UNIVERSITY OF CINCINNATI

Date:

I, ,

hereby submit this original work as part of the requirements for the degree of:

in

It is entitled:

Student Signature:

This work and its defense approved by:

Committee Chair:

8/18/2010 996

16-Aug-2010

Andrew James Myer

Doctor of Philosophy

Criminal Justice

Hurricane Katrina, Citizen Displacement, and Social Control: A Test of the

Threat and Benign Neglect Hypotheses and an Investigation of the

Crime-Arrest Relationship

Mitchell Chamlin, PhDMitchell Chamlin, PhD

Andrew James Myer

Hurricane Katrina, Citizen Displacement, and Social Control: A Test of the Threat and BenignNeglect Hypotheses and an Investigation of the Crime-Arrest Relationship

A dissertation submitted to the

Graduate School

of the University of Cincinnati

in partial fulfillment of the

requirements for the degree of

Doctor of Philosophy

In the School of Criminal Justiceof the College of Education, Criminal Justice, and Human Services

by

Andrew J. Myer

B.A., Saint John’s University, 2004M.S., University of Cincinnati, 2005

Dissertation Committee: Mitchell B. Chamlin, Ph.D. (Chair)Francis T. Cullen, Ph.D.James Frank, Ph.D.William Alex Pridemore, Ph.D.

ii

ABSTRACT

A guiding theory often used by criminologist to examine the application of social control

is the conflict perspective. This perspective asserts that social control is used as a tool to protect

elite segments of society. The conflict theory posits an increase in social control when elite

groups are threatened, the threat hypothesis. While the benign neglect hypothesis predicts a

decrease in crime control when the population under threat is a non-elite population. One of the

main concerns of this paper is to address limitations in the oft studied threat hypothesis and the

understudied benign neglect hypothesis.

Two limitations of previous studies of conflict hypotheses are (1) lack of a direct

measure of threat and (2) aggregation bias. This research will employ a more direct measure of a

threatening event: the displacement of citizens to Houston, Texas, by Hurricane Katrina, moving

beyond the reliance between the correlation of structural antecedents and social control. This

research will also investigate aggregation bias by evaluating conflict hypotheses at a level below

the city—the traditional unit of analysis of past research. To this end, this research will use time

series analysis to directly account for social control pre- and post-displacement to determine if

any changes in the administration of social control occurred as a result of the displacement.

Finally, this paper also attempts to examine the role that social context plays in the

reciprocal relationship between crimes and arrests. Past research on the crime arrest relationship

has been mixed. Cross sectional designs often corroborate predictions of economic theory, while

the more rigorous time series designs fail to provide similar results. Recent research suggests

that the social context of an area may exert an influence on this relationship. To this end, this

investigation will employ bivariate time series techniques to examine the role that social context

plays in the reciprocal relationship between crimes and arrests.

iii

ACKNOWLEDGEMENTS

There are many people who deserve acknowledgement for their contributions in my

completion of this dissertation and my doctoral degree. Many professors in the department of

criminal justice influenced me greatly. Dr. Ed Latessa was instrumental in helping me feed my

family, as well as feed my curiosity about practical applications in correctional settings. I

learned a great deal from Dr. Smith on teaching and applying practical applications. I also wish

to thank Dr. Jim Frank for not only serving on my committee, but also for the great

conversations we had (some while golfing). I am in debt to Dr. Frank Cullen for showing me

how to frame probing questions in an interesting and academic fashion, as well as serving on my

committee. I am also grateful for the in-depth and thought-provoking comments to my

dissertation provided by Dr. Bill Pridemore. I also wish to thank others for all of their

contributions to my graduation: Dr. John Wooldredge, Dr. John Eck, Dr. Bonnie Fisher, Dr. Matt

Makarios, Dr. Ben Steiner, John Schwartz, Janice Miller, and Jean Gary.

Dr. Mitch Chamlin (maybe I will finally be able to call you Mitch now?) could not have

been a bigger influence on me. I owe a great deal to my success because of what you taught me,

the conversations we had, and the work we have done together. I truly cannot express my

gratitude for you taking the time to guide me and not just show me the way. Thanks for being a

great mentor and a wonderful friend.

My mom and dad also deserve credit for my accomplishment. I would not be asking all

of these questions if they had not fueled my curiosity and raised me to not fear asking questions.

Thanks for all you have done for me.

iv

To my wife, Leslie: I could not and would not be where I am if it wasn’t for you. Thanks

for your support, your kindness, and warmth. Thanks for your generosity and sacrifice. I love

you.

To my son, Benet: I love you. What follows is proof that you can accomplish anything,

as long as you listen to your mother.

v

TABLE OF CONTENTS

Abstract…………..………………………………………………………………………..... iAcknowledgements…………………………………………………………………………. iiiTable of Contents………..………………………………………………………………….. ivList of Tables…………..…………………………………………………………………… vi

CHAPTER ONE: THE ISSUES OF DIRECT MEASUREMENT, AGGREGATION BIAS, AND SOCIAL CONTEXT UNDER THE CONFLICT PERSPECTIVE

Introduction……………...………………………………………………………………….. 1The Present Research…………..…………………………………………………………… 7

CHAPTER TWO: A CRITICAL REVIEW OF THE CONFLICT PERSPECTIVE

Introduction………..……………………………………………………………………….. 9The Conflict Perspective………..………………………………………………………….. 9

The Threat and Benign Neglect Hypotheses…….……………………………………… 12Previous Research on the Threat and Benign Neglect Hypotheses……………………….. 14

Summary..………………………………………………………………………………... 20Methodological Issues……...………………………………………………………………. 20

Indirect Measurement….…............................................................................................... 20Aggregation Bias………..……..………………………………………………………… 22

The Current Study…………..……………………………………………………………… 24

CHAPTER 3: SOCIAL CONTEXT AND THE CRIME-ARREST RELATIONSHIP: EVALUATING THE PREDICTIONS OF THE CONFLICT PERSPECTIVE

Introduction……………………………………………………………………………….. 26The Causal Mechanisms Underlying the Crime-Arrest Relationship…………………….. 27A Review of the Crime-Arrest Literature……………….…………………………………. 31Research on the Tipping Effect……………….…………………………………………… 37The Current Study………………..………………………………………………………… 38

CHAPTER 4: METHODS

Introduction…………..…………………………………………………………………….. 40Research Design………………..…………………………………………………………... 40

Hurricane Katrina as Threat……………..………………………………………………. 42Data…………..……………………………………………………………………………... 44

Crimes………..…………………………………………………………………………... 45Arrests…………..………………………………………………………………………... 47Police Divisions………..………………………………………………………………… 51

Analytical Method…………..……………………………………………………………… 58Univariate Estimation………..…………………………………………………………... 59Interrupted Time Series……………………………………..…………………………… 62

vi

Bivariate ARIMA Analysis.……………………..………………………………………. 65Conclusion………………………..…………..…………………………………………….. 66

CHAPTER 5: RESULTS OF TIME SERIES ANALYSES OF CLEARANCES AND CRIMES

Introduction…………..…………………………………………………………………….. 67Interrupted Time Series Results………………….……………………………………... 67Summary…………….…………………………………………………………………... 88

Bivariate Analyses Results………………..………………………………………………... 89Conclusion……………..…………………………………………………………………… 111

CHAPTER 6: DISCUSSION AND SUMMARY OF FINDINGS

Introduction…………………………………………………………………………………. 116Interrupted Time Series Discussion………………………………………………………… 116Bivariate Analyses Discussion……………………………………………………………… 125Recommendations and Limitations…………………………………………………………. 128Conclusions…………………………………………………………………………………. 130

References…………………………………………………………………………………... 132

vii

List of Tables

Table 4.1: Crimes and Clearances by Year for the City of Houston, 1997-2008…..…..... 49Table 4.2: Crimes and Clearances by Police Division for the City of Houston, 1997-2008. 53Table 5.1: Final Univariate and Intervention Models for the City………………………… 68Table 5.2: Social Context of Westside Police Divisions in Houston Using Non-proportional Census Distribution…………………………………………………………… 71Table 5.3: Final Univariate Models for Westside Police Divisions……………………….. 72Table 5.4: Zero-Order Intervention Models for Westside Police Divisions………………... 73Table 5.5: Final Univariate Models for Crime in Westside Police Divisions……………… 76Table 5.6: Zero-Order Intervention Models on Crime for Westside Police Divisions…….. 77Table 5.7: Final Univariate Clearance Models for Eastside Police Divisions……………… 79Table 5.8: Social Context of Eastside Police Divisions in Houston Using Non-proportional Census Distribution…………………………………………………………………………. 81Table 5.9: Zero-Order Intervention Clearance Models for Eastside Police Divisions…….. 82Table 5.10: Final Univariate Crime Models for Eastside Police Divisions………………… 85Table 5.11: Zero-Order Intervention Crime Models for Eastside Police Divisions……….. 87Table 5.12: Final Univariate Models for Full, Pre-, and Post-displacement Series……….. 91Table 5.13: Estimated CCFs for the Full Series for All Aggregates……………………….. 96Table 5.14: Contextual Transfer Function Models, Full Series……………………………. 101Table 5.15: Estimated CCFs for the Pre-displacement Series for All Aggregates…………. 103Table 5.16: Contextual Transfer Function Models, Pre-displacement Series………………. 106Table 5.17: Estimated CCFs for the Post-displacement Series for All Aggregates……….. 107Table 5.18: Contextual Transfer Function Models, Post-displacement Series……………... 111Table 6.1: Social Context of Westside Police Divisions in Houston Using Non-proportional Census Distribution…………………………………………………………… 122

1

CHAPTER ONE

THE ISSUES OF DIRECT MEASUREMENT, AGGREGATION BIAS, AND SOCIAL CONTEXT UNDER THE CONFLICT PERSPECTIVE

INTRODUCTION

The focus of the current research is to determine the indirect effects of Hurricane Katrina

on crime, arrests, and the relationship between crime and arrests. More specifically, this research

assesses the impact of the displacement of citizens to Houston, Texas on crime and arrests in

Houston, a city not directly exposed to the natural disaster. This study occurs under the guidance

of the conflict perspective and addresses the issues of: (1) direct measurement of the conflict

perspective’s notion of threat, (2) the identification and selection of an appropriate unit of

analysis, and (3) consideration of the social contexts when examining crimes, arrests, and the

relationship between the two. The remainder of this chapter outlines the importance of

addressing these issues when examining the conflict perspective.

The conflict perspective states that crime control is a tool used to protect the interests of

elite populations (Black 1976; Blalock 1967; Turk 1969; Chambliss and Seidman 1971; Spitzer

1975; Quinney 1970, 1977; Jackson 1989; Liska 1992). Research on crime control under this

perspective generally focuses on two hypotheses. The first is known as the threat hypothesis.

This hypothesis states that symbolic or physical threats to elite populations will lead to an

increase in crime control (Liska 1992). This increase in crime control is to protect the position of

elites in society. The second hypothesis is known as the benign neglect hypothesis. The focus of

this hypothesis is on symbolic or physical threats to non-elite populations. When threat is

experienced by a non-elite population, the benign neglect hypothesis predicts a decrease in crime

control (Liska 1992). This occurs because the non-elite population lacks the ability to legitimize

2

their complaints to police, or because the acts are committed intra-group and are viewed as a

personal matter deemed unnecessary for formal intervention (Liska and Chamlin 1984). In

general, past research finds support for the threat hypothesis (Brown and Warner 1992;

Carmichael 2005; Corzine, Creech, and Corzine 1983; Eitle, D’Alessio, and Stolzenberg 2002;

Greenberg, Kessler, and Loftin 1985; Holmes 2000; Jackson and Carroll 1981; Jacobs 1979;

Jacobs and Britt 1979, Kane 2003; King and Wheelock 2007; Liska, Lawrence, and Benson

1981; Liska, Chamlin, and Reed 1985; Nalla, Lynch, and Leiber 1997; Ruddell and Urbina 2004;

Smith and Holmes 2003; Stults and Baumer 2007), but research on the benign neglect

hypothesis, having far fewer tests, receives mixed support (Chamlin and Liska 1992; Liska and

Chamlin 1984; Eitle, Stolzenberg, and D’Allesio 2005; Myer and Chamlin 2007; Parker et al.

2005; Stolzenberg et al. 2004). Two topics that are common to the testing of both the threat

hypothesis and the benign neglect hypothesis are (1) the measurement of the intervening variable

(i.e., the concept of threat), and (2) the unit of analysis used to study the threat and benign

neglect hypothesis (i.e., the city level of analysis).

Previous research on the conflict perspective typically conceptualizes threat as the size of

minority groups. The size of a non-elite population (e.g., percent black) is thought to be

indicative of perceived threat, because an increase of this subordinate population poses a threat

to the economic and political position of elite populations. As such, previous research has

assessed the relationship between the size of minority groups and the size of police institutions

(Chamlin, 1989; Greenburg, Kessler, and Loftin 1985; Jackson 1986, 1989; Jackson and Carroll

1981; Jacobs 1979; Liska, Lawrence, and Benson 1981; Nalla, Lynch, and Leiber 1997; Stults

and Baumer 2007) or the activity of police institutions (Brown and Warner 1992; Chamlin and

Liska 1992; Eitle, D’Alessio, and Stolzenberg 2002; Liska and Chamlin 1984; Liska, Chamlin,

3

and Reed 1985; Parker, Stults, and Rice 2005; Stolzenburg, D’Alessio, and Eitle 2004). The

emergence of a significant relationship between the size of a minority group and formal social

control is often used to infer perceived threat by elites. The consequence of this approach is that

the intervening variable of threat is not directly measured (Chamlin 1989; Chamlin 2009, Eitle et

al. 2002; King and Wheelock 2007; Jacobs 1979; Parker, Stults, and Rice 2005). By not directly

measuring the theoretical construct of threat, the statistical association between minority group

size and some outcome (e.g., crime control) is susceptible to multiple interpretations. For

example, the positive statistical relationship between minority size and arrests can also be

thought of as a challenge to the social solidarity of the social system, a structural functionalist

perspective (for example, see Inverarity 1976). It is the intention of the present research is to

directly account for threat, thus eliminating multiple theoretical interpretations.

In addition to the measurement of threat, this research also addresses the issue of

aggregation bias. The examination of data at an improperly specified unit of analysis may lead

to incorrect or null results. To avoid this, research must confront a theory with data collected at

the appropriate unit of analysis in order to falsify it (Bailey 1984; Greenberg, Kessler, and Logan

1981; Land, McCall, and Cohen 1990; Lieberson 1985). For example, Bailey (1984) states that

cities are more appropriate than SMSAs when studying the poverty-crime relationship.

Greenberg and colleagues (1981) demonstrate that state-level evaluations of general deterrence

theory have little probative value because the causal mechanism operates at a smaller level of

aggregation.

Aggregation bias is relevant to the present research because previous research has

evaluated threat and benign neglect across municipalities, when in fact the mechanisms

underlying the threat and benign neglect hypotheses may occur at a level below the city (Myer

4

and Chamlin 2007, Stolzenberg, D’Allesio, and Eitle 2004). Recall that the benign neglect

hypothesis predicts a decrease in crime control because of an inability of non-elite populations to

legitimize their complaints or because of an increase in intragroup crime. This is significant to

the conflict perspective because previous research has also evaluated the relationship between

the distribution of minority groups (via a measure of segregation at the city level) and crime

control (Brown and Warner 1992; Carmichael 2005; Chamlin and Liska 1992; Eitle et al. 2005;

Liska and Chamlin 1984; Liska, Lawrence, and Benson 1981; Liska et al. 1985; Parker et al.

2005; Parker, MacDonald, Jennings, and Alpert 2005; Stolzenberg et al. 2004).

The segregation of less powerful populations increases the likelihood of intraracial crime

on populations that already have limited sociopolitical power to legitimize their complaints to

police (Blauner 1972; Spitzer 1975). Past research typically measures segregation at the city

level through the use of the dissimilarity index, which compares the racial composition of city

blocks to the racial composition of the city as a whole. This is done for all blocks in order to

measure the percentage of one racial group that would have to move to a different neighborhood

to be distributed similarly as another racial group (See Massey and Denton, 1988). The resulting

index score provides a measure of segregation for the entire city. If results produce a negative

relationship between segregation and social control, support for benign neglect is revealed. The

issue paramount to this approach is that the city level, the typical level of aggregation when

examining the benign neglect (and threat) hypothesis, may be masking observable effects that

occur at a level beneath the city. As an example, imagine a sample of cities, each containing

only one or two neighborhoods that are segregated. If such were the case, there is likely to be

little variation in the level of segregation across the sample of cities. Necessarily, measures of

segregation would have little, if any, impact on crime control outcomes. The effects of

5

segregation that operate across neighborhoods within cities are then being masked by the use of

city-level data (Blauner 1972; Spitzer 1975). If such were the case, previous research has

neglected to use the appropriate unit of analysis. An objective of this study is to examine

whether the predictions of the threat and benign neglect hypotheses are evidenced at sub-city

level by taking into account contextual characteristics of neighborhoods within the city.

Accounting for the social context is important because previous research has demonstrated that

social control can be a function of the social context within which police officers operate

(Klinger 1997; Klinger 2004; Smith 1986; Smith, Visher, and Davidson 1984; Terrill and Reisig

2003).

The final intent of this research is to examine the relationship between crime and arrests.

While theory posits a relationship between crimes and arrests (see Becker 1968; Gibbs 1975;

Tittle 1980), different hypotheses predict different interactions between the two variables. The

overload hypothesis predicts that increases in crime will lead to a decrease in arrests because the

resources of the police are taxed (Fisher and Nagin 1978; Geerken and Gove 1977), whereas the

public choice hypothesis predicts that an increase in crimes will lead to an increase in arrests

because there is more pressure put on police to address the up-rise in crime (Borcherding and

Deacon 1972; Deacon 1978; Tridimas 2001). Alternatively, the deterrence hypothesis predicts

that an increase in arrests will lead to a decrease in crime because the costs of committing crimes

exceed the benefits (Becker 1968; Geerken and Gove 1977; Gibbs 1975).

Initial tests of the above hypotheses were undertaken using cross sectional designs.

While many of these tests produced significant findings, there was growing concern about the

limitations of cross sectional designs in the evaluation of the reciprocal relationship between

crimes and arrests. Accordingly, researchers began evaluating the predictions of these

6

hypotheses through time series analyses in an attempt to examine the temporal order and lag

structure of the relationship between crimes and arrests—both limitations of cross-sectional

designs. Generally, time series analyses did not replicate the findings of cross sectional designs

(Chamlin 1988; Greenberg et al. 1979; Greenberg and Kessler 1982; Logan 1975). This has led

some to argue that findings from the cross-sectional analyses are corrupted by model-

misspecification error (Greenberg et al. 1979). Recently, it has been argued that the inability of

time-series analyses to replicate findings from cross-sectional analyses on the crime-arrest

relationship may in fact be due to the inability to account for the social contexts of cities

(Chamlin and Myer 2009). This research will build off this new line of research to determine if

social context does in fact play a role in the reciprocal relationship between crimes and arrests.

The threat hypothesis and the benign neglect hypothesis vary in their predictions of crime

control based on the status of the group experiencing threat, but the effects of their predictions

may not be mutually exclusive. As such, the predictions of these hypotheses may have utility in

the investigation of the reciprocal relationship between crimes and arrests. If there is an increase

in arrests to protect the interests of social elites (the threat hypothesis), it would be expected to

simultaneously reduce law enforcement in areas dominated by non-elites. This is then likely to

generate a reduction in the amount of offenses cleared by arrest. Accordingly, the benign neglect

hypothesis predicts that after the experience of symbolic or physical threat, the level of crime

will begin to negatively affect the level of arrests in predominately black (non-elite) areas of the

city. For the purposes of the current research, this means that changes in the level of arrest will

affect changes in the level of crimes post-displacement, but not before. These changes will also

be a function of the social contexts of Houston, Texas.

7

THE PRESENT RESEARCH

The intent of this study is to determine the indirect effects of Hurricane Katrina on crime,

arrests, and the relationship between crimes and arrests. The current research utilizes a quasi-

experimental, time series design to account for the occurrence of Hurricane Katrina and the

resulting displacement of citizens to Houston. Previous research has evaluated the effects of

disasters such as hurricanes (Brezina and Kaufman 2008; Davila, Marquart, and Mullings 2005;

Faust and Kauzlarich 2008; Kirk 2009; Kulkarni, Bell, Beausoleil, Lein, Angel, and Mason

2008; Lanza-Kaduce, Dunham, Akers, and Cromwell 1998; LeBeau 2002; Rojek and Smith

2007; Thomas 2008), riots (Bergesen and Herman 1998; Chamlin 2009; Chamlin and Cochran

2000; Chamlin and Myer 2009; King and Waddington 2004; Myer and Chamlin 2007),

earthquakes (Green 2005), maritime disasters (Rothe, Muzzatti, and Mullins 2006), and terrorism

(Bornstein 2005; Frank, Dewart, Schmeidler, and Demirjian 2006; Pandiani, Knisley, Banks,

Simon, and Blackburn 2005; Pridemore, Chamlin, and Trahan 2008) on various outcomes. Most

of the research on Hurricane Katrina has evaluated the direct effects on New Orleans; however,

the indirect effects of Katrina also merit inspection. Assessing the effects of Hurricane Katrina

on Houston, Texas is relevant because of the amount of citizens that were affected, directly

(displaced New Orleans residents) and indirectly (Houston residents)—Houston eventually

housed approximately 250,000 evacuees (Berger 2006). The displacement of citizens to

Houston, Texas constitutes a threatening event for both the displaced citizens of Louisiana, as

well as the residents of Houston, due to the abrupt nature of the event.

This research will assess the predictions of the threat hypothesis and the benign neglect

hypothesis by providing a more direct measure of threat, the displacement of citizens. The

predictions of these two hypotheses will also be assessed at a level below the city. Houston

8

Police divisions and their social contexts will be examined. Examination of social context is

important because it can influence the administration of social control (Klinger 1997; Klinger

2004; Smith 1986; Smith, Visher, and Davidson 1984; Terrill and Reisig 2003). Finally, this

paper will also explore the predictions of these two hypotheses in the context of the crime-arrest

literature to determine if the reciprocal relationship between crimes and arrests is affected in

different social contexts of the city, post-displacement.

To this end, a number of objectives must be accomplished. A review of the research on

the conflict perspective’s threat and benign neglect hypotheses will be presented in Chapter 2.

This discussion will highlight how previous research measures threat and segregation and the

level at which these analyses have been conducted. The crime-arrest relationship literature will

be discussed in Chapter 3. Because one of the aims of the present research is to examine if the

relationship between crimes and arrests was influenced by the displacement of citizens to

Houston, it is important to review how previous research attempts to examine the association

between crimes and arrests. Chapter 4 provides the research strategy and methodology used to

examine the threat hypothesis, the benign neglect hypothesis, and the relationship between

crimes and arrests. The results of the time series analyses on crimes, arrests, and the relationship

between the two will be presented in Chapter 5. Finally, Chapter 6 provides a discussion on the

results, as well as the implications of the findings.

9

CHAPTER TWO

A CRITICAL REVIEW OF THE CONFLICT PERSPECTIVE

INTRODUCTION

The conflict perspective has a rich tradition in criminological research. In order to better

understand the foundations of the current research, this chapter offers a discussion on the origins

of the criminological conflict perspective’s views on crime and its predictions on the

administration of social control. This includes a review of the threat hypothesis and the benign

neglect hypothesis. A second priority of this chapter is to present past research on the threat and

benign neglect hypothesis. For each study reviewed, the measurement of threat and unit of

analysis will be offered. Third, because it is the intent of the current research to provide a more

direct measure of threat and identify the proper unit of analysis to inspect the two hypotheses, a

brief review of the methodological concerns of indirect measurement and aggregation bias will

be provided. Finally, an outline of how the present research will address the issues of threat and

aggregation bias will be offered.

THE CONFLICT PERSPECTIVE

The conflict perspective stems from the early works of the sociologists Karl Marx and

Friederich Engels. Their writings focused on the conflict between the working class and the

property owners. In short, they argue that it is in the best interest of property owners to maintain

their elite status through the exploitation of the working class and by determining the ruling ideas

of society. While much of the writings of Marx nor Engles did not place an emphasis on crime

and the criminal justice system, modern day scholars have produced a theoretical work on crime

and the criminal justice system based on Marx and Engle’s scholarship. This line of reasoning is

the focus of this research.

10

Building on the thinking of Marx and Engles, the conflict perspective takes a unique

perspective on crime in the sense that it does not view crime as an inherent condition. For

example, other theories explain crime in terms of an individual’s attachment to institutions of

society (Hirschi 1969), the level of personal self-control (Gottfredson and Hirschi 1990), the

ability to learn crime (Burgess and Akers 1966), or the amount of strain an individual has

(Agnew 1985, 1992). Instead, the conflict perspective asserts that crime results from the conflict

between powerful, elite groups of society and less powerful, non-elite groups of society. It is

this conflict between the groups that produces crime.

One of the first criminologists to build off of Marx and Engles was Willem Bonger

(1916). Bonger follows the original underpinnings of the conflict perspective and argues that a

consequence of capitalism is crime (see also Currie 1997). More specifically, Bonger argues that

capitalism stresses focus on individual level success, what Bonger labels “egoism.” Produced by

capitalism, egoism stresses individual profits through the exploitation of others at the benefit of

individual success and the exclusion of the larger social good. This leads to an unequal

distribution of resources and moves the cultural towards individualism. Crime emerges from the

increase in self-interest, as the powerless commit crimes out of a sense of need or injustice.

Turk (1969) agrees that the ongoing struggle between elite, powerful groups and non-

elite, powerless groups produces crime. But crime is not necessarily the result of differences in

economic standing so much as it is the social construction of law. According to Turk (1969),

perceptions of group behavior are relative—the behavior of any one group is going to be

perceived as negative by the other group. Turk argues that elite groups of society label the

behavior of non-elite groups of society as threatening and devote resources to curtail these

“threatening” behaviors. The labeling of non-elite’s behaviors as threatening allows elite groups

11

to protect their development of the cultural order and maintain their status and control as an elite

group (Chambliss 1975; Chambliss and Seidman 1971). This idea was further embraced by

Richard Quinney (1969; 1970), who argues that social segments of society conceptualize and

develop their own normative systems that define acceptable behavior. Each segment of society

then views their own system’s definitions as normal and the other’s as abnormal. These clashing

definitions lead to crime, with the end result being that the powerless have their definitions

labeled as criminal.

Imbedded in the above discussion is the notion that laws are created to protect the

interests of the powerful. In order to protect interests, laws are created that function as a

mechanism to control the powerless. Thus, a main feature of the conflict perspective is

explaining the administration of social control. It is also this aspect of the conflict perspective

emphasizes the notion of threat. One of the leading discussions of threat comes from the work of

Hubert Blalock.

Blalock (1967) argues that increases in social control will result when the political and

economic status of elite groups are threatened by non-elite groups. Up to this point, there had

been no clear articulation of what constitutes elite and non-elite groups. Addressing this, Blalock

couches his theory in terms of minority-group relations. Succinctly stated, Blalock argues that a

nonlinear relationship between discrimination and the size of minority groups is a result of threat

felt by non-minority groups (pp. 144-154). Accordingly, when increases in minority groups

threaten the socioeconomic position, competition, and power of non-minority groups, increases

in discrimination (or motivation to discriminate) will result (see also Black 1976).

The idea that laws are created to benefit some and not all has been amalgamated with the

theoretical underpinnings of Blalock’s theory on minority-group relations. This marriage of

12

ideas has led to the conflict perspective’s rationale on the administration of social control. One

of the first attempts to apply Blalock's theory of majority group discrimination to the relationship

between minority group size and macro social control is Jackson and Carroll’s (1981)

examination of variations in policing resources among 90 non-southern cities. Drawing on

Blalock’s power threat hypothesis, they contend that as minority group size increases, so too

does the level of policing resources. This relationship holds until a point at which racial

minorities achieve a numerical superiority (around 50%) and thereby begin to resist the use of

policing resources to suppress them. The current body of research uses two main hypotheses to

examine social control as a function of racial tensions. These two hypotheses are known as the

threat hypothesis and the benign neglect hypothesis.

The Threat and Benign Neglect Hypotheses

Both the threat and the benign neglect hypotheses make predictions on the use of social

control based on group exposure to threat. Key to both the threat and the benign neglect

hypotheses is the concept of threat. The difference between the two hypotheses is the group

(elite or non-elite) who experiences the threat.

The threat hypothesis predicts an increase in social control when elite groups experience

threat to their social status. In order to protect their social standing and position in society, elite

groups utilize the formal mechanisms of crime control to protect their interests from groups that

are viewed as threatening their status quo. The ancillary benign neglect hypothesis predicts a

decrease in crime control. This is because the groups experiencing the threat are powerless, non-

elite groups. There are two mechanisms underlying the benign neglect hypothesis (Liska and

Chamlin, 1984). First, non-elite groups may not be able to legitimize their complaints because of

13

their lack of socio-political power. Second, the threat may lead to increases in intra-group crime

which may be viewed by the police as a personal matter undeserving of formal intervention.

While there remains debate on the constitution of elite groups (Bierne 1979; Liska 1992;

Spitzer 1975), the operationalization of key variables involved in the testing of the threat and

benign neglect hypotheses has been established in the literature. Namely, tests of the threat

hypothesis look at the relationship between the size of minority groups and crime control, while

tests of the benign neglect hypothesis evaluate the relationship between the distribution of

minority groups and crime control. Past tests of the threat and benign neglect hypotheses have

evaluated the relationship between perceived threat and the size of police institutions (Chamlin,

1989a; Greenburg, Kessler, and Loftin 1985; Jackson 1986, 1989; Jackson and Carroll 1981;

Jacobs 1979; Liska, Lawrence, and Benson 1981; Nalla, Lynch, and Leiber 1997; Stults and

Baumer 2007), police use of force (Chamlin 1989b; Holmes 2000; Liska and Yu 1992; Parker,

MacDonald, Jennings, and Alpert 2005; Smith and Holmes 2003;), incarceration (Carmichael,

2005; Myers 1990; Tittle and Curran 1988), executions and lynchings (Phillips 1986; Tolnay,

Beck, and Massey 1989, 1992) or the use of arrests by police (Brown and Warner 1992;

Chamlin 2009, Chamlin and Liska 1992; D’Alessio, Stolzenberg, and Eitle 2002; Eitle,

D’Alessio, and Stolzenberg 2002; Eitle, Stolzenberg, and D’Alessio 2005; Liska and Chamlin

1984; Liska, Chamlin, and Reed 1985; Parker, Stults, and Rice 2005; Stolzenburg, D’Alessio,

and Eitle 2004). The focus of the present research is on the relationship between the use of arrest

as social control. As such, the following review of the literature on the threat and benign neglect

hypotheses will focus on the related research on the relationship between threat and police

aggressiveness. Special attention will be paid to the measurement of threat, segregation, and the

unit of analysis at which a study is conducted.

14

PREVIOUS RESEARCH ON THE THREAT AND BENIGN NEGLECT HYPOTHESES

Williams and Drake (1980) produced the first study to evaluate the relationship between

threat and police use of arrest. Investigating a sample of SMSAs with a population above

500,000 in 1970, Williams and Drake inspect the role of economic inequality, percent black,

percent unemployed, population size, and victimization rate on arrest rates for each of the Type I

index crimes. Results showed no relationship between the structural variables—including their

measure of percent black—and any of the seven index crimes.

One of the drawbacks of Williams and Drake’s (1980) research was the inability to

control for the crime rate. To address this, Liska and Chamlin evaluated a sample of 76 cities

with a population over 100,000. The authors used regression analyses and controlled for the

crime rate, and also the city population, police force size, percent poor, income inequality,

segregation, and percent nonwhite. Liska and Chamlin also took the unique step of disaggregated

property and personal arrest rates by race. This allowed for the creation of race specific models

of arrests. Analyses for the aggregate models (i.e., models that did not disaggregate arrests by

race) demonstrate a positive, significant relationship between percent nonwhite and personal and

property arrests. Arrests were then disaggregated by race, revealing no significant effect of

percent nonwhite and white personal or property arrests. This is contrary to the predictions of

the threat hypothesis. However, percent non-white was significantly and negatively related to

black arrest rates for both personal and property crimes, being the least important predictor in the

white arrest model and the most important predictor in nonwhite arrest model. Inspection of the

role of segregation revealed a significant, negative relationship to arrest rates for both white and

nonwhite arrest rate models. The results of Liska and Chamlin’s (1984) analyses provide

support for the benign neglect hypothesis, but not the threat hypothesis.

15

Liska, Chamlin, and Reed (1985) pit the predictions of the conflict perspective against

the predictions of an economic approach in explaining the certainty of punishment. To do this,

Liska and colleagues evaluate the clearance rates (ratio of arrests to crimes) for 77 cities with a

population over 100,000. Regression analysis is used to control for the effects of workload,

resources, population, percent poor, income inequality, segregation, and percent nonwhite on

each of the seven index crimes (i.e., homicide, rape, assault, robbery, burglary, larceny, and auto

theft). Results of the analyses indicate that after controlling for economic and conflict

exogenous variables, percent nonwhite—the indicator of threat—was positively and significantly

related to the certainty of arrest for all index crimes but assault, lending support to the threat

hypothesis. Moreover, segregation was significantly and negatively related to arrests for all

crimes except homicide, supporting the benign neglect hypothesis.

To account for the possibility of period effects of their earlier research (Liska and

Chamlin 1984), Chamlin and Liska (1992) examine similar data 10 years later. As such,

regression analyses were conducted on race specific arrest rates for property and personal crimes

for 97 cities. Analyses of the effects of percent nonwhite on white personal and property arrests

rates again revealed no support for the threat hypothesis. In fact, for property arrests, whites

were now significantly less likely to be arrested as the percentage of nonwhites in a city

increased. Percent nonwhite was not significantly related to the arrest rate for white personal

crimes. The relationship between segregation and arrest rates for both the white and nonwhite

arrest models was non-significant, unlike in previous findings. In short, this analysis now

revealed no support for benign neglect.

Brown and Warner (1992) argue that the previous tests of the threat hypothesis may be

subject to a historical effect—the turbulent social unrest of the 1960s. More specifically, Brown

16

and Warner argue that the reliance of the measure of percent minority may be affected by the

social movements of the period under investigation. To determine if the findings are relevant to

a different historical time period, Brown and Warner examine data from the 50 largest cities in

the United States in 1900. Rather than employ percent minority as their measure of threat, the

authors institute a measure percent foreign born to capture threat felt by native born Americans

in predicting arrests for drunkeness. Results demonstrated that percent foreign born was a

significant, positive predictor of arrests for drunkenness despite controls for alcohol consumption

and police force size. In later models, this significant effect was not observed, as it appears to be

mediated by the political and social structure of a city. With regards to segregation, there was no

support for the benign neglect hypothesis as this variable demonstrated no statistically significant

relationship to arrests.

Eitle, D’Alessio, and Stolzenberg (2002) take issue with the operationalization of threat

as the relative size of minority population. To address this, the authors utilize three distinct

measures of threat: (1) the ratio of black-to-white voting; (2) the ratio of black-to-white

unemployment; and (3) the black-on-white crime rate. Eitle and colleagues use NIBRS data

from 46 counties in South Carolina to estimate pooled cross-section time series equations.

Analysis on the effects of black-on-white crime on black arrest rates revealed a positive,

significant relationship. Specifically, as interracial crime increases, the probability of a black

individual being arrested also increases, which is consistent with the threat hypothesis.

However, there was no statistical relationship between the other two measures of threat, the ratio

of black-to-white voting or the ratio of black-to-white unemployment, and arrest rates. Eitle and

colleagues did not include a measure of segregation in any of their analyses.

17

In a subsequent study, D’Alessio, Stolzenberg, and Eitle (2002) evaluate the effects of

both the ratio of black-to-white voting and the ratio of black-to-white unemployment, as well as

the effect of percent nonwhite, on four different dependent variables. These four endogenous

variables are: (1) white-on-black crime rate; (2) black-on-white crime rate; (3) white-on-white

crime rate; and (4) black-on-black crime rate. Again, data were from the NIBRS on 46 counties

in South Carolina. Analyses from the pooled cross-section time series equations revealed no

significant effects for the percent nonwhite or the ratio of black-to-white voting across any of the

four dependent variables. The ratio of black-to-white unemployment was a significant, negative

relationship with white-on-black crime. This variable has no significant impact on any of the

other victim-offender dyads. Segregation was not included as a variable in any of the models.

Kane (2003) explores a different unit of analysis than past studies. Specifically, Kane

argues that threat hypothesis research is better suited for a smaller unit of analysis. Kane

suggests that police districts are the most appropriate units because this aggregate level is where

police develop work groups and norms of behavior. To this end, Kane hypothesizes that

increases in nonwhite population, disaggregated into percent black and percent Latino, will lead

to increases in police deployment. A panel design is used on three years of data from the New

York City Police Department. Results from the analyses showed no relationship between police

deployment and percent black. However, once the Latino population of a police district reached

23 percent, there was a significant, positive relationship with police deployment. Thus, Kane’s

police district analysis provided mixed support for the threat hypothesis.

While Kane (2002) did not include a specific measure of segregation in his models, his

data were able to capture the percent black and percent Latino of each district under

investigation. In this sense, he did succeed in capturing the relative segregation of each police

18

district. Accordingly, Kane found no support for the benign neglect hypothesis. Increases in

black population (i.e., increases in district segregation) were unrelated to arrests, and increases in

Latino population in each district (i.e., increases in district segregation) were in the opposite

direction predicted by the benign neglect hypothesis.

Stolzenburg, D’Alessio, and Eitle (2004) combine microlevel NIBRS data with macro

level census data to develop a multilevel test of the threat hypothesis. In short, Stolzenberg and

colleagues wanted to control for individual factors (e.g., race) as well as structural factors (e.g.,

segregation) to determine the important influences on the probability of arrest for a violent

crime. The results of the multilevel analysis failed to support the threat hypothesis. Instead, the

authors found that the percent population black was significantly and negatively related to the

probability of arrest. That is, as a city’s black population increased, the likelihood of arrests

decreased, which is not predicted by the threat hypothesis. While this finding is in disagreement

with the threat hypothesis, it appears to be consistent with the benign neglect hypothesis.

However, further analysis revealed that percent black was not significantly related to the

likelihood that black offenders will be arrested or the probability that intraracial crimes will

result in an arrest. Analyses of segregation revealed that there was a significant and negative

relationship between a city’s level of segregation and (1) the overall probability of arrest (black

or white offender), (2) the likelihood of black offenders being arrested, and (3) the probability

that intraracial crimes (black-on-white) resulted in an arrest. Taken as a whole, these findings

provided no support for the threat hypothesis, and mixed support for the benign neglect

hypothesis.

Parker, Stults, and Rice (2005) offer different operationalizations of threat by

incorporating three different measures of threat in their analyses. Specifically, Parker and

19

colleagues measure threat through the traditional percent black population, but also include the

measures of percent black immigration and a racial inequality index. The racial inequality index

was developed using principal components factor analysis with the following factors: percent

persons living below poverty, income inequality, percent males jobless aged 16 and older,

percent children not living with both parents, white-black unemployment ratio, white-black

bachelor degree ratio, and white-black high school diploma ratio. Data were from 245 cities

with a population over 100,000 in 2000. The authors estimated separate models for arrests

disaggregated by race. Results demonstrated no relationship for the racial inequality index for

either white or black arrests. Moreover, the measures of percent black and percent black

immigration were not related to white arrests, but were significantly and negatively related to

black arrests. Specifically, increases in the size of the black population and increases in the

number of black immigrants were associated with a decrease in the number of black arrests.

These findings are inconsistent with the threat hypothesis, but consistent with the benign neglect

hypothesis. Nevertheless, analysis of segregation produced no statistical relationship with

arrests, leading to mixed findings regarding the benign neglect hypothesis.

Eitle, Stolzenberg, and D’Alessio (2005) employed hierarchal linear modeling to examine

the impact of individual, city, and police organization variables on probabilities of arrest for

aggravated assaults and simple assault separately in 105 small cities. There was no relationship

between a city’s percent black population and simple or aggravated assaults. Thus, Eitle and

colleagues did not find support for the threat hypothesis. However, with regards to the benign

neglect hypothesis, there was a significant negative relationship between a city’s level of

segregation and probability of arrest for aggravated assault and simple assault. In fact, the

20

authors noted that the difference between arrest probabilities for whites and blacks was relatively

large. This finding supports the predictions of benign neglect.

Chamlin (2009) also attempts to provide a more direct measure of threat. Rather than

rely on a compositional measure of minority population, Chamlin uses the occurrence of a race

riot as a measure threat. Using time series data on robbery arrests in the city, Chamlin finds an

increase in robbery arrests directly after the threatening event of the race riot, as predicted by the

threat hypothesis. To control for the possibility of a history effect, similar data were examined

for the cities of Dayton and Columbus, Ohio, where no riots occurred, and no changes were

observed in the level of robbery arrests. There were no controls for segregation in Chamlin’s

analysis.

Summary

The above discussions have demonstrated that results of tests of the threat hypothesis and

benign neglect hypothesis are mixed. Two themes emerged in the above discussion: (1) tests of

the threat hypothesis either lacked direct measures of threat or the exploration of more direct

measures was a focal concern; and (2) the vast majority of tests were conducted at the city level

of analysis. Because findings for both hypotheses were clearly mixed, this dissertation will

address these two themes. As such, the next section provides a discussion surrounding the

concerns of the two methodological issues: indirect measurement and aggregation bias.

METHODOLOGICAL ISSUES

Indirect Measurement: The Threat Hypothesis and the Size of Minority Groups

The size of minority group is the most frequently used operationalization of threat. The

use of this measure stems from Blalock’s (1967) assertion that increases in black minority groups

are viewed as threatening to the status of the white majority. Tests of the threat hypothesis

21

evaluate the correlation between percent black and the size of a police force or the use of arrest

by police. A significant positive association between the size of minority group and crime

control is taken as an overall indication that there is a response to perceived threat to elites.

Therefore, the indirect measurement of threat has become a staple in previous research on the

conflict perspective’s hypotheses on the administration of crime control.

The inability to directly measure threat presents an immediate obstacle for theory testing,

thus leaving the interpretation of the correlation between the size of a minority group and crime

control susceptible to multiple interpretations. For example, a structural functionalist argument

would say that increases to the size of minority groups represent a remonstrance to the

universalistic values of the public good (Durkheim 1933; Inverarity 1976; Lauderdale 1976).

This argument was made by Inverarity (1976:278) who argues that the observed positive

relationship between percent black and lynchings across Louisiana Parishes is a function of the

detrimental effects of racial heterogeneity on the stable operation of societal order. A similar

example can be provided using social disorganization theory (Shaw and McKay 1972).

One of the key exogenous variables in social disorganization theory is population

heterogeneity. According to social disorganization theory, racial heterogeneity impedes

communication and centralizing community interaction. This in turn weakens informal social

control and increases the need for formal social control (Bursik 1988; Sampson and Groves

1989; Shaw and McKay 1972). But this relationship between heterogeneity and crime is

inherently nonlinear. As population heterogeneity lessens (increasing minority group

homogeneity), reliance on formal mechanisms of social control (such as arrest) should also

decrease. As noted above, Blalock (1967) argued for a nonlinear relationship between

discrimination and percent minority. In his power-threat hypothesis, increases in percent

22

minority threaten non-minority populations. However, once the minority groups numbers are

large enough, they are able to defy the discrimination by non-minority groups. The presence of

this curvilinear relationship has been supported by research on the conflict perspective. Jackson

and Carroll (1981) identified this concave relationship between percent black and police

expenditures, while Greenberg, Kessler, and Loftin (1985) found the same form in the

relationship between percent non-white and police force size.

The same relationships predicted by conflict theory can also be explained by competing

theories’ hypotheses, which fails to falsify the predictions of any theory. In order to avoid the

problem of multiple interpretations and failing to falsify conflict theory’s threat hypothesis, it

stands to reason that a more direct measure of threat is needed. This dissertation offers a more

direct measure of threat—the displacement of citizens by Hurricane Katrina—which allows for

the falsification of competing theoretical explanations.

The Proper Unit of Analysis: The Distribution of Minority Groups and the Benign Neglect

Hypothesis

The notion of group distribution within society has a place in the conflict perspective.

For example, Quinney (1974; 1977) argues that the powerful utilize class fragmentation to get

the powerless class to fight within themselves. Blauner (1972) suggests that segregation can

influence the administration of social control by affecting the relative probabilities of the

offender-victim dyad. Specifically, the segregation of blacks (the less powerful) lessens the

likelihood of interracial victimizations and simultaneously increases the probability of intraracial

victimizations. Thus, based on the benign neglect hypothesis, one would predict that the

segregation of racial minorities would reduce reliance on more overt and formal mechanisms of

social control (Blauner 1972; Spitzer 1975).

23

Evaluation of the benign neglect hypothesis looks at a city’s level of segregation and its

relationship to crime control. If a significant, negative relationship is observed, this is taken as

evidence of benign neglect. Measurement of segregation is typically done through the use of the

dissimilarity index, which compares the racial composition of city blocks to the racial

composition of the city as a whole. This is done for all blocks in order to measure the

percentage of one racial group that would have to move to a different neighborhood to be

distributed similarly as another racial group, and produces an index score that measures

segregation for the entire city (See Massey and Denton, 1988). Thus the benign neglect

hypothesis is studied at the city level of analysis. This research contends that this level of

analysis may be inappropriate for the study of the benign neglect hypothesis given the

mechanisms underlying benign neglect.

Picture a sample of cities, each containing only one or two neighborhoods that are

segregated. If this is the circumstance, there would likely be little variation in the level of

segregation across a sample of cities. Hence, measures of segregation probably would have

little, if any, impact on crime control outcomes. Therefore, the segregation on crime for the one

neighborhood of a city would go unnoticed (Blauner 1972; Spitzer 1975). In addition to the

mechanisms of benign neglect warranting further investigations of the proper unit of analysis,

there is another reason to suspect a more appropriate unit of analysis—police use of social

control is a function of the social context within which they operate (Klinger 1997; Klinger

2004; Smith 1986; Smith, Visher, and Davidson 1984; Terrill and Reisig 2003). Because the

conflict perspective is interested in explaining social control, it stands to reason to evaluate social

control at a level where effects may differ.

24

Research has demonstrated that social control is a function of social context. Smith,

Visher, and Davidson (1984) included a measurement of neighborhood poverty in a multivariate

analysis exploring the antecedents of arrest across sixty residential neighborhoods. Their

analysis shows that the probability of arrests by police increased as the poverty level of the

neighborhood increased. Smith (1986) analysis on the effects of 11 neighborhood characteristics

(e.g., poverty, residential mobility, racial heterogeneity) identified that: police are more likely to

stop suspicious people in racially heterogeneous neighborhoods; in neighborhoods of lower

socioeconomic status, the odds of arrest were higher; and there was an inverse relationship

between neighborhood crime rates and the likelihood of police officers taking a crime report.

Smith (1986: 337) concludes that “officers act differently in different neighborhood contexts.”

Terrill and Reisig (2003) found that police use of force was a function of the

neighborhood context. More specifically, Terril and Reisig’s analysis included a factor of

neighborhood poverty consisting of percent in poverty, percent unemployed, percent of female-

headed families, and percent black and found a significant, positive relationship between

neighborhood poverty and police use of force, as well as neighborhood crime level and police

use of force. The totality of these findings has spawned the advance of a theory that

acknowledges community characteristics when explaining police action (Klinger 1997).

Moreover, this research supports the arguments made in this dissertation that past conflict

perspective studies using the city as a unit of analysis may have masked observable effects.

THE CURRENT STUDY

Clearly the inability to provide a direct measure of threat and addressing aggregation bias

are important considerations when testing the threat and benign neglect hypotheses. The current

research utilizes a quasi-experimental, time series design to account for the occurrence of

25

Hurricane Katrina and the resulting displacement of citizens to Houston and determine whether

or not this event impacted arrest levels of various police districts. I believe the use of citizen

displacement by Hurricane Katrina constitutes a more direct measure of threat, and inspection of

police districts rather than just the city addresses the issue of aggregation bias.

Citizens were ordered to evacuate New Orleans on short notice, and eventually Houston

housed approximately 250,000 evacuees (Berger 2006). I believe that the abrupt nature and

magnitude of citizen displacement constitutes a threatening event for both the displaced citizens

as well as the citizens that make up communities that now must house a larger population. By

accounting for the displacement of citizens by Hurricane Katrina, this research provides a more

direct measure of threat than the traditional size of minority population.

Furthermore, data on clearance levels will be inspected by police division, not just at the

city level of analysis. The use of police divisions allows for the characteristics of the each

division to be accounted for. As police behavior can be influenced by the divisions within which

they operate (Klinger 1997; Klinger 2004; Smith 1986; Smith, Visher, and Davidson 1984;

Terrill and Reisig 2003), it is important to account for changes in clearances within a city and

across divisions. The time series design of this study allows for this to occur. Moreover,

because displaced citizens were housed within specific police divisions, this allows for specific

predictions on which areas of Houston should experience threat or benign neglect.

By directly accounting for the occurrence of a threatening event to all populations and

evaluating the effects of this event within a city, this paper is positioned to provide a more direct

test of the threat hypothesis and benign neglect hypothesis.

26

CHAPTER THREE

SOCIAL CONTEXT AND THE CRIME-ARREST RELATIONSHIP: EVALUATING THE PREDICTIONS OF THE CONFLICT PERSPECTIVE

INTRODUCTION

The previous chapter was devoted to the predictions of the conflict perspective’s threat

and benign neglect hypotheses, and presented the argument that issues of measurement and

aggregation bias may play a role in the proper identification of the level at which threat and

benign neglect occur. Central to the argument was the role of social context. Succinctly stated,

Chapter Two argued that it may be important to take into account characteristics of the social

context when evaluating conflict theory hypotheses. This chapter extends the argument that

social context is an important component of the conflict perspective to research on the crime-

arrest relationship.

It has long been posited that crimes and arrests are interlinked (Becker 1968; Gibbs 1975;

Tittle 1980). Three findings from the research on the crime-arrest relationship are paramount to

the present discussion: (1) most studies rely on the predictions of hypotheses derived from

economic theories and fail to take into account the predictions of the conflict perspective; (2)

results from previous research appear to be a function of the methodology used to examine the

reciprocal relationship between crimes and arrests; and (3) the role of social context appears to

be an important part of the crime-arrest relationship.

There are many hypotheses surrounding this relationship. Because the current study is

concerned with the macro level crime-arrest relationship, attention will be paid to the relevant

macro-social literature. This chapter is presented accordingly: first, a review of the theoretical

predictions regarding the crime and arrest relationship is discussed. This is provided so in order

27

to demonstrate how the predictions of the conflict perspective can be incorporated into the

research on the crime-arrest relationship. Second, a review of the research on the reciprocal

relationship between crimes and arrests is presented. This section will organize the relevant

literature around the methodology used to examine the crime-arrest relationship (i.e., cross

sectional or longitudinal). This vital section demonstrates how past research has relied on

economic theories of crime, although, as demonstrated in the first section of this chapter, the

conflict perspective may have utility in explaining the crime-arrest relationship. This section

also demonstrates how the methodology of past research on the crime-arrest relationship has

driven findings. Finally, an argument is offered on how threat may influence the social context

of an area and may be useful in examining the relationship between crime and arrests.

THE CAUSAL MECHANISMS UNDERLYING THE CRIME-ARREST

RELATIONSHIP

The attempt to identify the causal linkage between crimes and arrest has a long history

(see Geerken and Gove 1977). Much of this history surrounds an attempt to unearth the true

causal ordering of the relationship, as well as the direction of this relationship. For example, one

can imagine how crimes would affect arrests (e.g., as crimes go up, police respond with more

arrests). One could also picture how arrests affect crimes (e.g., as arrests increase, criminals

become more aware and crime decreases). In the case of the direction of the relationship, it is

viable to picture a situation in which crimes exert a positive influence on arrests, but it is also

likely that crimes could exert a negative impact on arrests, for example. The discussions below

will illustrate hypotheses dedicated to explaining the relationship between arrests and crimes.

Economic theory has been at the forefront of reasoning behind research into this

relationship (Becker 1968; Ehrlich 1973; Schmidt and Witte 1984). Economic theory

28

approaches the relationship between crime and arrests using a precise model based on a general

economic perspective. Namely, economic theory assumes that individuals have relatively stable

interests. Behavior exhibited by individuals is a result of this stability and the weighing of costs

versus benefits to alternative behaviors. Individuals choose to exhibit behavior that maximizes

the ratio of benefits to costs. Therefore, individuals will not exhibit particular behaviors when

the costs of that behavior outweigh the benefits of displaying that behavior (see, Becker 1968).

The role of crime control (e.g., arrests), from an economic standpoint, is to raise the costs

of criminal behavior so that individuals will choose to exhibit non-criminal behavior because the

ratio of benefits to costs is reduced. Failure to increase the costs of crime will result in more

criminal behavior. Thus, the crime arrest relationship can be viewed as part of an overall general

model (see, Liska 1987). Further, crime control can be affected by workload and resources (see

Phillips and Votey 1981; Liska et al. 1985). The following section details predictions of an

economic approach to the crime arrest research.

The first hypothesis is termed the public choice hypothesis. It predicts that increases in

crime lead to increases in arrests. This hypothesis makes the assumptions that public citizens are

knowledgeable about the costs and consequences of municipal functioning (Borcherding and

Deacon 1972: 892) and the polity respond to voter outcry (Tridimas 2001: 300). Therefore, this

hypothesis states that increases in crime lead to citizens’ placing more pressure on the

government (i.e., police, politicians) to crack down on crime in their area. As an example,

politicians, serving at the pleasure of voters, may cry out for more crime control because of

pressure from the public. This may then result in more arrests as crime increases (Borcherding

and Deacon 1972; Deacon 1978; Tridimas 2001).

29

Another hypothesis put forth by economic theory predicts that increases in crime lead to

decreases in clearances. This hypothesis is known as the overload hypothesis (Chamlin and

Brandl 1998; Fisher and Nagin 1978; Geerken and Gove 1977; Schulenberg 2003). The

overload hypothesis predicts that increases in crime can overwhelm the capacities of law

enforcement. When police capacities have reached their limit, the ability to respond to other

crimes is greatly reduced. Therefore, the lessening of police resources leads to fewer aggregate

arrests (Fisher and Nagin 1978; Geerken and Gove 1977).

Economic theory also hypothesizes how arrests can influence crime, the deterrence

hypothesis (in general, see Becker 1968; Geerken and Gove 1977; Gibbs 1975; Lynch 1999;

Nagin 1998; Paternoster 1987; Petersilia 1998; Pratt, Cullen, Blevins, Daigle, and Madensen

2006). The deterrence hypothesis also operates under a utilitarianism approach by arguing that

humans are rational actors who base their decisions on the maximization of profit. Because

rational actors weigh the costs of exhibiting a behavior against the benefits of exhibiting the

same behavior, an increase in arrest (i.e., the certainty of punishment) should sway rational

actors away from performing criminal behaviors. The deterrence hypothesis argues that

increases in arrests (cost) make crime a less profitable option and, therefore, leads to a decrease

in crime (Becker 1968; Geerken and Gove 1977; Gibbs 1975).

Another hypothesis, the incapacitation hypothesis, makes a similar prediction of the

affect of punishment (e.g., arrests) on crimes (in general, see DiIulio and Piehl 1991; Geerken

and Gove 1977; Gottfredson and Gottfredson 1994; Marvel and Moody 1994; Petersilia 1992;

Piehl and DiIulio 1995; Sabol and Lynch 2000; Spelman 2000; Visher 1987; Zimring and

Hawkins 1988). Increases in arrests lead to the removal of offenders from the social order,

thereby reducing the amount of crime that could have been committed had these individuals not

30

been apprehended. To the extent that an increase in arrests removes individuals from society

and they cannot return to the general public while awaiting criminal justice proceedings, the

aggregate level of crime should decrease (Geerken and Gove 1977).

The hypotheses outlined above provide predictions on the reciprocal relationship between

arrests and crimes under the umbrella of economic theory. As will be discussed in the

subsequent section, the vast majority (all but one) of the macro-social studies on the crime-arrest

relationship evaluate the crime-arrest relationship using one or more of these hypotheses. Far

fewer tests have used the predictions of the conflict perspective to inform research on the

reciprocal relationship between arrests and crimes. The following paragraphs will illustrate how

the predictions of the threat hypothesis and benign neglect hypothesis can be utilized to better

understand the crime-arrest relationship.

As discussed in Chapter Two, the conflict perspective conceptualizes crime control as a

tool used by elites to advance their own interests (Black 1976; Blalock 1967; Quinney 1970,

1977; Turk 1969). This view-point argues that culturally dissimilar groups are viewed as threats

to the social order by elites and law enforcement practices are used as a mechanism to control

these threatening populations (Turk 1969). The threat and benign neglect hypotheses are two

predictions used to explain the use of social control. The threat hypothesis predicts an increase

in arrests when the status of the social elites is threatened. The benign neglect hypothesis

predicts a decrease in arrests when the non-elite are threatened. Therefore, the difference

between an increase or a decrease in social control is the group that is experiencing threat.

The utility of the threat and benign neglect hypotheses role in the crime-arrest

relationship is clear. If the displacement of citizens by Hurricane Katrina to Houston, Texas,

increased fear of crime among elite populations (i.e., the group experiencing threat), this would

31

be reflected in a positive association between crimes and arrests (the threat hypothesis). If the

group experiencing threat were the non-elite populations, then the benign neglect hypothesis

would be reflected by a negative association between crime and arrests (see Chamlin and Myer

2009).

The relationship and direction between crime and arrests has received significant

empirical examination. The following section reviews macro-level research on this relationship.

Two issues are relevant—methodology used and social context. As such, the section that follows

will begin with a discussion on cross-sectional research, followed by discussions on longitudinal

research. Finally, research on the role of social context in the examination of the crime-arrest

relationship is presented.

A REVIEW OF THE CRIME-ARREST LITERATURE

Examination of the crime-arrest relationship has typically employed two different designs

in an attempt to investigate the reciprocal nature of crimes and arrests: cross sectional designs

and longitudinal designs. Research on the reciprocal relationship between crimes and arrests

began under examination of cross-sectional data. This section begins with a review of research

on the crime-arrest association with cross-sectional data.

Sjoquist (1973) used data from 53 municipalities with populations between 25,000 and

200,000 in 1960 to examine 1968 property crimes (i.e., burglary, larceny, and robbery) and

arrests and convictions reported to the FBI. Multiple regression was used to estimate the effects

of arrests on crimes. Results demonstrated that an increase in the probability of arrest and

conviction was significantly related to a decrease in property crime. This result offers support

for the deterrence hypothesis. Tittle and Rowe (1974) also revealed support for the deterrence

hypothesis. Using data from cities and counties with populations over 2,500, the authors found a

32

significant negative correlation between certainty of arrest and crime rates for counties (-.65) and

cities (-.19).

Geerken and Gove (1977) used data on 65 SMSAs with populations over 500,000. For

each of these units, the authors combined the reported number of crimes (i.e., homicide and non-

negligent manslaughter, aggravated assault, rape, robbery, burglary, larceny, and auto theft) for

the years 1970, 1971, and 1973. For each of these indices, Geerken and Gove then created a

certainty of arrest measure by dividing the number of crimes cleared by the number of crimes

reported. These two measures were then correlated to determine if any significant relationship

existed. Geerken and Gove found a significant negative association for all crimes (r = -.25), auto

theft (r = -.65), larceny (r = -.41), robbery (r = -.40), burglary (r = -.22), and rape (r = -.26).

There were no significant findings for either assault or homicide. Thus, the authors argue their

findings, at least in regards to economic crimes, support the deterrence hypothesis.

Brown (1978) analyzed crime and arrest data in California cities and counties. In regards

to the California counties (n=58), Brown found a negative association between the arrest

clearance rate and the crime rate (r = -.39). When cities in California were the unit of analysis (n

= 114), a negative association between arrest probability and crime rate also emerged (r = -.17),

although smaller than the counties measure of association.

Using data from 35 large American cities in 1975, Wilson and Boland (1978) used two-

stage least squares regression to examine the crime arrest relationship. Their analysis revealed a

significant negative relationship between the robbery crime rate and the robbery arrest ratio

while controlling for age, sex, race, unemployment, and population. The same findings could

not be replicated for burglary or auto theft.

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While the above studies demonstrate that the crimes and arrests are in fact related to one

another, the above cross-sectional research fails to do is explain the mechanisms underlying this

relationship. The above research cannot articulate whether crimes influence arrest, or whether

arrest influence crimes. While one could employ simultaneous equations to unravel the

reciprocal effects between crimes and arrests, it would involve the ability to identify and employ

instrumental variables that allow one to uniquely identify the two equations (Hanushek and

Jackson 1977). However, there has yet to be an identifiable instrumental macro-level predictor

that affects one of these variables and not the other (for example, see Fisher and Nagin 1978;

Greenberg and Kessler 1982; Nagin 1978). In short, cross-sectional designs investigating this

relationship are unable to deal with simultaneous equation bias (Greenberg and Kessler 1982).

As Logan (1975) laments, cross-sectional designs fail to divulge the direction of the crime-arrest

relationship.

In an attempt to unearth the proper temporal order of the crime-arrest relationship, many

studies began to use longitudinal designs. Specifically, researchers employed the technique of

multi-wave panel designs to examine the reciprocal relationship between arrests and crimes.

Logan (1975) used 1964 to 1968 state level data to examine the effect of arrest clearances on

crimes. Arrest clearance was calculated as the number of crimes cleared by arrest divided by the

number of crimes known to police. Seven indices were created for each of the FBI Type I

crimes (i.e., homicide, rape, robbery, aggravated assault, burglary, larceny, and auto theft).

Logan employed a two-wave panel design for successive years to examine a lagged and

immediate relationship between yearly measures of crime and arrest. Findings from Logan’s

analyses reveal no evidence of any relationship between crimes and arrests or arrests and crimes.

34

Greenberg, Kessler, and Logan (1979) used a three-wave panel design on yearly arrest

clearance and offense rates for 98 U.S. cities for the years 1964 to 1970. As above, the panel

design was used to examine possible lagged and instantaneous effects of the reciprocal

relationship. Of the 24 estimated coefficients examining the effect of crime on arrest, only two

were significant (assault and homicide). However, the assault coefficient was small and unstable

and the homicide coefficient was not in the predictive direction (i.e., positively related). For the

24 coefficients in their model predicting the effect of arrest on crime, no coefficients emerged as

significant predictors. In an extension of this analysis, Greenberg and Kessler (1982) again used

a three-wave panel design on the same data, this time controlling for 12 structural predictors.

The results of these analyses provided few estimates reaching statistical significance, and were

thus not noticeably different from the above study.

The above panel designs were an attempt to address the troubles cross-sectional designs

had in determining the reciprocal relationship between crimes and arrest, and these studies were

unable to replicate the findings of cross-sectional studies. However, panel studies are not

without their own limitations. Namely, the panel studies and the data used place restrictions on

the estimation of the lag structure between crime and arrests. The studies by Logan (1975),

Greenberg et al. (1979), and Greenberg and Kessler (1982) use yearly data. If the relationship

between arrests and crimes is distinguished by yearly lags, then the techniques used are

satisfactory. However, there is reason to believe that the reciprocal relationship between crimes

and arrests occurs at a smaller lag (see, for example, Bursik, Grasmick, and Chamlin 1990;

Chamlin 1988; Chamlin, Grasmick, Bursik, and Cochran 1992). Thus, the inability of panel

designs to provide evidence of a reciprocal relationship may be due to model misspecification.

35

Chamlin (1988) addressed the identification of a lagged relationship through the use of

auto regressive integrated moving average (ARIMA) techniques. The use of ARIMA techniques

does not require one to make rigid assumptions about the potential lag structure between arrests

and crimes. Rather, bivariate ARIMA analyses allow the data to determine the lag structure.

This is beneficial because no theory specifies precisely the lag at which crimes affect arrests or

vice versa (Greenberg and Kessler 1982; Loftin and McDowall 1982). To this end, Chamlin

(1988) uses monthly data for both Oklahoma City and Tulsa spanning 1967 to 1980 for the

offense categories of robbery, burglary, larceny, and auto theft. Chamlin found that arrests have

a negative effect (with a 1 month lag) on crime for robbery, but not for the remaining crimes.

This is in partial support of the deterrence hypothesis. However, there was no lagged

relationship evidenced for the effect of crime on arrests for either city on any of the offense

types.

In a further examination of the lag structure between arrests and crimes, Chamlin and

colleagues (1992) evaluated the reciprocal relationship between arrests and crimes for the

individual offenses of robbery, burglary, larceny, and auto theft in Oklahoma City. Each of the

series was examined at the monthly, quarterly, and semiannual time aggregation. Bivariate

ARIMA analyses indicated: (1) crime had no significant lagged effects on arrests; (2) monthly

levels of arrest had significant negative effects on robbery crimes and auto theft at the one month

lag; and (3) quarterly arrests had a negative effect on larceny crimes at the 1 quarter lag. Thus,

the results support a short term deterrent effect.

Bursik, Grasmick, and Chamlin (1990) argue that prior examinations of the reciprocal

relationship between crimes and arrests are not only hindered by the inflexibility in examining

the proper lag structure, but they are also confounded with aggregation bias. Greenberg and

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colleagues (1981) and Green