Abstract
Objectives
To assess the role of selection in the observed association between residential mobility and delinquency among adolescents.
Methods
This study draws on a sample of adolescents from the National Longitudinal Study of Adolescent Health (Add Health). We first examine whether adjusting regression models for several well-established determinants of moving attenuates the association between mobility and delinquency. We then employ propensity score methods to estimate the effect of residential mobility on delinquency among a sub-sample of movers and non-movers who had similar likelihoods of moving.
Results
The association between mobility and delinquency is significant and positive in regression models, although it is somewhat attenuated by additional control variables that are rarely considered in prior work. However, the distribution of mobility determinants differs substantially across movers and non-movers, potentially biasing these estimates. After covariate balance is achieved using a propensity score approach, we observe no differences in delinquency between groups.
Conclusions
Results suggest that certain adolescents are more likely to move than others, explaining the observed association between mobility and delinquency. Future research should therefore be mindful of selection when trying to account for differential outcomes between mobile and non-mobile adolescents.
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Notes
Following standard convention we generated five imputed datasets using chained equations. Missing values on each of the covariates was estimated as a function of the remaining covariates presented in Table 1. The models presented in the following section were estimating on the imputed datasets and average coefficients are reported. Missing data was not imputed on either of the dependent variables. We also estimated the proceeding models using list wise deletion and detected no significant departures from the results presented here.
Other studies have also operationalized mobility as both residential and school moves (Gasper et al. 2010). In this study we are specifically interested in addressing literature that establishes an association between residential mobility and delinquency, although we also conducted supplementary analyses that consider ‘movers’ to be adolescents who moved both census tracts and schools. The findings were not substantively different than models presented here (Results available upon request). In addition, movers could also move blocks within the same census tract. In the Add Health survey we identified 63 such movers. Supplemental analyses were also conducted with an expanded definition of “mover” that included these 63 intra-tract moves. This expanded definition also did not alter results substantively (Results available upon request).
Of course, relying on administratively defined units to differentiate neighborhoods is an imperfect practice. Without more elaborate data on street patterns and social network structures, however, census tracts are the most valid measure available in this case (see Sampson et al. 2002 for a summary of neighborhood effects research).
Many studies find that the incidence of moving among adolescents is more common. We surmise that only a small percentage are classified as movers because we are looking at moves that occurred over a one year period, rather than over a period of several years (as many of the earlier studies using Add Health have done).
We expressly focus on residential moves, although other studies have noted the relevance of school mobility as well (Gasper et al. 2010). Thus, we replicated the analyses presented here measuring mobility as whether a respondent had moved both tracts and schools between waves. Results do not differ substantively and are available upon request.
The relationship between mobility and family structure is potentially complex. Unfortunately it is not possible using the Add Health data to ascertain the mobility of a second parent or caregiver in cases where the respondent splits time between two households. As such, it is possible that our measure of mobility underestimates mobility in instances where one parent moved, but the other did not, especially when the mobile parent does not have joint or full custody.
Within parsimonious approaches, there is also some disagreement over which variables best reduce bias: (1) variables that are highly correlated with the treatment, and not highly correlated with the outcome, (2) variables that are highly correlated with the outcome, and not the treatment, and (3) variables that are highly correlated with each. We adopt an approach most consistent with the work of Steiner et al. (2010), who show that only a minimal set of covariates that are central to the selection process are necessary and sufficient for bias reduction (p.261).
We estimated model fits by multiplying the difference between likelihood functions of the full and restricted models by −2. The quotient approximates a Chi square distribution with degrees of freedom equal to the difference in parameters between the two models. A significant Chi square value indicates the full model is preferred over the restricted model.
We also estimated the propensity score models separately for males and females as prior research indicates moving may be more detrimental for males (Kling et al. 2005). However, for both males and females we detected no significant difference in these outcomes in the matched samples. Models are available upon request.
As noted by Abadie and colleagues (2009), bootstrapping techniques for estimating the variance of matching estimators may be inaccurate and significance tests of treatment effects should be interpreted with caution.
Covariate adjustment and propensity score methods were also implemented to estimate the effect of moving on delinquent peer affiliation, since past research posits that the mobility-delinquency link operates through shifts in the behavioral composition of peers. These results were also largely consistent with self-reported delinquency models, suggesting that any link between these variables is due to selection (Results available upon request).
As one reviewer notes, the disparate results across models might indicate that the association is sensitive to modeling strategy rather than evidencing that a propensity score approach reduced a selection bias that is driving these differences. To test this possibility, we conducted a negative binomial regression of general delinquency and violence on moving using our matched sample. If the effect is sensitive to modeling strategy we would expect a negative binomial regression using the matched sample to yield significant results consistent with the models presented in Tables 2 and 3. However, moving remained a non-significant predictor of both types of delinquency (Results available upon request).
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Acknowledgments
A version of this paper was presented at the 2010 annual meeting of the American Society of Criminology in San Francisco, CA. We are grateful to Ryan D. King, Scott J. South, Shawn Bushway and anonymous reviewers for feedback on earlier drafts of this paper. The Center for Social and Demographic Analysis of the University at Albany provided technical and administrative support for this research through a grant from the National Institute of Child Health and Human Development (R24-HD044943). This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for this analysis.
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Lauren Porter and Matt Vogel contributed equally to this project.
Appendices
Appendix 1: Delinquency Items
In the past 12 months how often did you…
(Never, 1 or two times, 3 or 4 times, 5 or more times)*
-
1.
Paint graffiti or signs on someone else’s property or in a public place?
-
2.
Take something from a store without paying for it
-
3.
Get into a serious physical fight?
-
4.
Hurt someone badly enough to need bandages or care from a doctor or nurse?
-
5.
Steal something worth more than $50?
-
6.
Go into a house or building to steal something?
-
7.
Use or threaten to use a weapon to get something from someone?
-
8.
Sell marijuana or other drugs?
-
9.
Take part in a fight where a group of your friends was against another group?
During the past 12 months, how often did each of the following things happen?
(Never, Once, More than Once)
-
10.
You Pulled a Knife or a Gun on Someone
-
11.
You Shot or Stabbed Someone
*Each item was collapsed into a dichotomy indicating whether the respondent participated in any of these activities. The variety scale was computed by summing across these dichotomous indicators
Appendix 2: Violence Items
In the past 12 months how often did you…
(Never, 1 or two times, 3 or 4 times, 5 or more times)*
-
1.
Get into a serious physical fight?
-
2.
Hurt someone badly enough to need bandages or care from a doctor or nurse?
-
3.
Use or threaten to use a weapon to get something from someone?
-
4.
Take part in a fight where a group of your friends was against another group?
During the past 12 months, how often did each of the following things happen?
(Never, Once, More than Once)
-
5.
You Pulled a Knife or a Gun on Someone
-
6.
You Shot or Stabbed Someone
*Each item was collapsed into a dichotomy indicating whether the respondent participated in any of these activities. The variety scale was computed by summing across these dichotomous indicators
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Porter, L., Vogel, M. Residential Mobility and Delinquency Revisited: Causation or Selection?. J Quant Criminol 30, 187–214 (2014). https://doi.org/10.1007/s10940-013-9200-7
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DOI: https://doi.org/10.1007/s10940-013-9200-7