Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances
Leopoldo Catania () and
Anna Gloria Bill\'e
Authors registered in the RePEc Author Service: Anna Gloria Billé ()
Papers from arXiv.org
We propose a new class of models specifically tailored for spatio-temporal data analysis. To this end, we generalize the spatial autoregressive model with autoregressive and heteroskedastic disturbances, i.e. SARAR(1,1), by exploiting the recent advancements in Score Driven (SD) models typically used in time series econometrics. In particular, we allow for time-varying spatial autoregressive coefficients as well as time-varying regressor coefficients and cross-sectional standard deviations. We report an extensive Monte Carlo simulation study in order to investigate the finite sample properties of the Maximum Likelihood estimator for the new class of models as well as its flexibility in explaining several dynamic spatial dependence processes. The new proposed class of models are found to be economically preferred by rational investors through an application in portfolio optimization.
Date: 2016-02, Revised 2023-01
New Economics Papers: this item is included in nep-ets, nep-geo and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed
Downloads: (external link)
http://arxiv.org/pdf/1602.02542 Latest version (application/pdf)
Journal Article: Dynamic spatial autoregressive models with autoregressive and heteroskedastic disturbances (2017)
Working Paper: Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1602.02542
Access Statistics for this paper
More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().