estimateW: An R Package for Bayesian Estimation of Weight Matrices in Spatial Econometric Panels

Tamás Krisztin and Philipp Piribauer
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Tamás Krisztin: International Institute for Applied Systems Analysis
Philipp Piribauer: WIFO

No 722, WIFO Working Papers from WIFO

Abstract: This document introduces the R library estimateW to estimate spatial weight matrices for Bayesian spatial econometric panel models. The approach focuses on spatial weights that are binary prior to row-standardization. However, unlike recent literature our approach requires no strong a priori assumptions on (socio-)economic distances between the spatial units. The estimation approach relies on efficient Bayesian Gibbs sampling techniques and the library supports a variety of the most common spatial econometric panel specifications. estimateW moreover supports to elicit flexible shrinkage priors, which allow to estimate spatial spillovers even in settings where the number of time period is small relative to number of cross-sectional units. An empirical illustration for European NUTS-1 regions demonstrates that the method recovers plausible spatial dependence patterns, interpretable spillover effects, and meaningful clustering in the estimated network structure.

Keywords: Bayesian spatial econometrics; spatial weight matrix estimation; regional economic growth; R (search for similar items in EconPapers)
Pages: 25 pages
Date: 2026-03-17
New Economics Papers: this item is included in nep-eff, nep-geo and nep-net
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Persistent link: https://EconPapers.repec.org/RePEc:wfo:wpaper:y:2026:i:722

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