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The Mechanism(s) of Neighbourhood Effects: Theory, Evidence, and Policy Implications

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Neighbourhood Effects Research: New Perspectives

Abstract

Although there is now a large body of empirical research on neighbourhood effects, we know relatively little about the causal mechanisms responsible for relationships between neighbourhood attributes and individual outcomes. A list of 15 potential causal pathways which may lead to neighbourhood effects is given, grouped into four categories: social-interactive mechanisms, environmental mechanisms, geographical mechanisms, and institutional mechanisms. The ultimate goal of neighbourhood effects research is not only to identify which mechanisms are responsible for neighbourhood effects, but also to quantitatively ascertain their relative contributions to the outcome under investigation. A pharmacological metaphor of “dosage-response” is used to understand how the theoretical mechanisms could be causally linked to individual outcomes. This metaphor refers to questions regarding the composition and the administration of the neighbourhood dosage, and the neighbourhood dosage-response relationship. This chapter concludes that despite the ever growing literature on neighbourhood effects, there is far too little scholarship to make many claims about which causal links dominate for which outcomes for which people in which national contexts and any conclusions on the existence of such effects should be treated as provisional at best.

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Notes

  1. 1.

    By contrast, Manski (1995) groups them into “endogenous,” “exogenous,” and “correlated” categories. Ellen and Turner (1997) group them into five categories: concentration, location, socialization, physical, and services. Leventhal and Brooks-Gunn (2000) use the rubrics “institutional resources,” “relationships,” and “norms/collective efficacy.”

  2. 2.

    Note that this discussion is related to but distinct from the question of how to accurately measure the magnitude of this dosage-response relationship, about which I wrote in Galster (2003; 2008).

  3. 3.

    I combine the competition and relative deprivation mechanisms because, to my knowledge, there is little extant statistical evidence that can distinguish between them.

  4. 4.

    However, it is not definitive about the extent to which such negative socialization is general across races. Turley (2003) probes beyond her discovery of overall positive correlations between median family income of neighborhood and youths’ behavioral and psychological test scores to see whether there were interaction effects with proxies for number of peer interactions and time spent in neighborhood. She found such strong interaction effects for white but not black youths in her sample, and concluded “differences in neighborhood socializing may explain why neighborhood income affects black and white children differently” (2003: 70).

  5. 5.

    Duncan et al. (1997) did not explicitly test for a threshold at a below-average percentage of affluent, however.

  6. 6.

    Turley (2003) analyzes behavioral and psychological test scores for youth as measured in a special supplement of the PSID. She relates these scores to the median family income of the census tract, so one cannot be certain whether the relationship is being generated by share of affluent or share of poor. She tests for non-linearities by employing a quadratic version of neighborhood income variable and finds that its coefficient is statistically significant and negative for the self-esteem outcome, implying that improving the economic environment of youth has a much greater psychological impact for those initially in disadvantaged neighborhood circumstances. Unfortunately, quadratic specifications are not precise in identifying thresholds.

  7. 7.

    See review in Kleinhans (2004).

  8. 8.

    I recognize that practitioners who deal directly with deprived neighborhoods hold divergent and conflicting opinions about which neighborhood effect mechanisms are most important (Atkinson and Kintrea 2004). The same can be said of low-income minority parents (Galster and Santiago 2006).

  9. 9.

    After their review, Leventhal and Brooks-Gunn (2000) similarly concluded that the strongest support seems to be for the combined role of norms, collective efficacy (informal social controls), and peers as major neighborhood influences on adolescent behaviors.

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Acknowledgments

I wish to thank Roland Atkinson, Jason Booza, Derek Hyra, Jeff Morenoff, Peter Phibbs, Kami Pothukuchi, and Lyke Thompson for stimulating conversations and helpful citations related to the subject matter of this paper. The research assistance of Sarah Marolf, Rebecca Grace Stokan, Lisa Stack, and Lonnisha Thomas is gratefully acknowledged. This paper was written with the support of the MacArthur Foundation.

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  1. Department of Urban Studies and Planning, Wayne State University, Detroit, MI, USA

    George C. Galster

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  1. , OTB Research Institute for the Built Environment, Delft University of Technology, Delft, Netherlands

    Maarten van Ham

  2. , Centre for Housing Research, University of St. Andrews, St. Andrews, KY16 9AL, Fife, United Kingdom

    David Manley

  3. , Urban Studies, University of Glasgow, Glasgow, G12 8RS, United Kingdom

    Nick Bailey

  4. , The Cathie Marsh Centre for Census and S, University of Manchester, Manchester, M13 9PL, United Kingdom

    Ludi Simpson

  5. , Centre for Housing Research, University of St. Andrews, St. Andrews, KY16 9AL, Fife, United Kingdom

    Duncan Maclennan

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Galster, G.C. (2012). The Mechanism(s) of Neighbourhood Effects: Theory, Evidence, and Policy Implications. In: van Ham, M., Manley, D., Bailey, N., Simpson, L., Maclennan, D. (eds) Neighbourhood Effects Research: New Perspectives. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2309-2_2

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