Estimation of spatial panel data models with time varying spatial weights matrices

- We investigate spatial panel data models with time varying spatial weights matrices.
- Asymptotic properties of QMLE is derived.
- Estimation and inference for the impact analysis are studied.
- Simulations show that parameter and impact estimators have satisfactory performance.
- Simulations show that misspecification of weights matrices causes substantial biases.

This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models where spatial weights matrices can be time varying. We show that QML estimate is consistent and asymptotically normal. We also derive the asymptotic distribution of average impact coefficients (direct, indirect, total). Monte Carlo results are reported to investigate the finite sample properties of QML estimates and impact coefficients.