Bayesian Spatial Panel Model
The Bayesian Spatial Panel Model estimates spatial interaction effects (spatial lag, spatial error, or Durbin) in panel data using Bayesian inference via Markov Chain Monte Carlo (MCMC). It combines the ability to control for unobserved unit- and time-specific heterogeneity with principled uncertainty quantification, making it suitable for georeferenced longitudinal datasets in economics, public health, and regional science.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. · ISBN 978-1420064247
- Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. · ISBN 978-3642403392
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
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Related methods
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