In this paper we consider ML estimation for a broad class of parameter-driven models for discrete dependent variables with spatial correlation. Under this class of models, which includes spatial discrete choice models, spatial Tobit models and spatial count data models, the dependent variable is...

In this paper we introduce a new flexible mixed model for multinomial discrete choice where the key individual- and alternative-specific parameters of interest are allowed to follow an assumptionfree nonparametric density specification while other alternative-specific coefficients are assumed to...

I estimate a forward-looking, dynamic, discrete-choice monetary policy reaction function for the US economy, that accounts for the fact that there are substantial restrictions in the period-to-period changes of the Fed's policy instrument. I find a substantial contrast between the periods before...

This study investigates why the strong form of the spatial equilibrium is weakly supported in the literature. Using a discrete choice model, it shows that the strong form of the spatial equilibrium is rarely observed because workers are imperfectly mobile from the perspective of researchers....

Our goal in this chapter is to explain concretely how to implement simulation methods in a very general class of models that are extremely useful in applied work: dynamic discrete choice models where one has available a panel of multinomial choice histories and partially observed payoffs....

Discrete Choice Experiments (DCEs) designed to estimate willingness-to-pay (WTP) values are very popular in health economics. With increased computation power and advanced simulation techniques, random-coefficient models have gained an increasing importance in applied work as they allow for...

This paper empirically examines the determinants of the demand for alternative energy sources and propulsion technologies in vehicles. The data stem from a stated preference discrete choice experiment with 598 potential car buyers. In order to simulate a realistic automobile purchase situation,...

We present examples based on actual and synthetic datasets to illustrate how simulation methods can mask identification problems in the estimation of discrete choice models such as mixed logit. Simulation methods approximate an integral (without a closed form) by taking draws from the underlying...

Sequential decision making among agents is a noticeable feature in strategic interactions in many subjects. The full estimation of sequential games, however, has been problematic due to the computational burden, especially when the game is large and asymmetric. In this paper, I propose an...

This paper empirically examines the determinants of the demand for alternative energy sources and propulsion technologies in vehicles. The data stem from a stated preference discrete choice experiment with 598 potential car buyers. In order to simulate a realistic automobile purchase situation,...