Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/32107
Title: Estimating Spatial Dynamic Panel Data Models with Unobserved Common Factors in Stata
Authors: Kripfganz, S
Sarafidis, V
Keywords: panel data;longitudinal models;time lags;spatial lags;unobserved common factors;cross-sectional dependence;instrumental variables;heterogeneous coefficients;Stata
Issue Date: 28-Jul-2025
Publisher: American Statistical Association Publications
Citation: Kripfganz, S. and Sarafidis, V. (2025) 'Estimating Spatial Dynamic Panel Data Models with Unobserved Common Factors in Stata', Journal of Statistical Software, 113 (6), pp. 1 - 27. doi: 10.18637/jss.v113.i06.
Abstract: This article introduces the spxtivdfreg package in Stata, which implements a general instrumental variables (IV) approach for estimating dynamic spatial panel data models with unobserved common factors or interactive effects, when the number of both cross-sectional and time series observations is large. The estimator has been developed in a recent paper by Cui, Sarafidis, and Yamagata (2023). The underlying idea is to project out the common factors from exogenous covariates using principal components analysis, and to run IV regression in both of two stages, using defactored covariates (and their spatial counterparts) as instruments. The resulting two-stage IV estimator is valid for models with homogeneous slope coefficients, and has several advantages relative to existing popular approaches. In addition, the spxtivdfreg package allows estimation of short-run and long-run direct and indirect effects, as well as total effects, accounting for the cumulative effects over time and across space. Standard errors for such effects are computed using the Delta method. Last, the spxtivdfreg package allows for heterogeneous slope coefficients, as in Chen, Cui, Sarafidis, and Yamagata (2025). In particular, we construct a "mean group" IV estimator, which involves averaging first-step IV estimates of individual-specific slope coefficients.
Description: Article: Creative Commons Attribution License (CC-BY) Software: GPL General Public License version 2 or version 3 or a GPL-compatible license.
URI: https://bura.brunel.ac.uk/handle/2438/32107
DOI: https://doi.org/10.18637/jss.v113.i06
Other Identifiers: ORCiD: Sebastian Kripfganz https://orcid.org/0000-0002-7670-0834
ORCiD: Vasilis Sarafidis https://orcid.org/0000-0001-6808-3947
Appears in Collections:Dept of Economics and Finance Research Papers

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