Vector Autoregression (Var) — An Approach to Dynamic analysis of Geographic Processes.

Vector autoregression (VAR) is a widely used econometric technique for multivariate time series modelling. This paper shows that with several very attractive features, VAR may also provide a valuable tool for analysing the dynamics among geographic processes and for spatial autoregressive modelling....

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Publicado en:Geografiska Annaler Series B: Human Geography Vol. 83; no. 2; pp. 67 - 79
Autor principal: Lu, Max
Formato: Artículo
Publicado: Taylor & Francis Ltd 2001
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        10.1111/j.0435-3684.2001.00095.x
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        au: Lu, Max
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        Human geography
        Geography -- Statistical methods
        Autoregression (Statistics)
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          Human geography
          Geography -- Statistical methods
          Autoregression (Statistics)
      ab: Vector autoregression (VAR) is a widely used econometric technique for multivariate time series modelling. This paper shows that with several very attractive features, VAR may also provide a valuable tool for analysing the dynamics among geographic processes and for spatial autoregressive modelling. After a brief discussion of the VAR approach, a VAR model for the dynamics of the US population between 1910 and 1990 is estimated and interpreted to illustrate the techniques. The VAR makes it possible to view the interactions among the four variables used in the model (total population, birth rate, immigration and per capita GNP) more adequately. The paper then discusses recent developments in the VAR methodology such as Bayesian vector autoregression (BVAR), spatial prior for regional modelling and cointegration, as well as the limitations and problems that arise from the application of VARs.
      pubtype: Academic Journal
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      src: R
    language: English
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