  The paper proposes a Bayesian multinomial logit model to analyse spatial
patterns of urban expansion. The specification assumes that the log-odds of
each class follow a spatial autoregressive process. Using recent advances in
Bayesian computing, our model allows for a computationally efficient treatment
of the spatial multinomial logit model. This allows us to assess spillovers
between regions and across land use classes. In a series of Monte Carlo
studies, we benchmark our model against other competing specifications. The
paper also showcases the performance of the proposed specification using
European regional data. Our results indicate that spatial dependence plays a
key role in land sealing process of cropland and grassland. Moreover, we
uncover land sealing spillovers across multiple classes of arable land.
