Hierarchical or "multilevel" regression models typically parameterize the mean response conditional on unobserved latent variables or "random" effects and then make simple assumptions regarding their distribution. The interpretation of a regression parameter in such a model is the change in...

In this paper we develop a dynamic model for integer counts to capture the dis- creteness of price changes for financial transaction prices. Our model rests on an autoregressive multinomial component for the direction of the price change and a dynamic count data component for the size of the...

It is well understood that the two most popular empirical models of location choice - conditional logit and Poisson - return identical coefficient estimates when the regressors are not individual specific. We show that these two models differ starkly in terms of their implied predictions. The...

It is well known that the bridge regression (with tuning parameter less or equal to 1) gives asymptotically unbiased estimates of the nonzero regression parameters while shrinking smaller regression parameters to zero to achieve variable selection. Despite advances in the last several decades in...