Parameter estimates of structural economic models are often difficult to interpret at the light of the underlying economic theory. Bayesian methods have become increasingly popular as a tool for conducting inference on structural models since priors offer a way to exert control over the...

We consider treatment effect estimation via a difference-in-difference approach for data with local spatial interaction such that the outcome of observed units depends on their own treatment as well as on the treatment status of proximate neighbors. We show that under standard assumptions...

In a discrete model, the predicted probabilities of a particular eventcan be matched to the observed (0, I) outcomes and this will give riseto a measure of fit for that event. Previous results for the binomialmodel are applied to multinomial models. In these models the measureof fit will vary...

Spatial effects are endemic in models based on spatially referenced data. The increased awareness of the relevance of spatial interactions, spatial externalities and networking effects among actors, evoked the area of spatial econometrics. Spatial econometrics focuses on the specification and...

Mundlak (1978) proposed the addition of time averages to the usual panel equation in order to remove the fixed effects bias. We extend this Mundlak equation further by replacing the time-varying explanatory variables by the corresponding deviations from the averages over time, while keeping the...