EconPapers    
Economics at your fingertips  
 

Contemporary developments in the theory and practice of spatial econometrics

Arnab Bhattacharjee, Sean Holly and Jesus Mur

Spatial Economic Analysis, 2018, vol. 13, issue 2, 139-147

Abstract: The papers in this special issue cover a wide range of areas in the methodology and application of spatial econometrics. The first develops a generalized method of moments (GMM) estimator for the spatial regression model from a second-order approximation to the maximum likelihood (ML). The second develops Bayesian estimation in a stochastic frontier model with network dependence in efficiencies, with application to industry dynamics. The third studies cross-country convergence under the Lotka–Volterra model and obtains new insights into spatial spillovers. The penultimate paper develops robust specification tests for the social interactions model under both ML and GMM frameworks. The final paper proposes identification and GMM estimation in a high-order spatial autoregressive model with heterogeneity, common factors and spatial error dependence.

Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/17421772.2018.1449824 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:specan:v:13:y:2018:i:2:p:139-147

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RSEA20

DOI: 10.1080/17421772.2018.1449824

Access Statistics for this article

Spatial Economic Analysis is currently edited by Bernie Fingleton and Danilo Igliori

More articles in Spatial Economic Analysis from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-31
Handle: RePEc:taf:specan:v:13:y:2018:i:2:p:139-147