Interpreting dynamic space-time panel data models

DOI10.1016/J.STAMET.2011.02.002zbMath1248.62167OpenAlexW2016583478MaRDI QIDQ713935

James P. Lesage, Nicolas Debarsy, Cem Ertur

Publication date: 19 October 2012

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2011.02.002

zbMATH Keywords

Markov chain Monte Carlo estimationdynamic responses over time and space

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (9)

On the Mutual Dynamics of Interregional Gross Migration Flows in Space and Time ⋮ Measuring sovereign risk spillovers and assessing the role of transmission channels: a spatial econometrics approach ⋮ Markov chain Monte Carlo estimation of spatial dynamic panel models for large samples ⋮ Impact Analysis for Spatial Autoregressive Models: With Application to Air Pollution in China ⋮ Beyond distance: the spatial relationships of European regional economic growth ⋮ Unnamed Item ⋮ Modeling US housing prices by spatial dynamic structural equation models ⋮ Space-time transport schemes and homogenization. I: general theory of Markovian and non-Markovian processes ⋮ Estimation of spatial panel data models with time varying spatial weights matrices

Uses Software

• Arc_Mat

Cites Work

• Unnamed Item
• Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances
• Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both \(n\) and \(T\) are large
• A space-time filter for panel data models containing random effects
• Handbook of Spatial Statistics
• Reference priors with partial information

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