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Diagnostic Tools for Nonlinearity in Spatial Models

Author

Listed:
  • Thomas de Graaff

    (Vrije Universiteit Amsterdam)

  • Raymond J.G.M. Florax

    (Vrije Universiteit Amsterdam)

  • Peter Nijkamp

    (Vrije Universiteit Amsterdam)

  • Aura Reggiani

    (University of Bologna)

Abstract

There is an increasing awareness of the potential of nonlinear modeling in regional science, which can partly be explained by the recognition of the limitations of conventional equilibrium models in complex situationsand partly by the easy availability and accessibility of sophisticated computational techniques. Among the class of nonlinear models chaos theory stands out as an interesting approach, in which notable progress hasbeen made in economic research. However, the operational significance– in terms of solid empirical tests on chaos – has still been rather limited and a rigorous statistical-econometric treatment of chaos phenomena isstill lacking. This paper is concerned with a methodological and empirical analysis of chaos in spatial systems. It seeks to break new research ground by linking the classical diagnostic tools developed in spatial econometrics to nonlinearity tests for empirical data series, in particular the so-called BDS (Brock, Dechert, Scheinkman) test. A spatial variant of the BDS test is developed, and subsequently applied in the context of a shift-share model for Dutch regional labor markets.

Suggested Citation

  • Thomas de Graaff & Raymond J.G.M. Florax & Peter Nijkamp & Aura Reggiani, 1998. "Diagnostic Tools for Nonlinearity in Spatial Models," Tinbergen Institute Discussion Papers 98-072/3, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:19980072
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    References listed on IDEAS

    as
    1. Brock, W. A., 1986. "Distinguishing random and deterministic systems: Abridged version," Journal of Economic Theory, Elsevier, vol. 40(1), pages 168-195, October.
    2. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    3. Hordijk, L., 1974. "Spatial correlation in the disturbances of a linear interregional model," Regional and Urban Economics, Elsevier, vol. 4(2), pages 117-140, October.
    4. D C Knudsen & R Barff, 1991. "Shift-Share Analysis as a Linear Model," Environment and Planning A, , vol. 23(3), pages 421-431, March.
    5. Holden, Darryl R & Nairn, Alasdair G M & Swales, J K, 1989. "Shift-Share Analysis of Regional Growth and Policy: A Critique," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 51(1), pages 15-34, February.
    6. Raymond J. G. M. Florax & Serge Rey, 1995. "The Impacts of Misspecified Spatial Interaction in Linear Regression Models," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax (ed.), New Directions in Spatial Econometrics, chapter 5, pages 111-135, Springer.
    7. Scheinkman, Jose A, 1990. "Nonlinearities in Economic Dynamics," Economic Journal, Royal Economic Society, vol. 100(400), pages 33-48, Supplemen.
    8. Richard R. Nelson, 1995. "Recent Evolutionary Theorizing about Economic Change," Journal of Economic Literature, American Economic Association, vol. 33(1), pages 48-90, March.
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    10. Manfred M. Fischer & Arthur Getis (ed.), 1997. "Recent Developments in Spatial Analysis," Advances in Spatial Science, Springer, number 978-3-662-03499-6.
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    Cited by:

    1. Ernesto Calvo & Marcelo Escolar, 2003. "The Local Voter: A Geographically Weighted Approach to Ecological Inference," American Journal of Political Science, John Wiley & Sons, vol. 47(1), pages 189-204, January.

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    More about this item

    Keywords

    chaos theory; misspecification tests; spatial dependence; nonlinearity; shift-share model; regional labor markets;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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