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Samuel E. DeWitt, PhD Student

Robert J. Apel PhD, Associate Professor

Rutgers University, Newark

School of Criminal Justice

PERCEPTUAL DETERRENCE AND DETERRABILITY: INDIVIDUAL DIFFERENCES AND RISK PERCEPTIONS IN A NATIONAL SAMPLE

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DETERRENCE & DETERRABILITY

Deterrence Theory & Rational Choice Perspective

Assumption of a Rational Actor
Rational Actor & Criminal Justice Sanctions

Belief Updating

Deterrability

How much can one be deterred by the risk of a criminal justice sanction?
Groups of undeterrable offenders?

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RELEVANT LITERATURE

Loughran, Piquero, Fagan, & Mulvey (2009)

Pathways to Desistance
Salient Differences in Deterrability

Piquero, Paternoster, Pogarsky, Loughran (2011)

Individual Difference Components of Deterrence
Market v. Non-Market Offenders

Maxson, Matsuda, Hennigan (2011)

Deterrability of Gang Members

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CURRENT RESEARCH

Lochner (2003) Individual Perceptions of The Criminal Justice System

Risk Perceptions of Arrest

Current Analysis

Data: NLSY97 – Waves 1-5
Methods: OLS & Quantile Regression

Simple Individual v. Expanded Social Models

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INDEPENDENT VARIABLES

Respondent Measures

Thefts >$50 - Count
Drug Sales - Count
Arrests for Theft - Count
Arrest/Crime Ratio
Gang Involvement (Individual & Vicarious)
Prosocial/Antisocial Peer Influence Factors
Age of Onset: Property/Violent

Sibling Measures
Control Measures

Structural Influences

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DEPENDENT VARIABLES

Risk Perceptions of Arrest

Survey Question (Waves 1-5)

Percent Chance of Arrest if Respondent Stole a Vehicle

OLS Regression

Current Year’s Perceptions

Quantile Regression

Current Year’s Perceptions

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PERCEPTIONS ACROSS WAVES

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Regressor	OLS – Simple Model (iv)			OLS – Expanded Model (v)
Respondent	Coef.	Clstrd St Error	Std. Coef	Coef.	Clstrd St Error	Std Coef
Prior Yr Perceptions	.333***	.012	.332	.335***	.011	.333
# of Thefts >$50 Prev Yr	-.359**	.096	-.034	-----	-----	-----
# of Drug Sales in Prev Yr	-.064+	.033	-.019	-----	-----	-----
# of Arrests for Theft in Prev Yr	4.61+	.627	.016	-----	-----	-----
Arrest/Crime Ratio	-----	-----	-----	2.56	2.18	.008
Gang Involvement	-----	-----	-----	-10.01***	2.44	-.040
Vicarious Gang Inv.	-----	-----	-----	-2.74*	2.674	-.019
Prosocial Peer Influence	-----	-----	-----	1.09**	.418	.025
Antisocial Peer Influence	-----	-----	-----	-1.14*	.494	-.027
Family Member in Jail	-----	-----	-----	.218	1.71	.001
Siblings
# of Thefts >$50 Prev Yr	-.071	.251	-.003	-----	-----	-----
# of Drug Sales in Prev Yr	-.100	.071	-.015	-----	-----	-----
# of Arrests for Theft in Prev Yr	3.83	3.83	.008	-----	-----	-----
Arrest/Crime Ratio	-----	-----	-----	1.63	4.48	.004

+ p<.1; * p<.05; ** p<.01; *** p<.001; Sample Sizes: Model iv: 12183; Model v: 12805; R²: Model iv: .1354; Model v: .1380; Standard Errors are clustered by NLSY ID, Sample Weights are utilized

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RESULTS FROM OLS MODELS

Perception Formation

Effects While Controlling for Previous Year’s Perceptions
Effects of Other Control Variables
Arrest/Crime Ratio

Overall Conclusions

Do Youth Update Their Perceptions Based on Behavior Between Waves?
Are there groups of undeterrable offenders?

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PERCEPTIONS ACROSS WAVES

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PREDICTIONS OF LINEAR MODEL

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HOMOGENEITY OF VARIANCE?

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NORMALITY OF RESIDUAL TERM?

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	25th Quantile		50^th Quantile		75^th Quantile
Regressor	Coefficient	Standard Error	Coefficient	Standard Error	Coefficient	Standard Error
Prior Year Perception	.512***	.004	.804***	.006	.100***	.000
Arrest/Crime Rate	-1.32	.961	.486	1.47	.300***	.000
Gang Membership	-2.18*	1.04	-8.52***	1.55	-3.22***	.000
Vicarious Gang Membership	-.656	.610	-.667	.903	.000	.000
Prosocial Peer Influence	.526**	.186	.396	.274	.000	.000
Antisocial Peer Influence	-.731***	.210	-.763*	.309	.000	.000
Age at First Violent Offense	-.133*	.062	-.063	.093	.000	.000
Age at First Property Offense	.115	.122	.055	.181	-.033***	.000
Sibling Arrest/Crime Rate	1.22	2.08	-1.24	2.99	.000	.000
Family Member in Jail	.690	.756	-.735	1.13	.000	.000
Mother was a Teen When R Born	-1.80**	.534	-.393	.793	.000	.000
Intercept	1.04	2.51	20.91***	3.76	90***	.000

+ p<.1; * p<.05; ** p<.01; *** p<.001; Sample Size: 12805; Pseudo R²: 25^th Q:.1282; 50^th Q: .1573; 75^th Q: .0106

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PREDICTIONS OF SEMI-PARAMETRIC MODELS

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CONCLUSIONS/FUTURE DIRECTIONS

Model Diagnostics

Non-Parametric Methods

Quantile Regression v. Linear Models

Examine Perceptual Clustering

Concurrent Research

Examining Future Expectations

How do Future Expectations influence behavior?
How do Future Expectations change?

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Samuel E. DeWitt, PhD Student

Robert J. Apel, Associate Professor

Rutgers University, Newark

School of Criminal Justice

PERCEPTUAL DETERRENCE AND DETERRABILITY: INDIVIDUAL DIFFERENCES AND RISK PERCEPTIONS IN A NATIONAL SAMPLE

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CORRELATIONS

Correlation Matrix

Problematic Correlations

Arrest, Thefts, Drug Sales & Crime/Arrest Ratio - .28, .31, .51
Sibling # Arrests, Drug Sales, Thefts & Sib C/A Ratio - .31, .37, .54
Sibling # Arrests & Sibling # Thefts - .36

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Regressor	OLS (Quasi-First Differences) (iv)			OLS (Quasi-First Differences) (v)
Respondent	Coef.	Clstrd St Error	Std. Coef	Coef.	Clstrd St Error	Std Coef
MSA	-3.646***	.987	-.037	-3.54***	.958	-.037
Black	-6.143***	1.062	-.054	-4.80***	1.05	-.042
Hispanic	-6.217***	1.051	-.053	-4.72***	1.03	-.040
Math PIAT Score (Percentile)	.101***	.026	.069	.103***	.026	.068
Math PIAT Dummy	7.739***	1.880	.082	7.52***	1.93	.077
Year Dummy 1999	5.556***	1.103	.061	4.76***	1.09	.052
Year Dummy 2000	4.031**	1.201	.044	1.76	1.21	.020
Year Dummy 2001	4.961**	1.433	.054	2.87*	1.44	.032
Lived w/Both Bio Parents Age 12	-.217	.831	-.003	-.311	.834	-.004
Age	-1.080**	.367	-.050	-.629+	.373	-.029
Mother was a Teen When R Born	-1.812	1.372	-.014	-2.33+	1.28	-.018

+ p<.1; * p<.05; ** p<.01; *** p<.001; Sample Sizes: Model iv: ; Model v: ; R²: Model iv: ; Model v: Standard Errors are clustered by NLSY ID, Sample Weights are utilized

CONTROLS – QUASI-FIRST DIFFERENCES MODELS

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	25^th Quantile		50^th Quantile		75^th Quantile
Regressor	Coef.	Std Error	Coef.	Std Error	Coef.	Std Error
No Criminal Behavior	-.639	.421	.153	.626	.000	.000
Sib – No Criminal Behavior	.394	.996	.537	1.48	.000	.000
MSA Status	-1.15*	.445	-1.37*	.657	-.000	.000
Black	-3.06***	.465	-4.33***	.676	-.000	.000
Hispanic	-3.28***	.468	-4.25***	.686	-.000	.000
Piat Test Scores	.082***	.012	.069***	.018	.000	.000
Year Dummy 1999	3.97***	.511	2.22**	.760	.000	.000
Year Dummy 2000	3.17***	.589	1.74*	.874	.000	.000
Year Dummy 2001	3.95***	.696	2.33*	1.03	.000	.000
Household Structure	.362	.371	-.355	.551	-.000	.000
Age	-.256	.167	-.641*	.249	-.000	.000
Mother was Teen when R Born	-1.80**	.534	-.393	.793	-.000	.000

CONTROLS – QUANTILE REGRESSION MODELS

+ p<.1; * p<.05; ** p<.01; *** p<.001; Sample Size: 12805; Pseudo R²: 25^th Q:.1282; 50^th Q: .1573; 75^th Q: .0106

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Regressor	Mean	Std. Deviation	Regressor	Mean	Std. Deviation
Perceptions	58.35	40.57	# Drug Sales	1.86	10.89
Difference in Perceptions	-.227	46.93	# Arrests-Theft	.068	..318
Gang Membership	.039	.193	Sib - # Thefts >$50	.007	.086
Vicarious Gang Membership	.111	.315	Sib - # Drug Sales	.409	5.44
Prosocial Peer Influence	-.000	.999	Sib - # Arrests-Theft	.120	.459
Antosocial Peer Influence	.000	.999	MSA Status	.817	.387
Age at First Violent Offense	9.86	3.23	Black	.254	.435
Age at First Property Offense	11.12	2.98	Hispanic	.212	.409
Arrest/Crime Ratio	.122	.467	Teen Mom	.129	.336
Sibling Arrest/Crime Ratio	.009	.113	Household Struc.	.505	.500
Family Member in Jail	.061	.239	No Crim. Behavior	.749	.433
# of Thefts >$50	.395	4.17