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A Linear Structural Equation Approach to Cross-Sectional Models with Lagged Variables

Author

Listed:
  • H Folmer

    (Department of Geography, University of Groningen, Groningen, The Netherlands)

  • G A van der Knaap

    (Department of Economics, Economic Geography Institute, Erasmus University, Rotterdam, The Netherlands)

Abstract

Lagged variables play an important role in cross-sectional models in geography and regional sciences. This paper starts with an overview of the situations in which they may be required. Lagged variables also pose serious problems from a statistical point of view: multicollinearity and the determination of the length of the lag. Some common approaches to these two problems are discussed and evaluated. As an alternative a linear structural equation approach is presented, where the lagged variables are compressed to latent variables in a measurement model. The relationship between the lagged variables, thus compressed, and the dependent variable is expressed in the structural model. Both the measurement model and the structural model are estimated simultaneously. The paper ends with an application. A model of urban immigration for the thirty-three largest Dutch cities is estimated.

Suggested Citation

  • H Folmer & G A van der Knaap, 1981. "A Linear Structural Equation Approach to Cross-Sectional Models with Lagged Variables," Environment and Planning A, , vol. 13(12), pages 1529-1537, December.
  • Handle: RePEc:sae:envira:v:13:y:1981:i:12:p:1529-1537
    DOI: 10.1068/a131529
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    References listed on IDEAS

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    1. H Folmer, 1981. "Measurement of the Effects of Regional Policy Instruments by Means of Linear Structural Equation Models and Panel Data," Environment and Planning A, , vol. 13(11), pages 1435-1448, November.
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    Cited by:

    1. repec:asg:wpaper:1013 is not listed on IDEAS
    2. Folmer, H. & Nijkamp, P., 1982. "Linear structural equation models with spatiotemporal auto- and cross- correlation," Serie Research Memoranda 0020, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    3. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.

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