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....
| Publicado en: | Geografiska Annaler Series B: Human Geography Vol. 83; no. 2; pp. 67 - 79 |
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| Formato: | Artículo |
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Taylor & Francis Ltd
2001
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=6860691&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 6860691 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 04353684 7QV jtl: Geografiska Annaler Series B: Human Geography issn: 04353684 maglogo: N pubinfo: dt: 2001 vid: 83 iid: 2 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 6860691 10.1111/j.0435-3684.2001.00095.x ppf: 67 ppct: 12 formats: tig: atl: Vector Autoregression (Var) — An Approach to Dynamic analysis of Geographic Processes. aug: au: Lu, Max su: Human geography Geography -- Statistical methods Autoregression (Statistics) sug: subj: 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 doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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