Testing Judicial Power

Abstract

The U.S. Supreme Court is traditionally thought to hold little influence over social or political change; however, recent evidence suggests the Court may wield significant power, especially with regard to criminal justice. Most studies evaluate judicial power by examining the effects of individual rulings on the implementation of specific policies, but this approach may overlook the broader impact of courts on society. Instead, I adopt an aggregate approach to test U.S. Supreme Court power. I find that aggregate conservative decision making by the Court is positively associated with long-term shifts in new admissions to U.S. federal prisons. These results suggest the Court possesses significant power to influence important social outcomes, at least in the context of the criminal justice system.

Keywords

judicial power policy impact U.S. supreme court incarceration law and social change

To what extent can the U.S. Supreme Court influence social and political outcomes? Traditionally, the Court is said to wield little power: “The judiciary,” as Alexander Hamilton observed, “has no influence over either the sword or the purse . . . and must ultimately depend upon the aid of the executive arm even for the efficacy of its judgments” (Federalist 78). Most empirical research confirms Hamilton’s expectations, finding that “the Court is quite constrained in its ability to secure social change” (Baum, 2003, p. 177). The Court is said to be ineffectual even in the domain it most directly supervises: the criminal justice system (Horowitz, 1977; Rosenberg, 2008; Wasby, 1976). However, some recent studies challenge this traditional view and suggest the Court possesses substantial influence (Howard & Steigerwalt, 2012; Keck, 2009), particularly with regard to criminal justice policy (Hall, 2011). Hence, considerable disagreement exists over the extent of Supreme Court power.

This debate has important implications for judicial politics, constitutional law, and democratic theory. The Court’s supposed lack of implementation power may compel the justices to strategically alter their decisions based on the preferences of the president (Owens, 2010), Congress (Segal, Westerland, & Lindquist, 2011), or the public (Casillas, Enns, & Wohlfarth, 2011). Moreover, if the justices are unable to influence social outcomes, it is unclear how they might protect the interests of minorities or promote principles of liberty and justice (Dahl, 1957). Alternatively, if the Court can significantly affect social change, it may raise democratic concerns, especially if it is acting as a countermajoritarian institution (Bickel, 1986).

In an effort to assess Supreme Court power, previous research has evaluated the effects of individual rulings on the implementation of specific policies in before-and-after studies (e.g., Hall, 2011; Rosenberg, 2008). These micro-level studies have undoubtedly yielded valuable insights into the effects of particular rulings, but they may overlook the Court’s broader social and political impact. A macro-level analysis of the Court’s influence may provide a more complete understanding of judicial power. Thus, I adopt a macro approach, in which the Court’s power is ascertained by testing the effect of its aggregate decision making on a broad policy output over time. Specifically, I test the Court’s aggregate influence on new admissions to federal prison.

The results of my analysis support my theoretical expectations. I find that conservative Supreme Court decision making is positively associated with long-term shifts in new admissions to federal prison. My analysis offers several important contributions to the study of American politics and policy impact. First, my findings highlight the importance of examining the aggregate effects of policymaking over time in addition to the direct implementation of specific policy enactments. Second, contrary to some accounts, the U.S. Supreme Court appears to exert considerable independent influence over important policy outputs. Finally, the Court’s independent influence in the domain of criminal justice reinforces normative concerns about the potentially countermajoritarian role of the federal courts.

Supreme Court Power and Social Change

A long and prestigious line of scholars and statesmen have argued that the U.S. Supreme Court is severely limited in its ability to alter social outcomes (e.g., Federalist 78, Horowitz, 1977; McCloskey, 2010; Rosenberg, 2008; Sweet, 2010). Possessing “neither FORCE nor WILL, but merely judgment” (Federalist 78), the Court is said to lack the implementation powers necessary to cause meaningful social change. The Court is even said to be ineffectual in the domain of criminal justice policy. For example, Stephen Wasby (1976) finds that for many law enforcement officials, the Court’s rulings simply “did not matter much” (p. 8), and Gerald Rosenberg (2008) concludes that the Warren Court’s criminal rights revolution “failed” because the Court ultimately depends on other actors to implement its rulings (p. 335). However, more recent evidence paints a very different picture of judicial power, in which the Court exerts profound influence over a wide range of social and political outcomes (Hall, 2011; Howard & Steigerwalt, 2012; Keck, 2009; McCann, 1994).

The effectiveness with which Supreme Court policies are implemented . . . depends on several conditions: communication of policies to relevant officials, the motivations of those officials to follow or resist the Court’s policies, the Court’s authority, and the sanctions it can use to deter noncompliance. (Baum, 2001, p. 233)

All of these factors suggest that lower-court judges should be the most faithful adherents to Supreme Court rulings. Legally trained officials are the most capable of understanding the Court’s decisions and the most likely to recognize the Court’s authority. Lower-court judges are also subject to reversal by the High Court and relatively insulated from other political pressures (Baum, 2001, p. 235, 238, 239). Thus, it is unsurprising that these lower courts overwhelmingly (though imperfectly) adhere to Supreme Court policies (Gruhl, 1980; Hoekstra, 2005; Songer, Segal, & Cameron, 1994; Westerland, Segal, Epstein, Cameron, & Comparato, 2010).

In many policy domains, the Supreme Court’s control over lower courts is insufficient to secure policy implementation. Instead, the Court often requires the cooperation of non-judicial officials, who do not carry out the Court’s policies as faithfully as judges (Baum, 2001; McGuire, 2009; Rosenberg, 2008; Sweet, 2010). However, lower-court judges enjoy unique powers with regard to implementing the High Court’s criminal justice rulings. These judges can often prompt implementation by simply refusing to convict defendants unless law enforcement officials comply with the Court’s policies. As a result of this institutional leverage, the Supreme Court’s power is particularly potent in the domain of criminal justice (Hall, 2011; see also Hall, 2014).

Most judicial impact studies evaluate the Supreme Court’s power at the micro level by examining the effects of particular rulings on specific behavior outcomes (see Canon & Johnson, 1998). For example, both Rosenberg (2008) and Hall (2011) examine the effects of the Court’s ruling in Miranda v. Arizona on the behavior of police reading Miranda warnings. These before-and-after studies offer simple and intuitive results; however, they may overlook the full extent of Supreme Court power. In a common law judicial system, courts do not typically pronounce major policy shifts in individual rulings; instead, case law develops gradually as judges make policy decisions on a case-by-case basis (Landes & Posner, 1979; Leoni, 1961; Ponzetto & Fernandez, 2008). Consequently, studies of judicial power that test the effects of individual rulings may fail to notice the aggregate impact of the Court’s decision making over time.

To overcome this limitation, I use a macro approach to evaluate Supreme Court power. This approach offers several methodological advantages. First, this strategy accounts for the fact that widespread social phenomena are probably influenced by numerous Court rulings as the justices decide a series of specific cases. Second, rather than evaluating the effects of a single ruling at a specific point in time, the aggregate approach facilitates the use of sophisticated statistical methods to examine both short- and long-term effects of the Court’s decision making. Third, this approach accounts for the possibility that the Court’s influence is not limited to its actual rulings; instead, the Court may indirectly influence outcomes in a variety of ways. For example, if the Supreme Court is especially conservative during a particular time period, lower-court judges, litigants, and public officials may anticipate conservative rulings from the Court and respond accordingly. In sum, we should not expect the Court’s influence to be concentrated at one particular moment in time when it issues a specific ruling or at a particular lag as the decision takes effect. Instead, the Court’s aggregate decision making may have a myriad of effects across time.

I adopt this macro approach to test the Supreme Court’s aggregate influence on the rate of new admissions to federal prison. This policy output is a particularly appropriate place to look for the Court’s influence given its supervisory role over the federal judiciary. The dramatic expansion of incarceration in the United States over the last few decades has produced numerous social (Mauer, 2006; Pager, 2007; Walmsley, 2006; Western, 2006), economic (Kirchhoff, 2010; Schmitt, Warner, & Gupta, 2010), and political (Burch, 2009; Gottschalk, 2008; Manza & Uggen, 2004; Simon, 2007; Uggen, Manza, & Thompson, 2006; Weaver & Lerman, 2010) consequences; yet, scholars continue to debate its causes. Although no one Supreme Court decision may produce a noticeable shock in the incarceration rate, I argue that the Court influences long-term shifts in incarceration through its aggregate decision making.

The Causes and Consequences of Incarceration

As of 2010, the United States imprisoned 1 out of every 200 adults in the country (Guerino, Harrison, & Sabol, 2011). The United States incarcerates a greater proportion of its population than any other nation in the world, topping Russia, Rwanda, and Cuba by substantial margins (Walmsley, 2006). Not only is the United States prison population exceptionally large, but it has also been steadily increasing for decades. As recently as 1980, the incarceration rate was roughly one fourth what it is today.

The consequences of this drastic social change are increasingly evident. A significant portion of African American males in the United States are disenfranchised as a result of felony convictions (Manza & Uggen, 2004; Mauer, 2006). After serving their sentences, convicts face serious barriers to obtaining legitimate employment and severely dampened economic prospects, which in turn contribute to the cycle of poverty and crime that led them to prison in the first place (Pager, 2007; Western, 2006). Incarceration also disrupts family life; for example, 1 out of every 10 young Black children had a father behind bars by the end of the 1990s (Western, 2006). Society also bears substantial costs as a result of rising incarceration rates. The emphasis on penal policies means that displaced criminal justice resources must be diverted from other programs (Mauer, 2006; Schmitt et al., 2010). Weaver and Lerman (2010) find that personal interactions with the criminal justice system also lead to decreased democratic participation and inspire negative orientations toward government. These effects may have far-reaching downstream consequences for the social and political health of a society.

The dramatic increase in the U.S. incarceration rate has prompted many scholars to search for causal factors behind this important social and political transformation. This search has produced several alternative explanatory theories. Interestingly, most studies conclude that the rising prison population is not the result of increased crime. In fact, many studies find an inverse relationship between crime and incarceration (Davey, 1998; Enns, 2014; Western, 2006; Zimring & Hawkins, 1991). This counter-intuitive finding should not necessarily be surprising given that the radical increase in the incarceration rate coincided with a significant drop in the crime rate during the 1990s (see, for example, Blumstein & Rosenfeld, 1998; Blumstein & Wallman, 2000; Donohue, 1998; Kelling & Bratton, 1998). Accordingly, “whatever pressures federal justice agencies may respond to, crime is probably not one of them” (Nicholson-Crotty & Meier, 2003, p. 125).

Instead, many scholars point to political factors as driving the incarceration rate.¹ For example, increased incarceration may be a strategy used by “tough-on-crime” politicians to curry electoral favor, especially during election years (Davey, 1998; Jacobs & Carmichael, 2001; Jacobs & Helms, 1996; Yates & Fording, 2005). In fact, even elected state judges tend to become more punitive as reelection contests approach (Huber & Gordon, 2004). Some studies have also found a partisan effect on incarceration: as Republican Party power increases in state and federal electoral institutions, so too does incarceration (Jacobs & Carmichael, 2001; Jacobs & Helms, 1996; Smith, 2004). Others cite specific policy agendas, such as the “war on drugs,” limitations on parole, and the establishment of sentencing guidelines and mandatory minimums, as potential explanations for the increase in imprisonment (Mauer, 2006; Nicholson-Crotty & Meier, 2003). Accordingly, the preferences of elected officials, including presidents (Jacobs & Carmichael, 2001), governors (Davey, 1998), and state legislators (Smith, 2004), have been found to influence the incarceration rate. More generally, increased attention to crime by policymakers or the public may also influence incarceration (Enns, 2014; Nicholson-Crotty & Meier, 2003; Nicholson-Crotty, Peterson, & Ramirez, 2009). However, very few studies consider the potential influence of courts on the incarceration rate (cf. Simon, 2007, 2013).²

The Supreme Court and Federal Incarceration

There are several reasons to suspect that courts generally, and the U.S. Supreme Court in particular, may influence federal incarceration. The Supreme Court ultimately resolves a wide range of questions related to criminal justice policy, including the interpretation of common law principles, federal statutes, and constitutional rights. By expanding or contracting the substantive protections afforded to criminal suspects and defendants, the justices may be able to significantly alter the rate at which Americans are put behind bars. Yet, despite the intuitive link between the Court and the criminal justice system, no previous study has considered Supreme Court rulings as one of the driving forces behind the incarceration rate.

The Supreme Court’s history is replete with decisions that may have affected federal incarceration. During the 1960s, the Warren Court engaged in a criminal rights “revolution.” As McCloskey (2010) notes, “[t]he Warren Court undoubtedly read the Constitution more generously than did prior Courts in terms of the formal legal rights offered criminal defendants” (p. 165). Although its most famous decisions involved state law, the Court also expanded the rights of federal criminal defendants related to searches and seizures (Rios v. U.S., 1960), self-incrimination (Marchetti v. U.S., 1968), and wiretapping (Katz v. U.S., 1967). Many scholars, politicians, and activists contend that expanded criminal rights detracted from the ability of police investigators to solve crimes and prosecutors to obtain convictions (e.g., Canon, 1974; Cassell & Fowles, 1998; Donohue, 1998; Nagel, 1965). Consequently, the Warren Court’s criminal rights “revolution” may have substantially limited federal incarceration.

Later decisions may have increased the incarceration rate. Beginning in the 1970s, the Supreme Court began to move criminal jurisprudence in a decidedly punitive direction (Keck, 2004, Chapters 4 and 5). Through his appointments of four new justices, Richard Nixon actively attempted to reshape the Court’s policies to advance his “law and order” agenda (McMahon, 2011), and Ronald Reagan continued this tradition during the 1980s (Clayton & Pickerill, 2006). The justices they appointed

backtracked on legal rights accorded criminal defendants . . . , “distinguished” the facts of newer cases [and] allowed warrantless searches ordinarily disallowed by the exclusionary rule if the police in “good faith” believed they were legal . . . (McCloskey, 2010, p. 166)

In short, these Courts made it easier to convict criminal suspects. These rulings may have contributed to the rising incarceration rate as criminal defendants found themselves with fewer legal protections and prosecutors enjoyed greater chances of obtaining convictions.

How might U.S. Supreme Court decisions such as these affect the federal incarceration rate? The most likely causal mechanism between Court rulings and incarceration is the Court’s direct and indirect influence over other actors in the criminal justice system. Supreme Court decisions initiate a series of reactions from lower-court judges, prosecutors, attorneys, and police, which in turn shape the incarceration rate.

First, and most directly, the Court influences decision making by lower federal courts. Studies of judicial compliance suggest that lower courts generally adhere to Supreme Court precedent (Brent, 1999; Gruhl, 1980; Songer et al., 1994; Songer & Sheehan, 1990); in fact, court of appeals judges actually anticipate Supreme Court preferences when making decisions (Westerland et al., 2010), and district court judges anticipate the behavior of court of appeals judges (Randazzo, 2008). Of course, lower court compliance is not perfect; judges sometimes exercise considerable discretion when making decisions (Baum, 1978; Scott, 2006). However, defying the Supreme Court tends to be the exception rather than the rule, and recent studies have found that the Court’s “hierarchical control appears strong and effective” (Westerland et al., 2010, p. 891). If district courts respond to Supreme Court decisions, the High Court’s rulings should directly influence the frequency with which district courts sentence criminal defendants to federal prison.

Second, the changing behavior of lower federal courts alters the behavior of prosecutors and defense attorneys. These actors strategically anticipate the probability of success when deciding whether to prosecute a case, appeal a decision, or plea bargain (Albonetti, 1987; Lederman, 1999; Taha, 2010; Wedeking, 2010). Accordingly, as the Supreme Court expands criminal rights and lower courts comply, prosecutors become less likely to initiate a prosecution and less likely to appeal a loss. Similarly, defense attorneys may become more likely to appeal a loss. The contraction of criminal rights likely produces the opposite effects.

Finally, as the behavior of lower-court judges and federal prosecutors changes, federal law enforcement officials may adjust their behavior to increase the odds of conviction. For example, studies of Supreme Court decision making with regard to the exclusionary rule, Miranda rights, and warrantless eavesdropping eventually produced significant changes in police behavior, including arrests and clearance rates (Hall, 2011). Thus, Supreme Court rulings might also indirectly influence incarceration by altering the behavior of law enforcement officials.

To better understand the causal mechanism linking Supreme Court decisions and incarceration, consider the effects of a hypothetical ruling that a certain type of evidence is inadmissible in criminal trials. What consequences should this ruling have for new admissions to federal prison? First, convictions that hinge on the admissibility of such evidence should be reversed at the appellate level and pending trials that depend on such evidence should result in acquittal. Second, as the probability of conviction in cases that depend on such evidence decreases, prosecutors should initiate fewer prosecutions. And finally, as prosecutors change their standards for when they will and will not prosecute, law enforcement officials should change their decisions about who to arrest in the first place. Law enforcement may also find it harder to make arrests if they comply with the new constitutional rule. A later ruling by the Court that this type of evidence is admissible should reverse this sequence of behavior. Note that any one of these subsequent patterns could substantially influence the incarceration rate. Consequently, through its influence over other actors in the criminal justice system, the Supreme Court should have a significant impact on incarceration.

Of course, numerous other actors may also influence the incarceration rate. Police, prosecutors, and lower-court judges undoubtedly wield significant discretion in exercising their duties, and this discretion may have significant effects on incarceration. The important theoretical point is not that the Supreme Court is the exclusive policymaker with regard to incarceration, but rather that it is an important policymaker in this domain because its decisions can partially shape the behavior of these other actors. Without question, not every relevant actor considers every Court ruling each time they make a consequential decision. But if some of these actors occasionally make subtle behavior changes based on the shifting legal landscape, these changes should have a substantial aggregate effect on incarceration.

Given this theoretical link between Court decisions and incarceration, I argue that Supreme Court decision making influences the rate of new admissions to federal prison. However, I expect this causal chain to unfold rather slowly as Supreme Court decisions influence the behavior of lower-court judges, prosecutors, defense attorneys, and law enforcement. The Supreme Court Database defines liberal decisions in criminal cases as “pro-person accused or convicted of a crime, or denied a jury trial” and conservative decisions as the reverse.³ Therefore, by definition, conservative criminal decisions should increase the likelihood of criminal convictions. Accordingly, I hypothesize that an increase in conservative decision making by the Supreme Court leads to a long-term increase in the federal incarceration rate.

Data and Analysis

Federal Incarceration

My goal is to test the influence of the Supreme Court’s aggregate decision making on federal incarceration. I begin by considering the annual rate (per 10 million people) of individuals convicted and sentenced to prison terms in federal courts from 1950 through 2008.⁴ My selection of this dependent variable is motivated by two considerations. First, the U.S. Supreme Court sits at the apex of the federal judiciary; accordingly, it should have more direct influence over federal incarceration than state incarceration. Of course, the Court may also affect state incarceration through its interpretation of the U.S. Constitution as applied to state law. However, the U.S. Supreme Court’s influence on these states may be mediated through the various state courts of last resort. At the very least, the behavior of these state courts might influence state incarceration. Because comprehensive data on decision making in these courts is limited to the years 1995-1998, an appropriate analysis of state incarceration rates would be exceedingly difficult.⁵ Accordingly, my analysis will only address the U.S. Supreme Court’s influence on federal incarceration.

Second, analyzing new commitments is appropriate because changes in judicial policy should primarily affect new conviction and sentencing practices rather than the existing prison population as a whole.⁶ In addition, the increase in incarceration over the last few decades has been primarily driven by new admissions rather than an increase in the average sentence (Wacquant, 2010). This methodological choice is also necessary because total state and federal prison population statistics were always combined prior to 1980.

Supreme Court Decision Making

I measure the Court’s decision making as the percentage of cases with a conservative outcome out of all decisions that involve federal incarceration and reverse a lower court in each year (% Conservative Reversals). The percentage of conservative (or liberal) reversals is a commonly used measure of judicial policy output. Prior research demonstrates that “reversals provide the most theoretically and empirically valid measures of the ideological content of the Court’s decisions” (Casillas et al., 2011, p. 76; see McGuire & Stimson, 2004; McGuire, Vanberg, Smith, & Caldeira, 2009). The Court generally moves the ideological direction of policy by reversing the decisions of lower courts, whereas affirmances are usually used to limit ideological change as litigants ask the justices to move policy even further in the direction they have been moving.⁷ I identify cases that involve federal incarceration as those that (a) involve a criminal or due process issue, (b) involve potential imprisonment, and (c) originated in a federal district court.⁸

Figure 1 presents the federal incarceration rate and incarceration-related reversals over time. Figure 1a reports the total number of incarceration-related reversals and the number of reversals with a conservative outcome. Figure 1b reports the standardized incarceration rate and the standardized percentage of conservative reversals. Figure 1c reports the standardized incarceration rate and the standardized net conservative reversals, that is, the number of conservative reversals minus the number of liberal reversals issued by the Court in each year. Finally, given that Supreme Court rulings appear to impact incarceration slowly over time, Figure 1d reports the standardized incarceration rate and standardized cumulative conservative reversals, that is, the accumulated net conservative reversals over time. As these figures illustrate, conservative shifts in Supreme Court decision making tend to precede increases in the incarceration rate but only after a fairly long lag.

Crime

I also include several control variables to account for other possible influences on the incarceration rate. I utilize two variables to control for the crime rate. The first is an index based on the annual rate of murder, forcible rape, robbery, aggravated assault, burglary, and motor vehicle theft.⁹ Previous research has shown that these variables share a great deal of over-time variation and a principal components analysis shows that the six crime rates load onto a single factor.¹⁰ That factor serves as an estimate of the over-time violent and property Crime Rate.

The second control variable for crime is a measure of illegal Drug Use. Drug-related offenses have become increasingly prevalent over the last several decades, and actually became the modal category of federal commitments in the 1980s. Unfortunately, direct measures of drug use are not available for the time period of my study. The best indirect measure of over-time drug use is the annual drug mortality rate (Paulozzi & Xi, 2008; Samkoff & Baker, 1982), that is, the rate of drug-induced deaths. The use of this proxy assumes that an increase in drug-induced deaths coincides with an increase in drug use. Accordingly, I use this proxy to control for drug use.

Non-Judicial Policymaking

Next, I include four variables to control for the possible influence of non-judicial policymakers. First, I control for the composition of federal electoral institutions. Previous studies have shown that increased Republican Party power in government leads to increases in the incarceration rate (Jacobs & Carmichael, 2001; Jacobs & Helms, 1996; Smith, 2004). My measure of Republican Party Strength is based on whether the president is a Republican or a Democrat and the proportion of Republicans in Congress. The measure codes Republican presidents as 1 and Democratic presidents as 0, and then adds this number to the proportion of Republicans (among Republicans and Democrats) in the U.S. House of Representatives and the proportion of Republicans (among Republicans and Democrats) in the U.S. Senate. While this variable could theoretically range from 0 to 3, the lowest value is .64 (in 1964 and 1965) and the highest value is 2.09 (in 2005 and 2006). In the supporting information, I run robustness checks with separate measures of partisanship for the president, House, and Senate. I also run robustness checks with ideological measures of the median House member, median Senator, and president to account for the possible influence of ideology apart from partisanship. All of my results are robust to these alternative specifications.

Second, I include a measure of federal laws related to incarceration. I begin with a list of every public law enacted by Congress from 1947 to 2010 that is coded as a “Law, Crime, and Family Issue” by the Policy Agendas Project.¹¹ I exclude public laws that could not affect the incarceration rate.¹² I then supplement this list with significant public laws related to drug enforcement.¹³ I code each of these public laws as either punitive (enhancing penalties) or liberalizing (reducing penalties). Punitive legislation is counted +1 and liberalizing legislation is counted −1. I then sum punitive minus liberalizing legislation for each year from 1947 to 2010 to create an annual, aggregate measure of Punitive Laws.

Third, I control for federal Criminal Justice Spending (in billions of dollars) using the annual budget authority devoted to “Justice Administration” as identified by the Policy Agendas Project.¹⁴ These data are adjusted for inflation and revised to be consistent across time using Office of Management and Budget functions and subfunctions. If the federal government devotes more resources to incarcerating criminals during certain periods, it should be reflected in this measure.

Finally, the incarceration rate may have been particularly influenced by changes to federal law regarding drug use. The most profound change in this regard occurred in 1970 with the passage of the Controlled Substances Act, which, among other things, repealed mandatory minimums for possession and trafficking of various drugs. Another important change occurred with the Anti-Drug Abuse Act of 1986, which reinstated mandatory minimums. Accordingly, I include a dichotomous indicator variable, Mandatory Minimums, taking on the value 1 for years when mandatory minimums were in place, and 0 otherwise.¹⁵

Salience

Last, the incarceration rate may be indirectly influenced by the salience of criminal justice issues among policymakers or the public. Accordingly, I include two variables to control for salience. First, I control for the salience of criminal issues in Congress using the number of Congressional Hearings related to “Law, Crime, and Family” issues, as identified by the Policy Agendas Project.¹⁶ If increased congressional attention leads to higher incarceration rates, then Congressional Hearings should be positively associated with incarceration. Second, I control for Public Attention to criminal justice issues. Specifically, I include the percentage of respondents indicating “Law, Crime, and Family” issues as the nation’s most important problem in Gallup polls, aggregated at the annual level.¹⁷ If Public Attention prompts increased incarceration, this variable should also be positively associated with incarceration.

Additional Controls

In the supporting information I run robustness checks with additional control variables, including the public’s policy mood and economic inequality. All of the findings reported below are robust to the inclusion of all of these control variables, as well as other dichotomous indicator variables for specific policy enactments (e.g., The Anti-Terrorism and Death Penalty Act of 1996).¹⁸

Model Estimation

I utilize an error correction model (ECM) to test my hypothesis (De Boef & Keele, 2008).¹⁹ One way to express a single-equation ECM is as follows (excluding a constant term for the sake of simplicity):

Δ Y_{t} = α_{1} Y_{t - 1} + β_{1} Δ X_{t} + β_{2} X_{t - 1} + ε_{t} .

The key feature of the ECM is that for each independent variable X there are up to two parameter estimates: β₁ for the differenced variable and β₂ for the lagged variable. This modeling strategy allows me to differentiate between short- and long-term effects. In this simple bivariate example, β₁ provides an estimate of the immediate (yet permanent) change in the dependent variable produced by a shock to the independent variable. β₂ can be used to calculate the slightly more complicated long-term impact when combined with α₁, called the error correction rate. The “long run multiplier” (LRM) is calculated by dividing β₂ by α₁, which reflects the total expected change in the dependent variable for each unit change in the independent variable (De Boef & Keele, 2008). Accordingly, this modeling strategy allows me to measure both short- and long-term effects of Supreme Court decision making on new admissions to federal prison. The ability to test long-term effects is especially important in this context because I expect the Court’s decisions to have a delayed effect as judges, prosecutors, defense attorneys, and law enforcement officials incorporate new legal rules into their behavior.

Results

The results of the multivariate analyses are reported in Table 1. First, I present a parsimonious model to demonstrate that my results are not the result of over-fitting the data. I then present a model with the control variables. Both of the models support my theoretical expectation: conservative reversals by the U.S. Supreme Court in federal criminal justice rulings are positively and significantly associated with long-term increases in the federal incarceration rate. The long-term effect of Supreme Court decision making is more than twice as large after including the control variables. As expected, the results offer little evidence that Court decisions immediately affect incarceration; the short-term effect of % Conservative Reversals does not reach conventional levels of statistical significance in either model. These findings suggest the Court affects the incarceration rate over the long term as its decisions gradually influence the behavior of other actors in the criminal justice system.

Table 1.

The Influence of Supreme Court Decision Making on the Federal Incarceration Rate.

	Mobel 1	Mobel 2
	β (SE)	β (SE)
Short-term effects
Δ % Conservative Reversals	0.32 (0.46)	0.76 (0.53)
Δ Crime Rate		−57.41 (37.51)
Δ Drug Use		−3.31 (10.03)
Δ Republican Party Strength		21.45 (29.48)
Δ Punitive Laws		4.63 (6.70)
Δ Criminal Justice Spending		−2.54 (5.77)
Δ Mandatory Minimums		61.94 (66.81)
Δ Congressional Hearings		−0.49 (0.60)
Δ Public Attention		−1.74 (2.27)
Long-term effects
% Conservative Reversals_{t − 1}	1.00* (0.41)	2.35* (0.75)
Crime Rate_{t − 1}		−3.58 (11.39)
Drug Use_{t − 1}		5.15 (7.73)
Republican Party Strength_{t − 1}		49.58 (28.03)
Punitive Laws_{t − 1}		11.67 (11.42)
Criminal Justice Spending_{t − 1}		8.76* (2.89)
Mandatory Minimums_{t − 1}		129.60* (44.94)
Congressional Hearings_{t − 1}		−1.49 (0.88)
Public Attention_{t − 1}		1.56 (1.85)
Error correction rate
Incarceration_{t − 1}	0.04 (0.02)	−0.26* (0.09)
Constant	−71.70* (32.29)	−61.94 (77.52)
n	58	58
R ²	.16	.57

Note. Table reports error correction models of changes in the federal incarceration rate.

p < .05 (two-tailed test).

Most of the control variables behave as expected in the second model. The long-term effects of Criminal Justice Spending and Mandatory Minimums are both positive and statistically significant. Both the short- and long-run effects of Republican Party Strength and Punitive Laws are positive, but none reach conventional levels of statistical significance. Together, these results reinforce the conclusion that the incarceration rate responds to political factors, especially the enactment of punitive public policies such as mandatory minimums.

Neither the violent and property Crime Rate, nor Drug Use, have significant short- or long-term associations with incarceration. In fact, the coefficients for both short- and long-term effects of the Crime Rate, as well as the short-term effect of Drug Use, are all signed in the wrong direction. These results are consistent with several other studies that find a nonexistent or inverse relationship between crime and incarceration (Davey, 1998; Enns, 2014; Nicholson-Crotty & Meier, 2003; Western, 2006; Zimring & Hawkins, 1991). Like these other studies, I find no evidence that crime drives the federal incarceration rate.²⁰

Contrary to my expectations and previous studies, I find no evidence that salience of criminal justice issues affects incarceration. Neither Congressional Hearings nor Public Attention has significant short- or long-term effects on incarceration, and several of the coefficients for these effects are signed in the wrong direction. If congressional or public attention to criminal justice issues does influence the incarceration rate, this effect is most likely captured by the non-judicial policy variables in my model.

The Court’s influence on incarceration is substantively, as well as statistically, significant. The total effect of the Court’s decision making on new admissions can be calculated using the LRM. The LRM represents the total effect of a change in the predictor variable in 1 year as it continues to influence the dependent variable at a decaying rate across time. Figure 2 reports the LRM for each variable with a significant long-term effect in the second model of Table 1.²¹ As a point of reference, during the period of my analysis the rate of new admissions to federal prison per 10 million people ranges from a low of 580.02 in 1980 to a high of 2,294.51 in 2008 with a standard deviation of 502.72.

As reported in Figure 2, a one standard deviation increase in % Conservative Reversals is associated with a total long-term increase of 279.26 new admissions per 10 million people. In other words, a one standard deviation shift in the Court’s decision making is associated with about a one-half standard deviation shift in new federal commitments. Based on the current U.S. population, these findings suggest that a typical increase in conservative decision making by the Supreme Court in cases involving federal incarceration would be associated with an additional 8,766 new admissions to federal prison over time. Nonetheless, the effects of Supreme Court decision making are substantially smaller than the effects of spending on criminal justice or the enactment of mandatory minimum sentences.

The error correction rates in Table 1 indicate the speed at which these long-term effects take place. For example, the error correction rate of −0.26 in the second model in Table 1 indicates that 26% of the total long-term impact of a one standard deviation increase in conservative decision making by the Court (279.26) influences incarceration at time t + 1 (72.61), an additional 41% of the remaining effect takes place at time t + 2 (53.73), and so on until the total long-term effect is distributed. Therefore, these results indicate that the Court’s long-term effect on incarceration manifests itself rather slowly; it takes more than a decade for 95% of the total long-run impact of decision making in a particular year to be realized in the incarceration rate. This delay is consistent with my theory that Supreme Court decisions influence the incarceration rate by gradually shaping the behavior of other actors in the criminal justice system.

Finally, I perform Granger “causality” tests based on vector autoregressive models. Granger tests do not prove a causal relationship; the definitive identification of a causal effect is extremely difficult, particularly with observational data (Gerber & Green, 2004; Morgan & Winship, 2007). However, a Granger test can reinforce the plausibility of a causal relationship between two longitudinal variables by testing the temporal ordering of changes in those variables. The intuition behind a Granger test is fairly simple: If changes in X cause changes in Y, then changes in X should precede changes in Y. Such a pattern would suggest that the temporal ordering of changes fits with the causal narrative (Baumgartner & Jones, 1993). Consistent with my expectations, changes in % Conservative Reversals “Granger cause” changes in the federal incarceration rate (p = .037). Furthermore, the results of the Granger test do not suggest reverse causality, that is, changes in the incarceration rate do not “Granger cause” changes in Conservative Reversals (p = .612).²²

Taken together, these results support my theory that U.S. Supreme Court decision making influences the federal incarceration rate. Aggregate conservative decision making by the Court in incarceration-related cases is associated with long-term increases in the federal incarceration rate, and the temporal pattern of these effects is consistent with a causal narrative. Furthermore, the magnitude of the Court’s influence is considerable. A typical conservative shift in Supreme Court decision making has more than half the effect of a typical increase in federal spending on criminal justice.

Conclusion

Numerous scholars have studied possible explanations for the increasing severity of American penal policies, including public attitudes, electoral politics, and socio-economic factors. However, none of these previous studies have considered the influence of the U.S. Supreme Court. Yet, the rise in the incarceration rate over the last few decades has coincided with increasing conservatism among those who are ultimately responsible for supervising the federal judiciary. My findings suggest that changes in the Court’s decision making may be partly responsible for the increase in federal incarceration.

I find that the U.S. Supreme Court influences the rate of new commitments to federal prison. Increased conservative decision making by the Supreme Court leads to a substantial long-term increase in the incarceration rate. These findings are robust to a wide range of model specifications and control variables. However, this study also suffers from a significant limitation: I have examined the U.S. Supreme Court’s effect on federal incarceration only. The vast majority of inmates in the United States are held in state prisons, and this study does not examine the Court’s influence on that population. An examination of state incarceration rates is a promising avenue for future research. In addition, future studies should explore the causal mechanisms that link judicial decisions to incarceration.

The present study offers several important contributions to our understanding of American politics and policy impact. First, my findings suggest that scholars should consider policy impact at the macro level. Micro-level studies offer valuable insight into the concrete realization of particular policy enactments; however, these studies may fail to capture the total influence of numerous policymaking decisions over time. In contrast, a macro approach facilitates an understanding of policymakers’ aggregate influence over broad social and political outcomes. The ability of policymakers to broadly shape public policy outputs in this manner is essential for a properly functioning political system. Accordingly, researchers should consider the myriad of ways policymakers may influence social and political outcomes through aggregate decision making.

Second, this study contributes to a growing literature that contends the U.S. Supreme Court has significant influence over social and political outcomes (Hall, 2011; Howard & Steigerwalt, 2012; Keck, 2009). Not only do individual Court rulings prompt the implementation of specific policies, aggregate decision making also shapes broad policy outputs over time. The Court appears to have significantly altered the nature of the federal penal system over the last half-century and, in so doing, indirectly influenced the subsequent social, economic, and political changes. However, scholars should be cautious in applying these conclusions to other policy domains; the Court may be particularly powerful in the realm of criminal justice (Hall, 2011).

Finally, my findings raise normative concerns about the Supreme Court’s broader role in policymaking and its potentially countermajoritarian influence in American politics. The Court appears to exercise significant independent influence over the most basic output of the federal criminal justice system. Consequently, these unelected judges may be able to thwart popular will by imposing their own policy preferences (Bickel, 1986). This concern is especially heightened given recent findings that the Court does not tend to follow public opinion in criminal cases because they do not fear nonimplementation of their decisions (Hall, 2014). Taken together, these studies suggest the U.S. Supreme Court may indeed play a truly countermajoritarian role in the American political system. At the very least, the Court appears to exercise significant influence over some important policy outcomes.

Footnotes

Acknowledgements

Special thanks to Peter Enns, Gregory Huber, Amber Knight, Jason Windett, Christopher Witko, and Brittany Solomon for their thoughtful comments.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biography

Matthew E.K. Hall is an assistant professor of Political Science and Law at the University of Notre Dame. His research focuses on American political instititutions with a special emaphsis on judicial power and independenance. He is the author of The Nature of Supreme Court Power (Cambridge University Press).

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