Introduction to Spatial Econometrics

By M. Ugarte. 2011

4,425 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/abfbbe2bd56a176fa706a3feda40649810ba442c

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Citations in the corpus

Cross-Border Interbank Networks, Banking Risk and Contagion (2015, methodology): “To take network effects into account and to detect if banking stability in a particular country i is affected by the riskiness of the banking systems of all countries j to which banks in the given country lend or from which they borrow, I make use of a spatial interaction term (Anselin, 1988; LeSage”
Spatial Panel-data Models Using Stata (2017, positive): “This is due to the fact that xsmle, by default, uses the Monte Carlo procedure outlined in LeSage and Pace (2009), hence the point estimates (standard errors) are averages (standard deviations) over the (default) 500 Monte Carlo replications.”
On spatial econometric models, spillover effects, and W (2013, methodology): “LeSage and Pace (2009) propose to report one direct effect measured by the average of the diagonal elements and one spillover effect measured by the average row sums of the off-diagonal elements.”
Maximum likelihood estimation of a spatial autoregressive Tobit model (2015, background): “LeSage (2000) and LeSage and Pace (2009) consider the Bayesian estimation of the spatial autoregressive Tobit (SART) model.”
Monetary Policy Through Production Networks: Evidence from the Stock Market (2017, background): “The standard SAR model is a special case of equation (18) in which D(ρ) is a scalar and β is identical across industries (see LeSage and Pace (2009)).”
Interpreting dynamic space-time panel data models (2012, methodology): “However, for interpretative purposes we follow [8] who note that the columns represent a partial derivative change arising from a change in a single region, whereas the rows reflect changes in all regions.”
Education or Creativity: What Matters Most for Economic Performance? (2012, positive): “The change in the dependent variable caused by a unit change in one given explanatory variable amounts to the total effect, which is given by the sum of the direct effect, generated by the change in a certain region’s own regressor, and the indirect effect due to spillovers (Le Sage and Pace 2009).”
Bayesian Model Averaging for Spatial Autoregressive Models Based on Convex Combinations of Different Types of Connectivity Matrices (2020, methodology): “For the standard SAR model, LeSage and Pace (2009) derived these partial derivatives along with scalar summary measures reflecting own- and cross-partial derivatives that they label average direct and indirect effects.”
The determinants of regional specialisation in business services: agglomeration economies, vertical linkages and innovation (2015, background): “The second interpretation measures the cumulative impact of a change in each explanatory variable in region i over all neighbouring regions, which LeSage and Pace (2009) label the average total impact from an observation (see also Le Sage and Fischer, 2008).”
Quantifying Knowledge Spillovers Using Spatial Econometric Models (2009, neutral): “Oerlemans and Meeus (2005) and Capello and Faggian (2005) analyze the impact of proximity and industrial organization on innovation and firm performance.”
US Metropolitan Area Resilience: Insights from dynamic spatial panel estimation (2017, background): “It is now standard practice to acknowledge that the effect of a variable should equal the true derivative of ln y with respect to ln x, which in the presence of significant spatial lag and dynamic effects is not simply the estimate ̂ [Le Sage and Pace (2009) and Elhorst (2014)].”
Regional Branching and Key Enabling Technologies: Evidence from European Patent Data (2017, background): “Because exclusive reference to coefficients may not be reliable in ascertaining the existence of spatial spillovers (Le Sage and Pace 2009), following Elhorst (2014b), in the lower part of Table 9, we look at the effects that a change in our explanatory variables in a particular region have on the…”
Proximity, networking and knowledge production in Europe: What lessons for innovation policy? (2013, background): “The only previous study which provides an analogous KPF econometric setting, where the relational/social matrix (based on FP5 links) is introduced as a weight matrix, is Maggioni et al. (2007), although they estimate a SEM rather than a SAR model.”