This study investigates spatial segregation of the population in fiscally decentralized urban areas. The theoretical part proposes the progressivity of local income taxes as a new explanation for income segregation. The empirical part studies how income tax differentials across municipalities in...

This study investigates spatial segregation of the population in fiscally decentralized urban areas. The theoretical part proposes the progressivity of local income taxes as a new explanation for income segregation. The empirical part studies how income tax differentials across municipalities in...

Until recently, inference in many interesting models was precluded by the requirement of high dimensional integration. But dramatic increases in computer speed, and the recent development of new algorithms that permit accurate Monte Carlo evaluation of high dimensional integrals, have greatly...

Discrete choice models are widely used in studies of recreation demand. They have proven valuable when modeling situations where decision makers face large choice sets and site substitution is important. However, when the choice set faced by the individual becomes very large (on the order of...

A number of authors have discussed the possible advantages of conditioning parameter distributions on observed choices when working with Mixed Multinomial Logit models. However, the number of applications is still relatively small, partly due to a limited implementation in available software. To...

Discrete choice models are widely used in studies of recreation demand. They have proven valuable when modeling situations where decision makers face large choice sets and site substitution is important. However, when the choice set faced by the individual becomes very large (on the order of...

The choice of a specific distribution for random parameters of a discrete choice model is a critical issue in transportation analysis. Indeed, various pieces of research have demonstrated that an inappropriate choice of the distribution may lead to serious biases in model forecast and in the...