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Temporal dimensions and measurement of neighbourhood effects

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  • Sako Musterd
  • George Galster
  • Roger Andersson
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    Abstract

    We conduct a panel analysis quantifying the degree to which the mixture of low-income, middle-income, and high-income males in the neighbourhood affects the subsequent labour income of individuals, and test the degree to which these effects vary by timing (lagging up to three years), duration (one to four years), and cumulative amount of exposure and to what extent these effects are persistent. We employ a fixed-effects model to reduce the potential bias arising from unmeasured individual characteristics leading to neighbourhood selection. The empirical study applies individual-level data for the working-age population of the three largest cities in Sweden covering the period 1991 – 2006. The analyses suggest that there are important temporal dimensions in the statistical effect of neighbourhood income mix: recent, continued, or cumulative exposure yields stronger associations than lagged, temporary ones, and there is a distinct time decay (though some persistence) in the potential effects after exposure ceases, though with some gender differences. Keywords: neighbourhood effects, social mixing, duration effects, lag effects, cumulative effects, fixed-effects models

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    Bibliographic Info

    Article provided by Pion Ltd, London in its journal Environment and Planning A.

    Volume (Year): 44 (2012)
    Issue (Month): 3 (March)
    Pages: 605-627

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    Handle: RePEc:pio:envira:v:44:y:2012:i:3:p:605-627

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    Web page: http://www.pion.co.uk

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    Cited by:
    1. Magnus Strömgren & Tiit Tammaru & Alexander Danzer & Maarten Ham & Szymon Marcińczak & Olof Stjernström & Urban Lindgren, 2014. "Factors Shaping Workplace Segregation Between Natives and Immigrants," Demography, Springer, vol. 51(2), pages 645-671, April.
    2. Maarten van Ham & David Manley, 2012. "Neighbourhood Effects Research at a Crossroads: Ten Challenges for Future Research," Working Paper Series of the German Council for Social and Economic Data 204, German Council for Social and Economic Data (RatSWD).
    3. Титкова В. В. & Иванюшина В. А. & Александров Д. А., 2013. "Популярность Школьников И Образовательная Среда Школы," Вопросы образования // Educational Studies, НИУ ВШЭ, issue 4, pages 145-167.
    4. Hedman, Lina & Manley, David & van Ham, Maarten & Östh, John, 2012. "Cumulative Exposure to Disadvantage and the Intergenerational Transmission of Neighbourhood Effects," IZA Discussion Papers 6794, Institute for the Study of Labor (IZA).

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