Local Estimation of Spatial Autocorrelation Processes

Hernández, Fernando A. López; Mur, Jesús; Angulo, Ana

doi:10.1007/978-3-642-03326-1_6

Cited by 8 publications

(2 citation statements)

References 47 publications

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“…For example, Kelejian and Prucha (2009) show that the maximum likelihood estimator of a spatial model with cross‐sectional dependence and heteroscedastic innovations can be inconsistent (see also Brunsdon et al. 1998b; McMillen 2004; Koop and Potter 2007; or López et al. 2008 and references therein for other pitfalls).…”

Section: Conclusion and Future Perspectivesmentioning

confidence: 99%

Testing the hypothesis of stability in spatial econometric models

Mur¹,

Hernández²,

Angulo³

2009

Papers in Regional Science

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The objective of this paper is to advance in the discussion of the topic of heterogeneity in a spatial econometric model. The proposal is not a novelty as there is a great deal of experience accumulated on the same subject. What differentiates this work is that we use a broad notion of the term heterogeneity, in association with different symptoms of stability in the elements of the equation. That is, we deal with problems ("i") in the coefficients of regression, ("ii") in the variance of the random term and ("iii") in the mechanisms of spatial dependence. With this purpose, we develop several tests through which we tackle the problem of heterogeneity from various perspectives. We assess their performance through a Monte Carlo experiment. Copyright (c) 2009 the author(s). Journal compilation (c) 2009 RSAI.

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Section: Conclusion and Future Perspectivesmentioning

confidence: 99%

Testing the hypothesis of stability in spatial econometric models

Mur¹,

Hernández²,

Angulo³

2009

Papers in Regional Science

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“…Anselin (1988c) was one of the first to combine the two topics, giving rise to the well-known battery of tests of autocorrelation and heteroskedasticity; Anselin (1990) and Páez, Uchida, and Miyamoto (2001) continue along the same lines, adapting the Chow test to models with spatial dependence. Later, Brunsdon, Fotheringham, and Charlton (1998a), Pace and Lesage (2004), and López, Mur, and Angulo (2009) develop models where the mechanism of spatial dependence is specific for each point in space. These last three articles may be seen as a natural extension of the Locally Weighted Regressions algorithm, introduced by Cleveland (1979) and Cleveland and Devlin (1988) and subsequently developed by, among others, McMillen (1996), McMillen and McDonald (1997), Brunsdon, Fotheringham, and Charlton (1998b), and Páez, Uchida, and Miyamoto (2002a, 2002b).…”

Section: Introductionmentioning

confidence: 99%

Looking for the Causes of Instability in Spatial Econometric Models

Mur

Angulo

Hernández

2012

International Regional Science Review

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It is relatively easy to find symptoms of misspecification in a model that suffers from instability. Problems arise in relation to their interpretation: They may be due to a wrong selection of the functional form. There may be a problem of omitted variables or the parameters of the model may not be homogeneous across space. The authors focus their attention on the last aspect. Specifically, the intention is to develop a strategy to analyze the hypothesis of stability in the parameters of a spatial econometric model. It is important that this procedure should provide the user with information about the cause of instability. The content of the article is mixed. First, the authors develop a collection of robust Multipliers to test the hypothesis of stability in the main elements of a spatial econometric model. Then, they solve a Monte Carlo to analyze the behavior of the Multipliers. Finally, they present an application to the case of the Spanish elections by municipalities.

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Models for spatial outcomes and geographical association

Congdon

2014

Applied Bayesian Modelling

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Local Estimation of Spatial Autocorrelation Processes

Cited by 8 publications

References 47 publications

Testing the hypothesis of stability in spatial econometric models

Testing the hypothesis of stability in spatial econometric models

Looking for the Causes of Instability in Spatial Econometric Models

Models for spatial outcomes and geographical association

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