An Overview on Econometric Models for Linear Spatial Panel Data
Brajendra C. Sutradhar ()
Additional contact information
Brajendra C. Sutradhar: Carleton University
Sankhya A: The Indian Journal of Statistics, 2021, vol. 83, issue 1, No 9, 206-244
Abstract:
Abstract When spatial data are repeatedly collected from the same spatial locations over a short period of time, a spatial panel/longitudinal data set is generated. Thus, this type of spatial longitudinal data must exhibit both spatial and longitudinal correlations, which are not easy to model. This work is motivated by existing studies in statistics and econometrics literature but the proposed model and inference procedures should be applicable to the spatial panel data encountered in other fields as well such as environmental and/or ecological setups. Specifically, unlike the existing studies, we propose a new dynamic mixed model to accommodate both spatial and panel correlations. A complete theoretical analysis is given for the estimation of regression effects, and spatial and panel correlations by exploiting second and higher order moments based quasi-likelihood methods. Asymptotic properties are also studied in details. The step by step estimation results developed in the paper should be useful to the practitioners dealing with spatial panel data.
Keywords: Spatial panel dynamic mixed model; spatial correlations; auto-regression type dynamic model for panel data; quasi-likelihood and moment estimation; consistency and asymptotic normality.; Primary 62H11; 62H12; Secondary 62H20 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s13171-019-00178-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:spr:sankha:v:83:y:2021:i:1:d:10.1007_s13171-019-00178-z
Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/13171
DOI: 10.1007/s13171-019-00178-z
Access Statistics for this article
Sankhya A: The Indian Journal of Statistics is currently edited by Dipak Dey
More articles in Sankhya A: The Indian Journal of Statistics from Springer, Indian Statistical Institute
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().