Spatial dynamic panel data models with interactive effects
Vasilis Sarafidis
Economics Virtual Symposium 2025 from Stata Users Group
Abstract:
We introduce a new instrumental-variables (IV) approach for spatial dynamic panel-data models with interactive effects under large N and T asymptotics. Alongside the methodology, we present the spxtivdfreg spxtivdfreg spxtivdfreg spxtivdfreg package, which implements the proposed approach in Stata. Most existing approaches in this literature rely on quasi–maximum likelihood estimation. Our IV approach is appealing from both theoretical and practical standpoints for several reasons. First, it is linear in the parameters of interest and computationally inexpensive. Second, the IV estimator avoids the asymptotic bias that typically arises from the incidental parameters problem. Third, the approach accommodates endogenous regressors, provided suitable external instruments are available. For the homogeneous-slope case, we develop a pooled two-stage IV (2SIV) estimator, which is consistent and asymptotically normal as N and T grow large. For the heterogeneous-slope case, we propose an N - consistent mean group IV (MGIV) estimator based on averaging individual- specific estimated slopes. To our knowledge, no existing method in the literature allows for this level of heterogeneity in dynamic spatial models with interactive effects. We also provide practical guidance on how best to run these methods in Stata.
Date: 2025-11-07
References: Add references at CitEc
Citations:
Downloads: (external link)
http://repec.org/econ2025/Econ25_Sarafidis.pdf presentation materials (application/pdf)
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:boc:econ25:01
Access Statistics for this paper
More papers in Economics Virtual Symposium 2025 from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().