In this paper, we propose an integrated modified harmonic mean estimator (IHME) for nested and non-nested model selection problems in spatial panel data models with entity and time fixed effects. We formulate the IHME based on the integrated likelihood functions obtained by analytically integrating out the high-dimensional entity and time fixed effects from the complete likelihood functions. To investigate the finite sample properties of the IHME, we design a comprehensive simulation study that allows for both nested and non-nested model selection exercises in some popular spatial panel data models. Our simulation results show that the IHME has excellent finite sample performance and outperforms some competing estimators in terms of precision. We provide an empirical application on the US house price changes to show the usefulness of the proposed IHME in a model selection exercise.
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