This paper places the key issues and implications of the new 'introductory' book on spatial econometrics by James LeSage & Kelley Pace (2009) in a broader perspective: the argument in favour of the spatial Durbin model, the use of indirect effects as a more valid basis for testing whether spatial spillovers are significant, the use of Bayesian posterior model probabilities to determine which spatial weights matrix best describes the data, and the book's contribution to the literature on spatiotemporal models. The main conclusion is that the state of the art of applied spatial econometrics has taken a step change with the publication of this book.Relever le niveau de l'économetrie spatial appliquée RÉ SUMÉ La pre´sente communication place les principales questions et implications du nouvel ouvrage d'introduction sur l'e´conome´tries spatiale de James LeSage & Kelley Pace (2009) dans un contexte plus ge´ne´ral: l'argument favorisant le mode`le spatial de Durbin, l'emploi d'effets indirects comme base plus valable pour e´valuer l'aspect significatif des de´versements spatiaux, l'emploi des probabilite´s d'un mode`le baysien poste´rieur pour e´valuer laquelle des matrices de poids spatiaux de´crit le mieux les donnes, et la contribution de l'ouvrage la documentation sur les mode`les spatio-temporels. La principale conclusion est qu'avec la publication de cet ouvrage, l'e´tat de l'art de l'e´conome´tries spatiale applique a effectue´un grand pas en avant.Alzar el nivel de la econometría espacial aplicada RÉ SUMÉ Este trabajo plantea las cuestiones e implicaciones clave del nuevo libro introductorio sobre econo´metra espacial de James LeSage & Kelley Pace (2009) dentro de una perspectiva ma´s amplia: el argumento a favor del modelo espacial Durbin, el uso de efectos indirectos como una base ma´s válida para poner a prueba si los desbordamientos espaciales son significativos, el uso de probabilidades posteriores bayesianas para descubrir que matriz de pesos espaciales describe mejor los datos, y la contribucio´n del libro a la biblio´grafa sobre modelos espaciotemporales. La principal conclusio´n es que la econometría espacial aplicada ma´s avanzada ha experimentado un cambio radical con la publicacio´n de este libro.

This article provides a survey of the specification and estimation of spatial panel data models. These models include spatial error autocorrelation, or the specification is extended with a spatially lagged dependent variable. In particular, the author focuses on the specification and estimation of four panel data models commonly used in applied research: the fixed effects model, the random effects model, the fixed coefficients model, and the random coefficients model. The survey discusses the asymptotic properties of the estimators and provides guidance with respect to the estimation procedures, which should be useful for practitioners.

Elhorst (2003, 2010a) provides Matlab routines to estimate spatial panel data models at his Web site. This paper extends these routines to include the bias correction procedure proposed by Lee and Yu (2010a)

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Abstract.  This paper provides an integrated overview of theoretical and empirical explanations used in the applied literature on regional unemployment differentials. On the basis of 41 empirical studies, four different model types covering nine theoretical constructs of regional unemployment determination and 13 sets of explanatory variables are identified. The overall conclusion is that theoretical and empirical explanations help to reduce the weaknesses in each other. While theory is found to predict that the regional unemployment rate depends on labour supply factors (a collection of factors which affect natural changes in the labour force, labour force participation, migration and commuting), labour demand factors and wage‐setting factors, it is the empirical studies that provide a more profound understanding of the explanatory variables involved. Conversely, whereas most empirical studies provide clear‐cut explanations for the signs of the explanatory variables, it is theory that shows that some of these explanations might be out of proportion. By grouping many studies together, this paper shows that there are indeed clear‐cut trends.