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A Comparison of Traditional and Discrete-Choice Approaches to the Analysis of Residential Mobility and Locational Attainment

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  • Lincoln Quillian

Abstract

This article contrasts traditional modeling approaches and discrete-choice models as methods to analyze locational attainment—how individual and household characteristics (such as race, socioeconomic status, age) influence the characteristics of neighborhoods of residence (such as racial composition and median income). Traditional models analyze attributes of a neighborhood as a function of the characteristics of the households within them; discrete-choice methods, on the other hand, are based on dyadic analysis of neighborhood attributes and household characteristics. I outline two problems with traditional approaches to residential mobility analysis that may be addressed through discrete-choice analysis. I also discuss disadvantages of the discrete-choice approach. Finally, I use data from the Panel Study of Income Dynamics to estimate residential mobility using traditional locational attainment and discrete-choice models; I show that these produce similar estimates but that the discrete-choice approach allows for estimates that examine how multiple place characteristics simultaneously guide migration. Substantively, these models reveal that the disproportionate migration of black households into lower-income tracts amounts to sorting of black households into black tracts, which on average are lower income.

Suggested Citation

  • Lincoln Quillian, 2015. "A Comparison of Traditional and Discrete-Choice Approaches to the Analysis of Residential Mobility and Locational Attainment," The ANNALS of the American Academy of Political and Social Science, , vol. 660(1), pages 240-260, July.
    • Handle: RePEc:sae:anname:v:660:y:2015:i:1:p:240-260
    DOI: 10.1177/0002716215577770
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    References listed on IDEAS

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    1. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    2. Stanley Wasserman & Philippa Pattison, 1996. "Logit models and logistic regressions for social networks: I. An introduction to Markov graphs andp," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 401-425, September.
    3. John Logan & Richard Alba, 1993. "Locational returns to human capital: Minority access to suburban community resources," Demography, Springer;Population Association of America (PAA), vol. 30(2), pages 243-268, May.
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    Cited by:

    1. Korpi, Martin & Halvarsson, Daniel & Öner, Özge & A.V. Clark, William & Mihaescu, Oana & Östh, John & Bäckman, Olof, 2022. "Native Population Turnover & Emerging Segregation: The Role of Amenities, Crime and Housing," Ratio Working Papers 358, The Ratio Institute.
    2. Michael D. M. Bader & Maria Krysan, 2015. "Community Attraction and Avoidance in Chicago," The ANNALS of the American Academy of Political and Social Science, , vol. 660(1), pages 261-281, July.
    3. Ted Mouw & Arne L. Kalleberg & Michael A. Schultz, 2024. "“Stepping-Stone†versus “Dead-End†Jobs: Occupational Structure, Work Experience, and Mobility Out of Low-Wage Jobs," American Sociological Review, , vol. 89(2), pages 298-345, April.
    4. Mulholland, Sean E. & Hernandez-Julian, Reynaldo, 2021. "Does Economic Freedom Lead to Selective Migration by Sex and Race?," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 53(1), July.
    5. Christine Leibbrand & Kyle Crowder, 2018. "Migration, Mobility, and Neighborhood Attainment: Using the PSID to Understand the Processes of Racial Stratification," The ANNALS of the American Academy of Political and Social Science, , vol. 680(1), pages 172-192, November.

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