:522–35.First citation in articleCrossrefGoogle ScholarGaroupa, N. 1999. “Optimal Law Enforcement with Dissemination of Information.” European Journal of Law and Economics 7:183–96.First citation in articleCrossrefGoogle ScholarGaroupa, N. 2003. “Crime and Social Norms.” Portuguese Economic Journal 2:131–44.First citation in articleCrossrefGoogle ScholarGlater, J. D. 2005. “Debating the Role of Celebrity in the System.” New York Times. Last accessed December 2, 2019. http://nytimes.com/2005/06/15/us/debating-the-role-of-celebrity-in-the-system.html.First citation in articleGoogle ScholarGordon, J. P. F. 1989. “Individual Morality and Reputation Costs as Deterrents to Tax Evasion.” European Economic Review 33:797–805.First citation in articleCrossrefGoogle ScholarJost, P. J. 2001. “Crime, Coordination, and Punishment: An Economic Analysis.” International Review of Law and Economics 21:23–46.First citation in articleCrossrefGoogle ScholarKahan, D. M. 1997. “Social Influence, Social Meaning, and Deterrence.” Virginia Law Review 83:349–95.First citation in articleCrossrefGoogle ScholarKeagle, H. Y. 2019. “Manual on New Jersey Sentencing Law. Appelate Division, New Jersey Superior Court.” Last accessed December 2, 2019. http://njcourts.gov/attorneys/assets/attyresources/manualsentencinglaw.pdf?c=gFx.First citation in articleGoogle ScholarKrupka, E., and R. A. Weber. 2009. “The Focusing and Informational Effects of Norms on Pro-Social Behavior.” Journal of Economic Psychology 30:307–20.First citation in articleCrossrefGoogle ScholarPolinsky, A. M. 2006. “Optimal Fines and Auditing When Wealth Is Costly to Observe.” Journal of Public Economics 26:323–35.First citation in articleGoogle ScholarPolinsky, A. M., and S. Shavell. 1992. “Enforcement Costs and the Optimal Magnitude and Probability of Fines.” Journal of Law and Economics 35:133–48.First citation in articleLinkGoogle ScholarPolinsky, A. M., & S. Shavell, eds. 2007. “Public Enforcement of Law.” In Handbook of Law and Economics. Amsterdam: North Holland.First citation in articleGoogle ScholarPortman, J. 2019. Celebrity Morals and the Loss of Religious Authority. New York: Routledge.First citation in articleGoogle Scholar Previous articleNext article DetailsFiguresReferencesCited by Supreme Court Economic Review Volume 282020 Sponsored by the Antonin Scalia Law School, George Mason University Article DOIhttps://doi.org/10.1086/709736HistoryPublished online September 15, 2020 © 2020 by the University of Chicago. 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Searching for dimensions or judicial tendencies about criminal procedure in a long-lived composition of the Indiana Supreme Court, we find six and produce their graphical illustration. The resulting signal-to-noise ratio of about 3∶1 gives cautious optimism about describing the work of courts with locational models of this level of generality.
In “Judicial Choice among Cases for Certiorari,” Álvaro Bustos and Tonja Jacobi develop a newmodel to investigate the Supreme Court’s grant of certiorari. Themodel focuses onwhich case the Court should select to make new law. Should the Court hear a case that clarifies the law as much as possible? Should the Court select a case that sets the law according to the desires of the median justice? Why does the Court, on occasion, grant certiorari in a series of cases that make minor changes to the existing law and at other times make sweeping change in a single case? The prior literature on certiorari is mainly empirical, focusing on the case characteristics—like the presence of a circuit split—that predict whether the Supreme Court will hear a case (Hellman 1985; Black and Owens 2009; Beim and Rader 2015). Bustos and Jacobi fruitfully advance the literature by asking not just whether the Supreme Court will hear a case but also what facts the Court will hunt for to develop new doctrine. I think this an interesting and unexplored question. Described briefly later, themodel is coherent andwell executed. It surfaces nonobvious trade-offs faced by the SupremeCourt in its selection of a case for discretionary review, trade-offs that would not be apparent without the aid of the formal analysis. The article presents several results. I focus on two. First, themodel demonstrates that, under reasonable conditions, the Court would not
A typical discussion of judicial review pits the view of Alexander Hamilton in Federalist no. 78 (protection from the “cabals of a representative body”) against the much more circumscribed view of Justice Owen Roberts (“lay the article of the Constitution which is invoked beside the statute which is challenged and decide whether the latter squares with the former”). This tension between two views informs much of the current debate over judicial review. But the “tension” is illusory; the real problem can be analyzed as a two-dimensional spatial problem, with participants having preferences over both the substantive issue being litigated and the principle of judicial review in the abstract. This article presents a set of results based on such a spatial analysis and considers an answer to the apparent paradox that judicial review may prevail against political majorities for long periods. Furthermore, the results from the model indicate that any purely issue-oriented “median voter” approach to court voting is misspecified and will lead to incorrect predictions.
The Supreme Court’s campaign finance jurisprudence rests on a distinction between spending restrictions (generally struck) and contribution restrictions (often upheld). In Buckley v. Valeo (1976), the case originating this distinction, the majority rejected an “anti-distortion” rationale for spending restrictions, claiming that campaign spending is merely an effect of candidate support, not a cause of candidate support. If this claim is true, then removing restrictions on campaign spending should have no discernible causal impacts. This article tests the Buckley majority’s empirical claim using its own ruling, which struck limits on campaign spending in state elections in 26 states. Estimates consistently suggest that the Buckley-induced removal of state limits on campaign spending led to increased Republican vote shares, increased Republican candidate entry, and decreased Democratic candidate entry in state legislative and gubernatorial elections in states affected by the ruling, as well as increased Republican House vote shares and the election of more conservative House incumbents in states both affected by the ruling and holding concurrent federal and state elections. These findings suggest that the rationale for the core distinction in the Supreme Court’s campaign finance jurisprudence has little empirical foundation.
Prosecutors are immensely influential in every judicial system, yet very little is known about the impact of their organization. Here we ask two questions: (1) whether crimes committed by public officials are more likely to be prosecuted when prosecutors are independent and (2) whether this effect depends on the integrity of the prosecutors themselves. We use a novel indicator for prosecutorial independence based on data from the World Justice Project to answer these questions. We find that prosecutorial independence favors the prosecution of different types of public officials and that this effect appears to be conditional on the level of prosecutorial accountability.
How does the Supreme Court choose among cases to grant cert? In a model with a strategic Supreme Court, a continuum of rule-following lower courts, a set of potential cases for revision, and a distribution of future lower court cases, we show that the Court takes the case that will most significantly shape future lower court case outcomes in the direction that the Court prefers. That is, the Court grants cert to the case with maximum salience. If the Court is rather liberal (or conservative), then the most salient case is that which moves the discretionary range of the legal standard as far left (or right) as possible. But if the Court is moderate, then the most salient case will be a function of the skewedness of the distribution of ideologies of the lower courts and the likelihood that future cases will fall within the adjusted discretionary range. The extent of the political alignment of lower courts affects not only substantive lawmaking by the Supreme Court but also the earlier decision of whether to grant a given case cert to begin with.
Previous articleNext article FreeTesting for the Effect of Campaign Expenditure LimitsThomas StratmannThomas Stratmann*George Mason University. Search for more articles by this author PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreThe consequences of campaign expenditure limits are an understudied area in the field of campaign finance. The article “Is Campaign Spending a Cause or an Effect? Reexamining the Empirical Foundations of Buckley v. Valeo (1976)” by Anna Harvey is a welcome and interesting contribution to this field of study. Harvey’s article covers a lot of ground. It analyzes the effect of campaign expenditure limits on electoral outcomes for state House races, governor races, and federal races, and on US House of Representatives DW-NOMINATE scores. In this discussion of the article, I focus on the methodology employed and suggest future work that can build on the current article.In 1976 the Supreme Court found that campaign expenditure limits in electoral races are unconstitutional. Twenty-six states had these limits prior to 1976, both for state legislative and gubernatorial elections. After 1976, these 26 states were forced to repeal their expenditure limits. Harvey exploits these repeals in her empirical analysis by studying elections in the majority of the 50 states between 1972 and 1981. A large part of the empirical analysis in this article uses state and year fixed effects to identify the effect of the 1976 Supreme Court decision and uses outcome in a state House district in a given state in a given year as the unit of observation.The article suggests that repeal of expenditure limits for state legislative races had an effect on electoral outcomes and political competition. In particular, the results show that campaign expenditure limits hurt Republican candidates in terms of vote shares and political participation. The hypothesized mechanism is with the lifting of expenditure limits Republican candidates are able to spend larger amounts on their election campaigns, which in turn generates a larger vote share. A related idea proposed in this article is that the lifting of limits leads to entry by more Republican candidates because the lifting of limits allows them not to be subject to caps on spending. Although the regression results in the article support these hypotheses, it would be nice to have additional supporting evidence. For example, prior to 1976, were Republican candidates, as opposed to Democratic candidates, more likely to bump up against the spending limits? Another piece of supporting evidence might come from testing whether the effect found in this article was stronger in those states that had more stringent campaign expenditure limits.If expenditure limits have a bite, that is, if limits are in effect binding, their removal may motivate potential candidates to enter a race. The belief that they are binding may also motivate potential candidates to enter the race. It would be nice to have more evidence whether, prior to Buckley v. Valeo, expenditure limits were binding and, if so, for what percentage of all candidates, perhaps broken down by incumbents, challengers, and candidates in open seat races. And it would be good to know something of the “conceived wisdom” at that time, perhaps from newspaper articles, to what extent expenditure limits had a bite. However, these data are difficult to come by. One way to get to the issue for whom expenditure limits were binding prior to the 1976 decision is to analyze whether the striking down of expenditure limits had an asymmetric effect for a major party candidate entry versus a minor party entry, for incumbents versus challengers, or for entry in open seat races. For example, if major party candidates face fewer constraints in raising campaign contributions relative to minor party candidates and, consequently, major party candidates spend more on their campaigns, then lifting of expenditure restrictions may increase major party candidate entry.Hopefully, future theoretical work might provide more guidance for empirical work on campaign expenditure limits. In particular, theoretical work might suggest additional channels and mechanisms of how expenditure limits might matter for electoral outcomes and under what type of circumstances expenditure limits matter for political competition and participation. Other measures of competitiveness in addition to those in Harvey’s article could be examined as well, such as incumbency reelection rates, the frequency of competitive elections, and the frequency of open seat races.Other avenues of future research may examine whether the documented effect occurs because Republicans experienced an increase in campaign contributions, which in turn resulted in more spending. Or, assuming expenditure limits were binding, did Republican supporters contribute less to their preferred candidate prior to Buckley because they knew that their contributions could not be spent because of expenditure limits?For the analysis in this article, it is of interest to unpack the coefficient of interest, that is, to show the dynamics. Given the span of the data analyzed, different coefficients can be estimated for the two elections prior to the Buckley decision and for the three election years after that decision. This way we can better understand whether the estimated effect is because of an immediate change after the 1976 decision as opposed to a gradual adjustment over time. Or perhaps there was a large immediate effect that was attenuated over time. The descriptive statistics suggest that there was a onetime bump in entry, right after the Supreme Court decision, and a fairly stable pattern after 1976. It would be nice to see if such a statistical analysis would be consistent with these descriptive statistics.Given that some states have fewer than 100 House races (e.g., California) and others have more than 300 House races (e.g., New Hampshire), a regression analysis that uses a House race as a unit of observation will weigh the campaign expenditure law in states with a larger number of races more heavily. An alternative to the approach taken in the article would be to make the unit of observation a state in a given year, an approach which weights each state equally. Which approach is correct depends on the research question and hypotheses. At the same time, from a welfare perspective, districts composed of smaller populations are underweighted in a regression analysis that has a district as a unit of observation, as are low population states where the unit of observation a state. Which specification is correct will depend on the hypotheses being tested and the research question of interest.It would be nice to learn a bit more about what other elements of state election laws were changed when states adjusted their statutes in response to Buckley v. Valeo. For example, did states that removed their campaign expenditure limits increase, at the same time, their contribution limits from individuals, corporations, unions, or political action committees? Did they change public funding provisions or alter other aspects of their election laws, such as candidate ballot access or signature requirements?As in all studies that examine changes of a particular law, the concern is whether the particular introduction or removal of the law is the only thing that changed in the same legislative period, whether other laws were introduced at the same time, or whether regulatory procedures changed, which could account for some or all of the estimated effect. Harvey is clearly aware of these issues, as evidenced by offering a number of robustness tests. I would have liked to see some of the robustness tests shown as the main specification in the article rather than in an appendix.From reading this article, it is my understanding that the Supreme Court suggested that contribution limits are justified because of corruption concerns, but that campaign expenditures as a function of campaign contributions (i.e., underlying electoral support) were ruled not to be subject to caps. Put differently, the Supreme Court reasoned that campaign spending merely reflects the underlying support of the candidate and, thus, does not merit being limited. Although I follow the Court’s logic, I do not quite understand the view put forth in this article; that is, with this decision and line of reasoning, the Supreme Court implied that expenditure limits do not matter for election outcomes.Suppose campaign contributions are an expression of preference, as suggested by the Supreme Court. The way I understand the 1976 decision is that the justices opine that expenditure limits curtail the expression of preferences. But does this opinion imply that the justices assumed that by allowing additional expressions of preferences, one would not expect that removing such limits would result in changes in electoral outcomes? However, this is a matter of interpretation of Supreme Court assumptions used when making a decision and does not take anything away from the advance in our understanding of campaign expenditure limits to which this article makes a valuable contribution. Previous articleNext article DetailsFiguresReferencesCited by Supreme Court Economic Review Volume 272019 Sponsored by the Antonin Scalia Law School, George Mason University Article DOIhttps://doi.org/10.1086/704719HistoryPublished online December 04, 2019 © 2019 by the University of Chicago. All rights reserved.PDF downloadCrossref reports no articles citing this article.
In real life situations, potential offenders may only have a vague idea of their own probability of getting caught and possibly, convicted. As they have beliefs regarding this probability, they may exhibit optimism or pessimism. Thus there exists a discrepancy between the objective expected fine and the subjective expected fine. In this context, we investigate how the fact that the choice whether or not to commit an harmful act is framed as a decision under ambiguity can modify the standard Beckerian results regarding the optimal fine and the optimal resources that should be invested in detection and conviction.
We explore a quasi-natural experiment to assess whether a prosecutor’s political concerns affect rape’s prosecution. In 2006 rape charges were filed against players on Duke University’s lacrosse team. Although innocent, the student-athletes’ prosecution took place during the prosecutor’s primary and general election contests. We argue that this case made salient to voters across the state the concern regarding wrongful prosecution. Following a difference-in-difference strategy, we explore whether rape’s prosecution varies by the prosecutor’s reelection pressures and whether behavior adjusted after the media covered the scandal. We find significant changes in both the case filing levels and the use of jury trials. Fewer rape charges were filed after the Duke lacrosse case and the difference between the case filings during reelection years and nonelection years is muted. There are both fewer cases taken to trial after the scandal and an escalation in this effect during a prosecutor’s reelection. The results strongly suggest that the two important margins, whether to even pursue a conviction and whether to pursue it at trial, are affected by a prosecutor’s retention concerns.
Criminal convictions result in expected losses due to stigmatization. Among other things, the magnitude of these losses depends on the convict’s future expected earnings. People who face larger wage reductions due to convictions suffer more than others from stigmatization. Intuition suggests that this type of unequal stigmatization may lead to over- and underdeterrence problems. This intuitive deduction ignores the possibility that indirect harms from crime may be related to a person’s wage and, therefore, the stigma attached to conviction. I show that if wage cuts reflect employers’ efforts to match the reduction in convicts’ productivity caused by their criminal activity, they cannot cause overdeterrence. However, overdeterrence is observed if stigmatization is caused by simple adverse selection problems. As noted in previous work, overdeterrence can be mitigated by allowing offenders to seal their criminal records; thus, the value of these policies depends on the source of stigmatization.
