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Intermetropolitan Migration and Hierarchical Destination Choice: A Disaggregate Analysis from the US Public Use Microdata Samples

Author

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  • P A Pellegrini

    (Department of Geography, The Ohio State University, 1036 Derby Hall, 154 North Oval Mall, Columbus, OH 43210-1361, USA)

  • A S Fotheringham

    (Department of Geography, University of Newcastle upon Tyne, Daysh Building, Newcastle upon Tyne NE1 7RU, England)

Abstract

In this paper the authors describe the application of spatial choice models to microlevel intermetropolitan migration destination choice data from the US Public Use Microdata Samples (PUMS) for the period 1985–90. The metropolitan and the microlevel data facilitate an analysis incorporating well-defined geographic units and their respective attributes, as well as an analysis disaggregated by the personal factors of migrants. The PUMS files provide one of the richest sources of national-level migration micro data in terms of geographic resolution, the number of individual or household characteristics recorded, sample size, and availability. The focus of the modelling exercise is to examine the performance of competing-destinations migration models which are based on the assumption that migrants process spatial information hierarchically. To date the only empirical testing of such models has been undertaken with aggregate spatial flow data, so the PUMS data provide a unique opportunity to examine the behaviour of the competing destinations framework in more detail. The authors provide information on the determinants of intermetropolitan migration within the USA and on the validity of the theoretical foundations of the competing-destinations framework. Traditional spatial choice models are shown to be severely misspecified and the distance-decay parameter estimates from such models to be potentially biased in such a manner that they exhibit the well-known ‘spatial structure’ effect. This effect does not appear when the parameters are estimated from competing-destinations models.

Suggested Citation

  • P A Pellegrini & A S Fotheringham, 1999. "Intermetropolitan Migration and Hierarchical Destination Choice: A Disaggregate Analysis from the US Public Use Microdata Samples," Environment and Planning A, , vol. 31(6), pages 1093-1118, June.
    • Handle: RePEc:sae:envira:v:31:y:1999:i:6:p:1093-1118
    DOI: 10.1068/a311093
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    References listed on IDEAS

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    1. T J Fik & G F Mulligan, 1990. "Spatial Flows and Competing Central Places: Towards a General Theory of Hierarchical Interaction," Environment and Planning A, , vol. 22(4), pages 527-549, April.
    2. T J Fik & R G Amey & G F Mulligan, 1992. "Labor Migration Amongst Hierarchically Competing and Intervening Origins and Destinations," Environment and Planning A, , vol. 24(9), pages 1271-1290, September.
    3. Borgers, Aloys & Timmermans, Harry, 1987. "Choice model specification, substitution and spatial structure effects : A simulation experiment," Regional Science and Urban Economics, Elsevier, vol. 17(1), pages 29-47, February.
    4. Kingsley E. Haynes & Stewart Fotheringham, 1990. "The Impact of Space on the Application Of Discrete Choice Models," The Review of Regional Studies, Southern Regional Science Association, vol. 20(2), pages 39-49, Spring.
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    Cited by:

    1. Goodwin-White, Jamie, 2006. "Dispersion or Concentration for the 1.5 Generation? Destination Choices of the Children of Immigrants in the US," IZA Discussion Papers 2269, Institute of Labor Economics (IZA).
    2. Gitlesen, Jens Petter & Thorsen, Inge & Ubøe, Jan, 2004. "Misspecifications due to aggregation of data in models for journeys-to-work," Discussion Papers 2004/13, Norwegian School of Economics, Department of Business and Management Science.
    3. Korpi, Martin & Clark, William, 2013. "Human Capital Theory And Internal Migration: Do Average Outcomes Distort Our View Of Migrant Motives?," Ratio Working Papers 213, The Ratio Institute.
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    5. Kim, Chansung, 2008. "Commuting time stability: A test of a co-location hypothesis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(3), pages 524-544, March.
    6. Liv Osland & Inge Thorsen, 2006. "Testing for the Impact of Local Labour Market Characteristics on House Prices," ERSA conference papers ersa06p490, European Regional Science Association.
    7. Elhorst, J. Paul & Oosterhaven, Jan & Romp, Ward E., 2001. "Integral cost-benefit analysis of Maglev technology under market imperfections," Research Report 04C22, University of Groningen, Research Institute SOM (Systems, Organisations and Management).

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