IDEAS home Printed from https://ideas.repec.org/a/taf/specan/v5y2010i2p205-227.html
   My bibliography  Save this article

Estimation Strategies for a Spatial Dynamic Panel using GMM. A New Approach to the Convergence Issue of European Regions

Author

Listed:
  • Salima Bouayad-Agha
  • Lionel Védrine

Abstract

Abstract While estimation methods for dynamic panel data and spatial econometric models are standard in economic literature, there has been a relatively recent development in methods which include spatial considerations in dynamic panel data models. This paper proposes two estimation strategies for spatial dynamic panel data models using the generalized method of moments (GMM). The first is to extend the moment restrictions of Arellano and Bond's estimator to a spatial autoregressive dynamic panel. The second allows for spatial dependence in the error process. The empirical application focuses on European regional growth over a 25-year period. We find empirical evidence of conditional convergence, which is significantly affected by spatial disparities. Stratégies d'estimation pour un panel dynamique spatial faisant usage de GMM. Une nouvelle approche pour le problème de la convergence de régions d'Europe Rèsumè Bien que les méthodes d'estimation pour les données de panels dynamiques, et les modèles économétriques spatiaux, sont des instruments standards dans les ouvrages d’économie, on a assisté à une évolution relativement récente des méthodes, qui comprend des considérations spatiales dans les modèles de panels dynamiques. La présente communication propose deux stratégies d'estimation concernant des modèles de données de panel dynamique spatiales faisant usage de la méthodes des moments généralisés (MMG). La première consiste à étendre les restrictions de moments de l'estimateur d'Arellano et Bond à un panel dynamique autorégressif spatial. La deuxième tient compte de la dépendance spatiale dans le processus des erreurs. L'application empirique se concentre sur l'expansion régionale en Europe au cours d'une période de 25 ans. Nous relevons des preuves empiriques de convergence conditionnelle, qui sont affectées de façon significative par des disparités spatiales. Estrategias de estimación para un panel dinámico espacial utilizando GMM. Un nuevo planteamiento de la cuestión de la convergencia de regiones europeas Extracto Aunque los métodos de estimación para datos dinámicos de panel y modelos econométricos espaciales son estándar en la bibliografía económica, se ha producido un desarrollo relativamente reciente en dichos métodos que incluye consideraciones espaciales en modelos de datos dinámicos de panel. Este estudio propone dos estrategias de estimación para los modelos de datos espaciales dinámicos de panel utilizando el método general de momentos (GMM). El primero sirve para extender las restricciones de momentos del estimador de Arellano y Bond a un panel espacial dinámico autorregresivo. El segundo tiene en cuenta una dependencia espacial en el proceso de error. La aplicación empírica se centra en el crecimiento regional europeo en un período de 25 años. Descubrimos evidencia empírica de convergencia condicional, que es afectada significativamente por disparidades espaciales.

Suggested Citation

  • Salima Bouayad-Agha & Lionel Védrine, 2010. "Estimation Strategies for a Spatial Dynamic Panel using GMM. A New Approach to the Convergence Issue of European Regions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(2), pages 205-227.
  • Handle: RePEc:taf:specan:v:5:y:2010:i:2:p:205-227
    DOI: 10.1080/17421771003730711
    as

    Download full text from publisher

    File URL: http://www.taylorandfrancisonline.com/doi/abs/10.1080/17421771003730711
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Spatial econometrics; dynamic panel model; GMM; regional convergence; C21; C23; O52; R11;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:specan:v:5:y:2010:i:2:p:205-227. 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: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/RSEA20 .

    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.

    We have no references for this item. You can help adding them by using 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 RePEc Author Service 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.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.