Advanced Search
MyIDEAS: Login to save this article or follow this journal

Bootstrap Inference in Spatial Econometrics: the J-test


Author Info

  • Peter Burridge
  • Bernard Fingleton


Abstract Kelejian (2008) introduces a J-type test for the situation in which a null linear regression model, Model0, is to be tested against one or more rival non-nested alternatives, Model1, …, Model g , where typically the competing models possess endogenous spatial lags and spatially autoregressive error processes. Concentrating on the case g=1, in this paper we examine the finite sample properties of a spatial J statistic that is asymptotically under the null, and an alternative version that is conjectured to be approximately , both introduced by Kelejian. We demonstrate numerically that the tests are excessively liberal in some leading cases and conservative in others using the relevant chi-square asymptotic approximations, and explore how far this may be corrected using a simple bootstrap resampling method. Inférence ‘bootstrap’ dans l'économétrie spatiale: le test ‘J’ Résumé Kelejian (2008) présente un test de type J pour la situation dans laquelle on doit tester un modèle a régression linéaire nulle, Model0, par rapport à une ou plusieurs alternatives concurrentes non imbriquées, Model1, …, Model g , dans laquelle les modèles concurrents possèdent généralement des retards spatiaux endogènes et des procédés d'erreur spatialement autorégressifs. En nous concentrant sur le cas g=1, nous examinons, dans la présente communication, les propriétés d'échantillon finies d'une statistique spatiale J qui se trouve asymptotiquement sous le zéro, et une version alternative supposée être égale à environ , introduites toutes les deux par Kelejian. Nous démontrons de façon numérique que les tests sont excessivement libéraux, dans certains des principaux cas, et plutôt prudents dans d'autres, en faisant usage des approximations asymptotiques au chi carré, et nous explorons la mesure dans laquelle nous pouvons le corriger en appliquant un simple processus empirique ré-échantillonné. La inferencia bootstrap en la econometría espacial: el test J Résumén Kelejian (2008) introduce un test de tipo J para la situación en que un modelo de regresión lineal nulo, Model0, se pone a prueba contra una o más alternativas rivales no anidadas, Model1, …, Model g , donde típicamente los modelos competidores poseen lapsos espaciales endógenos y procesos de error espacialmente autorregresivos. Concentrándose en el caso, g=1, este trabajo examina las propiedades de muestra finita de una estadística espacial J que es asimptóticamente bajo el nulo, y una versión alternativa que se conjetura que es aproximadamente , ambas introducidas por Kelejian. Demostramos numéricamente que los tests son excesivamente liberales en ciertos casos destacados y conservadores en otros, utilizando las aproximaciones chi cuadradas oportunas, y exploramos hasta qué punto esto podría corregirse empleando un método simple bootstrap de remuestreo.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL:
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Spatial Economic Analysis.

Volume (Year): 5 (2010)
Issue (Month): 1 ()
Pages: 93-119

as in new window
Handle: RePEc:taf:specan:v:5:y:2010:i:1:p:93-119

Contact details of provider:
Web page:

Order Information:

Related research

Keywords: Spatial econometrics; bootstrap; J-test; C; C21;

Find related papers by JEL classification:


No references listed on IDEAS
You can help add them by filling out this form.


Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Luisa Corrado & Bernard Fingleton, 2011. "Where is the economics in spatial econometrics?," LSE Research Online Documents on Economics 33581, London School of Economics and Political Science, LSE Library.
  2. Jesus Mur & Antonio Paez, 2011. "Local weighting or the necessity of flexibility," ERSA conference papers ersa11p942, European Regional Science Association.
  3. Han, Xiaoyi & Lee, Lung-fei, 2013. "Model selection using J-test for the spatial autoregressive model vs. the matrix exponential spatial model," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 250-271.
  4. Jesus Mur & Marcos Herrera & Manuel Ruiz, 2011. "Selecting the W Matrix. Parametric vs Nonparametric Approaches," ERSA conference papers ersa11p1055, European Regional Science Association.
  5. Jin, Fei & Lee, Lung-fei, 2013. "Cox-type tests for competing spatial autoregressive models with spatial autoregressive disturbances," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 590-616.
  6. Marcos Herrera & Manuel Ruiz & Jes�s Mur, 2013. "Detecting Dependence Between Spatial Processes," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(4), pages 469-497, February.
  7. Emanuela Marrocu & Raffaele Paci & Stefano Usai, 2012. "The complementary effects of proximity dimensions on knowledge spillovers," ERSA conference papers ersa12p167, European Regional Science Association.
  8. Zhenlin Yang, 2013. "LM Tests of Spatial Dependence Based on Bootstrap Critical Values," Working Papers 03-2013, Singapore Management University, School of Economics.
  9. Bernard FINGLETON & Silvia PALOMBI, 2013. "The Wage Curve Reconsidered: Is It Truly An 'Empirical Law Of Economics'?," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 38, pages 49-92.
  10. Herrera Gómez, Marcos & Mur Lacambra, Jesús & Ruiz Marín, Manuel, 2011. "¿Cuál matriz de pesos espaciales?. Un enfoque sobre selección de modelos
    [Which spatial weighting matrix? An approach for model selection]
    ," MPRA Paper 37585, University Library of Munich, Germany.


This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.


Access and download statistics


When requesting a correction, please mention this item's handle: RePEc:taf:specan:v:5:y:2010:i:1:p:93-119. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.