Life in the Fast Lane: Drugs,Hedonistic Lifestyles,and Economic Crime

Abstract

We examine whether economic crimes are committed to fund drug addiction and/or to fund a hedonistic lifestyle. To address motivation, we estimate reciprocal relationships between economic crime and drug use and between economic crime and hedonistic activity generally. Analyses are based on event calendar data collected from 715 male offenders. Both simultaneous (within-month) relationships and effects involving a 1-month lag are examined. Offenders were more likely to engage in property crime and drug dealing during months in which they used hard drugs, marijuana, and alcohol, and when they engaged in more frequent unstructured socializing. The results from lagged models suggested that hedonistic activities lead to economic crime and economic crime creates opportunities for more frequent hedonistic activity.

Keywords

drug dealing property crime routine activities unstructured socializing alcohol

Introduction

Qualitative research suggests that offenders often commit property crime to fund their hedonistic or “party” lifestyle (e.g., Matza & Sykes, 1961; Shover, 1996; Wright & Decker, 1997). Offenders with this lifestyle spend a great deal of time engaged in pleasurable activities that involve nonessential consumption rather than satisfaction of basic needs or family requirements (Walsh, 1986). They frequently use recreational drugs, drink to intoxication, and spend extreme amounts of time socializing with peers in unstructured activities. A separate literature suggests that offenders often engage in property crime to fund their addictive use of serious drugs (e.g., Goldstein, 1985). This perspective implies that serious drug use creates special financial needs over and above the financial requirements of a hedonistic lifestyle. Both perspectives imply reciprocal processes: (a) A hedonistic lifestyle and/or drug addiction leads to economic crime and (b) the money that offenders gain from economic crimes creates an opportunity for increased hedonistic activity and/or addictive drug abuse.

The goal of this research is to present a quantitative assessment of these patterns using monthly event calendar data. We examine whether drug use, alcohol use, and unstructured socializing are associated with property crime and drug dealing in a sample of male criminal offenders. We also examine whether the relationship between serious drug use and economic crime is particularly strong (Felson & Staff, 2015). Our focus, then, is on the ebbs and flows of drug use and economic crime among offenders rather than on onset or desistance.

To increase confidence in causal inferences about the contributions of these processes, we estimate relationships between economic crime, substance use, and unstructured socializing through within-person analyses that control for the spurious contribution of preexisting individual differences (Allison, 1990, 2009). Methods that address this form of spuriousness are critical in this area of research because many of the risk factors for these behaviors are likely to be the same (Goode, 1997; Hanlon, Kinlock, & Nurco, 1991).¹ For example, family background, self-control, and other stable individual differences may account for much of the relationship (e.g., Gottfredson & Hirschi, 1990). It may also be that involvement in criminal subcultures or particular routine activities lead to drug use and other crime (e.g., M. Felson, 1998; White & Gorman, 2000). To reduce the likelihood of spuriousness, we capitalize on repeated measures over time and apply a version of fixed effects analysis. The within-person analyses that result control for all stable individual differences (whether measured or not). We also include controls for several relevant time varying covariates. Finally, as a step toward addressing the issue of causal direction, we use lagged explanatory variables in some analyses.

The Hedonistic Motive

The image of a hedonistic lifestyle among offenders implies that the effect of drug use on economic crime is an instance of a more general process. In this scenario, frequent engagement in a variety of hedonistic activities motivates individuals to commit economic crime to pay for those activities.

The role of hedonism is emphasized in the ethnographic literature on economically motivated crime by serious offenders. These studies consistently find that these offenders commit economic crime to fund their hedonistic lifestyle (e.g., Fleisher, 1995; Shover, 1996; Shover & Honaker, 1992; Walsh, 1986; Wright & Decker, 1997). Male offenders typically use recreational drugs, engage in frequent drinking, purchase drinks and gifts for women, gamble, and ostentatiously display luxury items. Because these offenders do not have enough income from legitimate sources to cover the expenses of such a hedonistic lifestyle, they engage in income producing crimes. They become involved in a cycle in which they “party,” run out of money, and then commit crimes to solve their financial problem. They are responding to a crisis or predicament, albeit one of their own making. From this perspective, illegal drug use, heavy alcohol use, and intensive unstructured socializing all lead to economic crime.²

Wright and Decker (1997) found evidence that a hedonistic lifestyle leads to economic crime in their ethnographic study of armed robbers in St. Louis (see also, Jacobs & Wright, 1999; Wright & Decker, 1994). The robbers, who were usually unemployed, committed their offenses to support their hedonistic lifestyle when they ran out of funds. De Haan and Vos (2003) found that street robbers in Amsterdam often “spent all their money on clubbing and luxurious consumer goods” (p. 36). Offenders felt constant pressure to commit more robberies because of their gambling and their unrestrained consumption of sex, drugs, and alcohol. Similar arguments have been used to explain the motivation for burglary (Wright & Decker, 1994), auto theft (Copes, 2003), identity theft (Copes & Vieraitis, 2008), property crime generally (Shover & Honaker, 1992), and drug dealing (Jacques & Wright, 2015). According to some of criminology’s most accomplished ethnographers, a hedonistic lifestyle is a fundamental cause of economic crime. A theme that is emphasized in so many ethnographic studies deserves attention from quantitative researchers.

A hedonistic lifestyle also has indirect effects that are conducive to crime according to Shover and Honaker (1992). Time schedules for work and a hedonistic lifestyle are often incompatible. Staying out until late at night drinking and using drugs makes it difficult to get to work on time in the morning. These constraints may lead some offenders to avoid conventional jobs. In addition, the pursuit of a hedonistic lifestyle may interfere with social bonds to conventional others, leading to lower external controls on criminal activity (Hirschi, 1969; Thompson & Uggen, 2012).

In their classic discussion of delinquency, Matza and Sykes (1961) also emphasized the importance of hedonistic pursuits. They argued that thrill seeking and leisure activities reflect subterranean values that exist side by side with more dominant values associated with routine and work. Delinquents share an interest in “having fun” with middle-class adults but they give it more emphasis. Adult offenders may be similar to delinquents in their pursuit of a hedonistic lifestyle, and as adults they have the independence to do so in a more extreme fashion.

Interestingly, the use of economic crime to fund hedonistic activity is consistent with classic strain theory’s emphasis on disjunctions between aspirations and expectations (Cloward & Ohlin, 1960; Merton, 1938). Some authors have suggested that crime reflects unsatisfied desires for “easy money” rather than unsatisfied desires for conventional status or economic success (Bernard, 1984; Farnworth & Leiber, 1989). A blocked opportunity approach to strain theory is quite compatible with the idea that crime flows from a hedonistic lifestyle.

The literature on unstructured socialization is also relevant to discussions of the effect of a hedonistic lifestyle on economic crime. Osgood, Wilson, Bachman, O’Malley, and Johnston (1996) defined unstructured socializing as time spent in leisure activities with peers, away from authority figures obligated to maintain order, and with no agenda for how the time will be spent. This is a common activity that most people engage in at least occasionally (Osgood & Lee, 1993), but even minor offenders spend much more time this way than nonoffenders (Osgood et al., 1996). Evidence suggests that these activities increase the opportunity for criminal behavior and substance use (Hoeben, Meldrum, Walker, & Young, 2016; Osgood et al., 1996). The qualitative literature discussed above suggests another criminogenic effect of an extreme hedonistic lifestyle: the financial pressure that results from its cost.

Studies with strong research designs to control for spuriousness have provided evidence of the influence of unstructured socializing on crime. Osgood and colleagues’ (1996) original study used a longitudinal fixed effects analysis to demonstrate the relationship, and Meldrum and Barnes (2017) obtained the same results using a twin sample that controlled for genetic confounds. Bernasco, Ruiter, Bruinsma, Pauwels, and Weerman (2013) applied a within-person analysis to time diary data to establish that offenses were heavily concentrated during unstructured socializing.

The Drug Money Motive

We suggested above that the effects of drug use on economic crime may be one instance of the effect of a hedonistic lifestyle. However, Goldstein’s (1985) influential description of drug effects as “economic-compulsive” implies that the effect of drug use is something special (see also, Dickinson, 2015). His approach implies that offenders who are dependent on or addicted to drugs are particularly likely to commit economic crimes, and that their behavior is likely to be compulsive. Infrequent use of serious drugs and use of minor drugs (e.g., marijuana) would not require large enough sums to produce the sort of economic compulsion envisioned by Goldstein. Evidence comes from a study in which inmates who had committed economic crimes (property and drug offenses) were asked whether they committed their offense to get money for drugs (Felson & Staff, 2015). It found that drug money was a more likely motive among daily users of heroin, crack cocaine, and powdered cocaine than among offenders who used these drugs less frequently and among users of marijuana. The results suggested that addiction was more likely to lead to economic crime than recreational drug use.

The drug literature suggests that drug addiction motivates individuals to commit economic crime to pay for their drugs. The hypothesis is supported by studies that find that individuals have higher rates of criminality during periods of frequent use and lower rates during periods of abstinence and low use (e.g., Collins, Hubbard, & Rachal, 1985; Fagan, 1989; French et al., 2000; Green, Doherty, Stuart, & Ensminger, 2010; Johnson, 2004; Nurco, Kinlock, Hanlon, & Ball, 1988). For example, Horney, Osgood, and Marshall (1995) reported that offenders were more likely to engage in property crime and drug trafficking during months in which they used illegal drugs. The relationship was much stronger for trafficking. Uggen and Thompson (2003) studied 5,000 released offenders, addicts, and school dropouts. They found that illegal earnings were US$500 to US$700 higher during months following serious drug use, net of all time-stable individual differences. Finally, Thompson and Uggen (2012) found generally similar relationships between drug use and income from drug sales and between drug use and income from other economic crimes.

Bennett, Holloway, and Farrington’s (2008) meta-analysis of studies using cross-sectional data also provides evidence suggesting addiction may have special effects. They found that the drug–crime relationship was strongest for crack cocaine, followed in order by heroin, powder cocaine, amphetamines, and marijuana. These cross-sectional relationships, however, could be spurious, due to preexisting individual differences. The individual differences that lead to serious drug use are also likely to lead to other crimes. In addition, these studies did not examine whether it is only the most frequent drug users—that is, those with addictions—who commit more economic crime.

Effects of Economic Crime on Opportunity

Numerous studies testify to the strong effects of opportunity and other situational factors on crime and other human behavior (e.g., M. Felson, 1998; Horney, 2006). In criminology, the focus has been on opportunity for crime produced by proximity between offenders, victims, and guardians (e.g., M. Felson, 1998). We suggest that, for expensive activities involving consumption, economic opportunity may also be important. According to this perspective, the money earned by economic offenders gives them greater opportunity to engage in hedonistic activity. They can better afford to use drugs, frequent bars, drink to excess, and spend money on potential sexual partners. As money is fungible (i.e., interchangeable) increases in legitimate income should have similar effects. Thus, teenage employment is associated with higher rates of drug use and alcohol consumption, at least during the summer (e.g., Paternoster, Bushway, Apel, & Brame, 2003). However, it may be that offenders engage in mental accounting where they have a psychologically different budget for their hedonistic activity (e.g., Thaler, 2015). People sometimes treat money differently, depending on its origin and intended use. Offenders may treat profits from drug dealing in a separate mental account for purchasing drugs. They may be more willing to spend profits from theft on hedonistic activity if they view them as easy money not hard-earned pay (legal earnings).

Economic opportunity (like other opportunity factors) should be particularly likely to increase consumption among offenders given that they tend to have low self-control (Gottfredson & Hirschi, 1990; Mischel, Ebbesen, & Raskoff Zeiss, 1972). Offenders may be just as opportunistic in their consumption as they are in their criminal behavior. The availability of drugs and alcohol, like the availability of unhealthy food at home, creates temptations that lead to greater consumption. Offenders are unlikely to save their money for rent or other legitimate expenses, and more likely to stay out late carousing. One would expect the temptation to be particularly strong for drug dealers as they have large amounts of drugs in their possession. In addition, according to what might be called the “potato chip principle,” offenders find it difficult to stop drug and alcohol use once they start (R. Felson, cited in M. Felson, 1998). The pattern has been shown in the use of alcohol (e.g., Baumeister, Heatherton, & Tice, 1994).

A reciprocal relationship between drug use and economic crime could reflect a single integrated process, consistent with drug addiction or a hedonistic motive. For example, the offender commits a robbery to get drug money and then uses that money to purchase drugs. In this case, offenders are forward-looking when they commit their offenses. A comparable reciprocal relationship between unstructured socializing and economic crime would also be consistent with the hedonistic motive.

On the contrary, it could be that drug use and hedonistic activity are consequences of economic crime but not its motivation. Offenders commit economic crimes to get money, with no particular purpose in mind. Then they use some of the proceeds to purchase drugs or go “out on the town.” It could be that this process entirely accounts for the finding from within-person studies that drug use and economic crime increase at the same time. In that case, the relationship would have nothing to do with the tendency for offenders to commit economic crime to purchase drugs. The relationship would instead reflect the effect of economic crime on the opportunity to purchase drugs—a reversal in causal direction.³

We are not aware of any quantitative research on the effects of economic opportunity on drug use or other hedonistic activity. Qualitative research, however, suggests that drug dealing leads to increased drug use (e.g., Contreras, 2012; Moyle & Coomber, 2015) and that economic crime activity preceded increases in heroin use (Faupel, 1991).⁴ Clearly, quantitative research is needed to address the issue of causality.

Current Study

In the current study, we examine the reciprocal relationships between economic crimes (property crime and selling drugs) and drug use, alcohol use, and unstructured socializing. We analyze calendar data from recently incarcerated offenders using a hybrid fixed effect model of within-individual change (Allison, 2009) in behavior over a 36-month period. Our first set of analyses is based on relationships between variables measured for the same month. Contemporaneous fixed effects models were used in prior research, so these first analyses allow us to determine if we achieve similar results. We assume that this time period is a reasonably accurate reflection of the time frame over which any of these variables would produce change in one another. We expect offenders to commit economic crime when they have an urgent need for money and to spend the money quickly when they have it.

Next, we address the issue of causal direction by using a 1-month time lag between predictors and outcome variables. The time lag reduces the likelihood that reverse causation or time-varying factors can explain the results. However, such analyses provide a conservative test because they probably impose a longer causal lag between these variables than is accurate. Our lagged analyses estimate the effects of drug use and other hedonistic activities on crime in the following month.

According to the hedonistic motive hypothesis, the relationship between drug use and economic crime reflects a more general causal process. Offenders who have a hedonistic lifestyle need money to finance it, and so they commit economic crime. According to this perspective, unstructured socializing, alcohol use, marijuana use, and both the frequent and infrequent use of hard drugs should be associated with economic crime in the following month. The frequent use of hard drugs should have an effect, but it should not be the only effect. In addition, a hedonistic lifestyle does not necessarily imply that an individual engages in every one of the recreational activities we include. For example, some offenders might go out every night and engage in heavy drinking but have no interest in drugs.

According to the addiction hypothesis, the daily use of hard drugs should give a particularly strong boost to the tendency to engage in economic crime. We assess this by examining the effect of daily use, above and beyond any effect of an ordinal measure of hard drug use that represents a broader range of frequency. The hypothesis follows from Goldstein’s description of these offenses as “economic-compulsive.” We recognize that in some cases the daily use of hard drugs involves recreational use rather than addiction or a serious drug problem. We cannot distinguish these two motives, but we can determine whether such daily use has a special effect or whether its effect is only one more step on a continuum of the frequency of use.

According to the economic opportunity hypothesis, economic crime leads to an increase in the offender’s drug use because the offender has the money to buy more drugs. Economic crimes should be related to drug use in the following month. In addition, selling drugs may have a stronger effect on drug use than does property crime as dealers are likely to have large quantities of drugs readily available. The economic opportunity hypothesis also implies economic crimes should have effects on hedonistic behavior generally. When offenders commit economic crimes, they have more money and they will spend it on their recreational activities. They are likely to engage in more unstructured socializing, drink more alcohol, and use more marijuana and hard drugs. From this perspective, economic crime has multiple behavioral consequences. A conceptual model that shows the relationships of interest is presented in Figure 1.

Figure 1.

Conceptual model.

Finally, we treat physical assault as an explanatory variable and substance use or unstructured socializing measures as outcomes. Assault should have no effect on the lifestyle variables as it is rarely an economic crime. If we find effects of economic crimes but not assault, it will provide further support for the idea that economic crime is producing economic opportunities.

Method

Our research uses the data of Horney’s (2001) Second Nebraska Inmate Study. The data have been used to study the role of guns in violent incidents (Wells & Horney, 2002) and the effects of stress on crime (R. B. Felson, Osgood, Horney, & Wiernik, 2012). The research design closely matches the First Nebraska Inmate Study, which was the basis of a well-known analysis of life events and offending (Horney et al., 1995). The sample included a random sample of male felons who were recently admitted to the state correctional system. The response rate was 90.4%. After omitting three cases with missing data on several measures, our sample included 715 male inmates. Our sample includes 21,831 person/months of data, after omitting months respondents were incarcerated, hospitalized, or otherwise not free in the community for at least half of the month.

Respondents completed a computerized interview that gathered monthly event history data for the 36 months prior to incarceration. The event history calendar method is useful for obtaining quantitative data based on relatively short time intervals when short-term effects are expected. As the method makes considerable demands on respondents’ memories, respondents are given valuable aids to recall to increase accuracy. Roberts and Horney’s (2010) review of the event calendar method offers strong support for its reliability and validity (see also, Sutton, 2010; Sutton, Bellair, Kowalski, Light, & Hutcherson, 2011). For extensive information about the sample, data collection procedures, and measures obtained, see Horney’s (2001) description of the study.

Inmate samples are well suited for assessing the relationship between criminal behavior and drug use and a hedonistic lifestyle. The respondents’ high rates of offending and the considerable instability of their lives provide the within-person variability necessary for detecting associations over short time spans.

Measures

The measure of property crime comes from respondents’ reports of how many times in each month they committed each of the following crimes: burglary, theft, robbery, robbery of a business, auto theft, forgery, and fraud. We treated each variable as a dichotomy, coded as “1” if the respondent had committed any of the offenses during the month, and “0” otherwise. Our measure of drug dealing was also treated as a dichotomy, based on a question in which respondents were asked whether or not they sold “drugs during this month.” Our measure of physical assault was also treated as a dichotomy.

We included two measures of illicit drug use. We distinguished marijuana use from other types of drug use because it is less addictive and less likely to pose a financial burden. The response categories for the marijuana use item ranged from 1 (never) to 4 (every day or almost daily). For hard drug use, we follow the lead of R. B. Felson et al. (2012), who constructed a measure based on the use of cocaine, crack, heroin, speed, acid, and other drugs. The measure reflected the frequency with which the respondent used whichever drug he used most often that month, using the same 4-point response scale used for marijuana. To detect any effect of addiction, we created a dummy variable coded 1 if the offender used the drug every day or almost every day and 0 otherwise.⁵

The measure of alcohol consumption was based on questions that asked whether and how often respondents were “using alcohol during this month” and, if they reported any use, the “number of drinks per day during this month.” We used this information to dichotomize the monthly reports as indicating heavy drinking versus less than heavy drinking, defining heavy drinking as consuming at least four drinks almost every day or at least 19 drinks in a day more than once per week.

Our measure of unstructured socializing is based on Osgood and colleagues’ (1996) concept of time spent in leisure activities with peers, away from authority figures obligated to maintain order, and with no agenda for how time will be spent. The measure derives from questions about participation in four types of activities: the number of nights spent out per week during the month (0-7), the frequency of hanging out with friends, cruising in an automobile, and going to bars (from 0 = never to 3 = almost every day). Our measure is the mean of the four responses after converting the “nights out” item to a 4-point scale to match the others (R. B. Felson et al., 2012).

Our statistical approach controls for stable individual differences (as discussed in the following section), so there is no need to control for stable variables such as race or initial age. Our control variables are therefore limited to variables that vary over time. Especially relevant are current life circumstances that research indicates may affect offending, drug and alcohol use (Horney et al., 1995), and unstructured socializing (Osgood & Lee, 1993). Following prior research, we therefore control for time-varying measures of whether the offender was employed, whether he was under justice system supervision (i.e., on probation or parole), and whether he lived with his wife, children, or a partner outside of marriage (Apel & Horney, 2017; R. B. Felson et al., 2012; Horney et al., 1995; Slocum, Simpson, & Smith, 2005).

Statistical Approach

We model our general statistical approach after previous studies using monthly event calendar data from serious offenders (R. B. Felson et al., 2012; Horney et al., 1995; Slocum et al., 2005). By focusing on within-individual change, we ensure that results reflect associations between change in the explanatory variable and change in the outcome variable, rather than stable individual differences (Osgood, 2010). This analytic strategy is one of the primary means of improving causal inference in nonexperimental data because it inherently controls for all time-stable effects of preexisting individual differences (Allison, 2009). The strategy is most widely known as a feature of fixed effects analysis of panel data (i.e., repeated measure longitudinal survey data), but as Allison (2009) has explained, properly specified random effects analyses and structural equation models also successfully implement this within-person analytic strategy. He labeled this approach “hybrid fixed effects” to emphasize that the results it produces support the same interpretation as conventional fixed effects analyses.

Our hybrid fixed effects model restricts estimates to within-person relationships through within-individual centering of explanatory variables (aka “group mean centering”) and controls for their individual means (Allison, 2009; Raudenbush & Bryk, 2002, p. 183). We estimated our models with the MLwiN 2.33 software (Rasbash, Steele, Browne, & Goldstein, 2015); months within individuals serve as Level 1 in the analysis and individuals as Level 2. To address potential dependence of the data due to residual mean differences among individuals and serial correlation, our models include variance components for individual intercepts and time trends (Raudenbush & Bryk, 2002).⁶

To ensure that findings are not attributable to confounding with a general pattern of escalating offending that culminated in the offense that led to inclusion in the sample, we control for overall time trends using the same approach and coding as previous work with these data (R. B. Felson et al., 2012; Horney et al., 1995). Specifically, we follow Horney et al. (1995) by allowing for a cubic function plus a dummy variable for the final month before incarceration, which provides considerable flexibility about the form of the time trend.⁷ We included the full cubic time function in all models because it functions as a control variable for ongoing, progressive change due to unmeasured factors (Osgood, 2010). Dropping nonsignificant components of time had negligible effect on results. We retained random effects for components of time up to the highest powers that proved significant.

Our analyses use linear multilevel regression models when unstructured socializing serves as the outcome measure because, as a mean across four items, it is relatively continuous, and its distribution is reasonably symmetric. We used ordinal logistic multilevel regression models to model hard drug use and marijuana use. The other outcome measures are all dichotomous, so we analyzed them through logistic multilevel regression models.

Results

Table 1 presents the descriptive statistics. Respondents committed property crimes in 13% of the months (combining all months for all respondents) and sold drugs in 31% of the months. Our analysis of the relationship between lifestyle variables and economic crime during the same month appears in Table 2. Here we treat economic crime as the dependent variable, though this choice is arbitrary because it is measured in the same month as the explanatory variables. If we assume that economic crime is an outcome, then our results generally support both the addiction hypothesis and the hedonistic motive hypothesis. All four lifestyle variables are associated with property crime and three of the four lifestyle variables are associated with selling drugs. Relationships are strongest for the associations of unstructured socializing with both drug dealing (a 95% increase in odds of dealing per unit on this 4-point scale) and property crime (86% increase in odds per unit) and of marijuana use with drug dealing (65% increase in odds per unit, also of a 4-point scale). The daily use of hard drugs has a positive relationship with property crime and drug dealing although neither coefficient is statistically significant at the .05 level. This coefficient adds to the association across lower levels of drugs, which is captured by the first coefficient for hard drug use. Figure 2 shows the full relationship between frequency of hard drug use and economic crime implied by the two coefficients. The relationships are curvilinear due to a boost in the effect with daily use, as captured by the second coefficient. The only result that does not support the hedonism hypothesis is the lack of an effect of heavy alcohol use on selling drugs. This absence of relationship partly stems from correlation with the other lifestyle measures; when they are not in the model, heavy alcohol use is significantly associated with selling drugs (b = .36, SE = 0.09, odds ratio [OR] = 1.52, p < .001).⁸

Table 1.

Variable Descriptives.

Variable	N	M	SD	Minimum	Maximum
Drug dealing	21,965	0.31	0.46	0	1
Property crime	21,965	0.13	0.34	0	1
Assault	21,965	0.08	0.28	0	1
Hard drug use	25,812	0.75	1.14	0	3
Daily use of hard drugs	25,812	0.14	0.35	0	1
Marijuana use	25,812	1.38	1.36	0	3
Frequent use of alcohol	21,965	0.23	0.42	0	1
Unstructured socializing	21,935	1.57	0.72	0	3
Lived with wife	21,965	0.16	0.36	0	1
Lived with significant other	21,962	0.25	0.44	0	1
Lived with kid(s)	21,965	0.19	0.39	0	1
Employed	21,868	0.69	0.46	0	1
Supervised	21,965	0.17	0.37	0	1
Time 1	25,812	−0.50	10.39	−18	17
Time 2	25,812	34.02	39.63	−10.9	119
Time 3	25,812	1,232.10	1,379.28	0.1	4,666

Table 2.

Hierarchical Logistic Regression Model Predicting Offenses (Contemporaneous Model; N = 21,835).

Variables	Drug dealing		Property crime
Variables	b	SE	b	SE
Within-person effects
Hard drug use	0.38***	0.06	0.25***	0.06
Daily use of hard drugs	0.27^†	0.16	0.21	0.17
Marijuana use	0.50***	0.05	0.14*	0.06
Frequent use of alcohol	0.06	0.12	0.42***	0.12
Unstructured socializing	0.67***	0.09	0.62***	0.10
Lived with wife	−0.10	0.21	0.09	0.21
Lived with significant other	0.26*	0.11	0.22*	0.11
Lived with kid(s)	−0.19	0.19	−0.40^†	0.21
Employed	−0.28***	0.08	−0.17*	0.08
Supervised	0.09	0.09	0.09	0.09
Time trend controls
Last month dummy	−0.07	0.13	0.38**	0.13
Time	0.02	0.02	0.04	0.02
Time²	−0.01	0.01	−0.02	0.01
Time³	0.00	0.00	0.00	0.00
	VC	SE	VC	SE
Random effects
Intercept	8.84***	0.69	10.72***	0.83
Time	0.016***	0.003	0.013***	0.003
Time²	0.001***	0.0002	0.001***	0.0002

Note. The equations included controls for individual means. b = multilevel logistic regression coefficient (log odds); VC = variance component.

†

p < .10. *p < .05. **p < .01. ***p < .001.

Figure 2.

Relationship of hard drug use to crime, relative to no use.

We observe only a few effects of the control variables. Offenders who are employed during the month are less likely to sell drugs and commit property crimes, consistent with Apel and Horney’s (2017) findings. The pattern suggests that having a legitimate source of income reduces the tendency to engage in economic crime. We also find that offenders who are living with a partner outside of marriage are more likely to commit economic crime. On the contrary, those who are living with their children are less likely to engage in property crime although the effect is not quite statistically significant.

Table 3 presents results from analyses that address the issue of causal direction by examining the effects of lifestyle variables on crime in the following month. The results for drug dealing provide support for the hedonist motivation hypothesis. The coefficient for the effect of the ordinal measure of hard drug use indicates an effect across the full range of use. The coefficient for daily use, an indicator of addiction, is small and statistically nonsignificant. For property crime, the pattern is more consistent with the addiction hypothesis. Daily use has an effect while the effect of the ordinal variable is small and not quite statistically significant. The effects, depicted in Figure 2, suggest a fairly linear effect for drug dealing and a curvilinear effect for property crime.

Table 3.

Hierarchical Logistic Regression Model Predicting Offenses With Lagged Predictors (N = 20,641).

Variables	Drug dealing		Property crime
Variables	b	SE	b	SE
Within-person effects
Hard drug use	0.35***	0.06	0.10	0.06
Daily use of hard drugs	0.13	0.17	0.41*	0.17
Marijuana use	0.42***	0.05	0.08	0.06
Frequent use of alcohol	0.01	0.12	0.44***	0.12
Unstructured socializing	0.57***	0.09	0.65***	0.10
Lived with wife	−0.10	0.21	0.02	0.22
Lived with significant other	0.19^†	0.11	0.19^†	0.11
Lived with kid(s)	−0.20	0.20	−0.39^†	0.22
Employed	−0.21**	0.08	−0.12	0.08
Supervised	0.14	0.09	0.11	0.09
Time trend controls
Last month dummy	−0.05	0.13	0.40**	0.13
Time	0.02	0.03	0.04	0.03
Time²	−0.01	0.02	−0.02	0.02
Time³	0.00	0.00	0.00	0.00
	VC	SD	VC	SD
Random effects
Intercept	8.66***	0.70	9.76***	0.81
Time	0.017***	0.003	0.014***	0.004
Time²	0.001***	0.0002	0.001***	0.0002

Note. The equations included controls for individual means. b = multilevel logistic regression coefficient (log odds); VC = variance component.

†

p < .10. *p < .05. **p < .01. ***p < .001.

Unstructured socializing has strong lagged effects on both economic crimes, with increases of 77% in the odds of drug dealing and 91% in the odds of property crime per unit of unstructured socializing. Marijuana use has a significant influence on drug dealing (OR = 1.52) but not property offending. However, it is significantly related to property offending when the other lifestyle measures are omitted from the equation (b = .22, SE = 0.05, OR = 1.25, p < .001). As in the simultaneous model, heavy alcohol use is related to property crime but not drug dealing. However, as before, when we exclude other measures of a hedonistic lifestyle, it is related to drug dealing (b = .31, SE = 10, OR = 1.36, p < .01).⁹

In Table 4, we examine the effects of crime on lifestyle variables in the following month. Recall that unstructured socializing is a continuous variable while the other dependent variables are dichotomies or ordered categories. The evidence from Table 4 provides support for the economic opportunity hypothesis. In months after offenders commit property crimes, they are more likely to use hard drugs and marijuana (increases of 34% and 21% in odds of higher categories on these ordinal measures), engage in heavy drinking (OR = 1.42), and have a higher frequency of unstructured socializing (.05 higher on the 4-point scale, with a standard deviation of 0.72). Dealing drugs affects three of the four hedonistic activities in the following month. It has no effect on heavy alcohol use. Effects of drug dealing on drug use are particularly strong, with OR of 2.20 for hard drug use, 2.12 for daily use of hard drugs, and 1.73 for marijuana use.

Table 4.

Hierarchical Regression Model Predicting Substance Use and Unstructured Socializing With Lagged Predictors (N = 20,641).

Variables	Hard drug use		Daily use of hard drugs		Marijuana use		Frequent use of alcohol		Unstructured socializing
	Ordinal logistic		Logistic		Ordinal logistic		Logistic		Ordinal logistic
	b	SE	b	SE	b	SE	b	SE	b	SE
Within-person effects
Drug dealing	0.79***	0.07	0.75***	0.11	0.55***	0.07	0.10	0.08	0.08***	0.01
Property crime	0.29***	0.08	0.35***	0.10	0.19*	0.07	0.20*	0.09	0.05***	0.01
Assault	0.08	0.07	0.05	0.09	0.06	0.06	0.03	0.07	0.01*	0.01
Hard drug use									0.03***	0.00
Daily use of hard drugs									0.01	0.01
Marijuana use									0.05***	0.00
Frequent use of alcohol									0.16***	0.01
Unstructured socializing	0.54***	0.07	0.43***	0.10	0.35***	0.06	0.60***	0.08
Lived with wife	0.01	0.14	−0.18	0.23	−0.05	0.12	0.07	0.15	−0.13***	0.02
Lived with significant other	0.03	0.08	−0.10	0.12	−0.13^†	0.08	0.06	0.09	−0.03***	0.01
Lived with kid(s)	−0.12	0.15	0.04	0.21	0.17	0.13	−0.46**	0.16	−0.03^†	0.02
Employed	0.03	0.06	−0.02	0.09	−0.06	0.06	0.02	0.07	0.01	0.01
Supervised	0.07	0.07	−0.03	0.10	−0.21***	0.06	−0.03	0.08	0.00	0.01
Time trend controls
Last month dummy	0.02	0.10	0.01	0.13	0.03	0.10	0.09	0.12	−0.01	0.01
Time	0.00	0.02	0.02	0.03	0.00	0.02	0.00	0.02	0.01*	0.00
Time²	0.01	0.01	0.00	0.02	0.00	0.01	0.00	0.01	0.00***	0.00
Time³	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00***	0.00
	VC	SD	VC	SD	VC	SD	VC	SD	VC	SD
Random effects
Intercept	5.11***	0.42	11.73***	0.93	3.41***	0.19	7.38***	0.57	0.60***	0.03
Time	0.009***	0.002	0.044***	0.006	0.001***	0.0001	0.001***	0.002	0.002***	0.0002
Time²	0.001***	0.000	0.002***	0.0003			0.000***	0.0002	0.0002*	0.00001
Time³
Level 1									0.032	0.0003

Note. The equations included controls for individual means. b = multilevel logistic regression coefficient (log odds); VC = variance component.

†

p < .10. *p < .05. **p < .01. ***p < .001.

Whereas economic crime predicts the lifestyle variables in the following month, physical assault does not. The fact that it has very weak and usually nonsignificant effects provides further support for our interpretation of the lagged effects of economic crime: For the four measures of substance use, ORs are less than 1.10, and the significant coefficient for unstructured socializing corresponds to a difference of less than 0.02 standard deviations.

Table 4 also demonstrates that substance use and unstructured socializing are mutually entwined, consistent with the idea of a hedonistic lifestyle. Unstructured socializing strongly affects all forms of substance use (increased odds by 42% to 82% per unit of unstructured socializing), and all forms of substance use predict unstructured socializing as well (other than a separate effect of daily use of hard drugs, beyond the contribution of the ordinal measure).

Discussion

Prior research suggests that offenders commit more property crime at times when their use of hard drugs increases. We found similar results using a contemporaneous hybrid fixed effects model: Offenders were more likely to engage in property crime during months in which they were frequent users of hard drugs. We extended the analysis to drug dealing, another economic crime, and found the same pattern. We also found that economic crimes were associated with other types of substance use and with levels of unstructured socializing. To test three potential explanations of these associations, we then estimated equations with lagged variables.

Hedonistic Motivation

We found consistent evidence in favor of the hedonism hypothesis in our analysis of the effects of unstructured socializing and use of substances other than hard drugs. The more frequently offenders engaged in unstructured socializing, the more likely they were to commit both types of economic crime in the following month. In addition, heavy drinkers were more likely to commit property crime in the following month, whereas users of hard drugs and marijuana engaged in more drug dealing. Note that our estimates only reveal the net effects of each of the lifestyle variables, controlling for the others, and that these variables are correlated with each other. For example, the correlation between marijuana use and unstructured socializing—both treated as metric variables—is r = .34. Each of the hedonistic lifestyle variables is significantly associated with both property crime and drug dealing when controls for the other aspects of the hedonistic lifestyle are left out of the equation.

Our evidence is consistent with evidence from ethnographic studies suggesting that a hedonistic lifestyle leads to economic crime (e.g., Shover, 1996; Wright & Decker, 1997). The pursuit of leisure is important to many people, particularly young people, and it may reflect a subterranean value held in the larger society (Matza & Sykes, 1961). It is of particular importance to offenders. We suggest that designers of programs seeking to reduce recidivism should consider offenders’ proclivity for hedonistic activity as a potentially fruitful domain for interventions. Another application might be in the study of the relationship between age and crime. The fact that interest in a hedonistic lifestyle declines with age may help explain desistance. In general, we believe that the effect of a hedonistic lifestyle on crime deserves more attention from criminologists.

For some of these effects, there are alternatives to our economic explanation. For example, unstructured socializing may produce opportunities for crime unrelated to money, and the effects of alcohol and drug use on economic crime might be psychopharmacological. Although we cannot rule out these interpretations, we do have some indirect evidence that the drug effects are based on financial need. Neither of our measures of hard drug use predicted assault, a crime that is usually unrelated to financial need (analyses not presented). We cannot make this argument for marijuana use, frequent alcohol use, and unstructured socializing as they were related to assault in the following month. It could be that the effects of lifestyle variables on economic crime and assault have different explanations. For example, alcohol has a stronger psychopharmacological effect on assault than on economic offenses (R. B. Felson, Savolainen, Aaltonen, & Moustgaard, 2008). Also, hedonistic activities may create opportunities for assault, as well as opportunities for property crime and drug dealing.

The Effects of Hard Drug Use

Our analyses of the relationship between hard drug use and property crime provided support for the addiction hypothesis as well as the hedonistic motive hypothesis. Consistent with the addiction hypothesis, we found that daily use of hard drugs predicted property crime in the following month, but that an offender who was using hard drugs less frequently was not much more likely than someone who abstained from committing property crime. The results support the idea that addiction to hard drugs leads offenders to commit property crimes while recreational use has a more limited effect. The results are consistent with Felson and Staff’s (2015) finding that the drug money motive for property crimes was more strongly associated with heavy drug use than recreational use. Both of these studies, however, are based on incarcerated samples. We cannot be certain that the relationships would be observed among the general population.

This result suggests that Goldstein’s (1985) description of economic offenses as “economic-compulsive” has at least a grain of truth. Daily users of hard drugs can be described as people with addictions who are “compelled” to commit property crime, and this accounts for at least some of the relationship between substance use and crime. We realize, however, that the meanings of “addiction” and “compulsive” are debated. Addiction could mean physical or psychological dependence and people with addictions do have some degree of choice (e.g., Baumeister et al., 1994).

In contrast, the impact of hard drug use on the economic crime of drug dealing is more consistent with hedonistic motivation. Drug dealing increases across the full frequency range of hard drug use. We found, at most, a modest extra boost for daily use (see Figure 2). We base this conclusion on the fact that the coefficient for the ordinal measure of hard drug use was statistically significant, whereas the coefficient specific to daily use was not significant in the lagged model (and of marginal significance in the simultaneous model). The more frequently offenders use hard drugs, the more likely they are to sell drugs in the following month, whether or not their use is frequent enough to suggest addiction.

The Economic Opportunity Hypothesis

We suggested that the money offenders earn from economic crimes increases their consumption of both legal and illegal goods and services. The money gives them the opportunity to purchase more drugs and more frequently engage in other hedonistic activity (e.g., Contreras, 2012; Moyle & Coomber, 2015). The evidence supported this hypothesis. Offenders who committed economic crimes engaged in more unstructured socializing in the following month, and they were more likely to use hard drugs, marijuana, and alcohol. Economic crimes had stronger effects on drug use than on the other hedonistic activities.

We cannot determine to what extent the effects of motivation and opportunity are an integrated process. We think it is reasonable to assume that some offenders are motivated to commit economic crime for drugs and other hedonistic activities and then use their proceeds for that purpose. We think it is also reasonable to assume that some offenders may have committed the economic crime without any idea of how they were going to spend the proceeds. As suggested earlier, money is fungible—it can be acquired for one purpose and easily used for another. Offenders can buy more drugs and socialize more extravagantly when they can afford it, regardless of the source of funding.

The evidence suggested that selling drugs is more likely than property crime to result in drug use. This pattern is consistent with an opportunity approach. Possessing large amounts of drugs increases availability and decreases the price and the effort required to obtain drugs. It also creates temptations that lead to greater consumption. Drug dealing is therefore associated with subsequent drug use but not subsequent alcohol use. The pattern suggests that drug users vary in the frequency with which they use drugs, depending on their financial situation. They respond to situational factors as well as internal factors (e.g., addiction). Offenders can be as opportunistic in their drug use as they are in committing other offenses. Note that the reciprocal relationship between economic crimes and drug use has policy implications. The results suggest that reducing economic crime would reduce drug use and reducing drug use would affect the frequency of economic crime. Of course, the proceeds from economic crime (like legal earnings) can also be used for legitimate expenditures.

Limitations

A potential limitation of our study involves measurement error. Although evidence suggests that the calendar method produces valid and reliable data (Roberts & Horney, 2010; Sutton, 2010; Sutton et al., 2011), our measurement is undoubtedly affected by less than perfect recall. We believe that the error from this source is more likely to be random than systematic in which case improving measurement would likely strengthen these results. Only additional research can determine whether this is the case.

The use of a 1-month time lag in some of our analyses is another potential limitation. Like almost all longitudinal research, the time lag is only an approximation. More broadly, the idea of a lagged effect oversimplifies the causal process as it does not take into account the time required for effects to accumulate, the length of time they endure, and the balance of stability and change in explanatory variables. Although our monthly measurement is much more frequent than it is in most longitudinal research, it may still be too long to capture the reciprocal processes that we are studying. For example, it might take only a few days for a hedonistic lifestyle to produce economic need and for ill-begotten gains to feed that lifestyle. If a 1-month time lag is too long, we may be underestimating the reciprocal effects. Of course, our simultaneous models effectively assume that minimal time is required for the effect to arise, but they are uninformative about the direction of influence.

Finally, it is not clear whether our use of an inmate sample limits the generalizability of our results. Our sample includes relatively serious offenders with relative high rates of serious drug use. It would be a mistake to infer from our results that recreational drug use in the general population leads to economic crimes.

Conclusion

In sum, these results contribute to our understanding of the relationships between economic crime, drug use, and other hedonistic activity. The frequent use of hard drugs, consistent with addiction, appears to increase property crime. However, more moderate drug use—indicative of a hedonistic lifestyle—has an effect on drug dealing as well as property crime. The results support the ethnographers’ claim about the role of a hedonistic lifestyle. Substance use and unstructured socializing lead to economic crime and economic crime contributes to a hedonistic lifestyle.

Footnotes

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

ORCID iD

Patrick R. Cundiff

Author Biographies

Richard B. Felson is professor of criminology and sociology at The Pennsylvania State University. He is interested in race; regional and national differences in violence; the role of situational factors; and differences between violence involving women and violence involving men.

D. Wayne Osgood is professor of criminology and sociology at The Pennsylvania State University. His current research interests include peers and delinquency, time use and offending, and crime and the life course.

Patrick R. Cundiff is a tenure-track assistant professor in the Department of Sociology at Western Michigan University. His research interests include criminology, delinquency, victimization, prisoner reentry, and criminal justice education.

Craig Wiernik is an assistant professor of sociology and anthropology at Wilkes University.

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