INTRODUCTION: WHITHER SPATIAL ECONOMETRICS?
By Mark D. Partridge, Marlon Boarnet, S. Brakman, Gianmarco I. P. Ottaviano. 2012
110 citations recorded by the source corpus.
Subfields: Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/c87ea72c413da359a01e0fb0bb584a6bc7a798b0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Raffaele Paci
- Emanuela Marrocu
- Stefano Raimondo Usai
- G. Resende
- A. Carvalho
- Patricia A. M. Sakowski
- T. Cravo
- Solmaria Halleck Vega
Citations in the corpus
- The Slx Model (2015, methodology): “Partridge et al. (2012) provide an overview of the three contributing papers of Gibbons and Overman (2012), McMillen (2012), and Corrado and Fingleton (2012).”
- On spatial econometric models, spillover effects, and W (2013, background): “Partridge et al. (2012) provide an overview of the three contributing papers.”
- The Composite Marginal Likelihood (CML) Inference Approach with Applications to Discrete and Mixed Dependent Variable Models (2014, background): “Studies of two correlated ordered-response outcomes include Scotti (2006), Mitchell and Weale (2007), Scott and Axhausen (2006), and LaMondia and Bhat (2011).”
- Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models (2016, background): “(5), which may better identify causality in most cases (see Partridge et al. 2012, for a comprehensive discussion).11 Equation (5) may incorporate a spatial lag of the dependent variable (known as Spatial Durbin Model/SDM).”
- Proximity, networking and knowledge production in Europe: What lessons for innovation policy? (2013, background): “14 The SAR specification has recently been criticized (Partridge et al., 2012 and Gibbons and Overman, 2012) for lacking identification of the ρ parameter (see model 2) when the weight matrix is block-diagonal and idempotent.”
- Recessions, recoveries and regional resilience: evidence on Italy (2015, background): “It is well-known that the SUR model is able to capture simultaneous spatial interdependencies among different units without specifying the familiar spatial matrix (W), overcoming some theoretical issues recently observed (Partridge et al., 2012).”