The discrete choice literature has evolved from the analysis of a choice of a single item from a fixed choice set to the incorporation of a vast array of more complex representations of preferences and choice set formation processes into choice models. Modern discrete choice models include rich...

This paper explores five under-recognised conceptual issues in the use of discrete choice tasks in eliciting a tariff for health and/or quality of life instruments. Its purpose is not to explore econometric and statistical techniques but to offer advice on design and practical matters gleaned...

We study panel data estimators based on a discretization of unobserved heterogeneity when individual heterogeneity is not necessarily discrete in the population. We focus on two-step grouped-fixed effects estimators, where individuals are classified into groups in a first step using kmeans...

This paper estimates returns to education using a dynamic model of educational choice that synthesizes approaches in the structural dynamic discrete choice literature with approaches used in the reduced form treatment effect literature. It is an empirically robust middle ground between the two...

This paper estimates returns to education using a dynamic model of educational choice that synthesizes approaches in the structural dynamic discrete choice literature with approaches used in the reduced form treatment effect literature. It is an empirically robust middle ground between the two...

Our paper contributes to bridge the gap between the microsimulation’s approach and applied GE models, by making use of exact aggregation results from the discrete choice literature: heterogeneous individuals choosing (possibly continuous amounts) within a set of discrete alternatives may be...

Households are forward-looking when deciding whether to default on or refinance their mortgages. There are two types of default generated by two mechanisms: illiquidity-triggered default and strategic default. However, researchers can observe only whether households default but not whether the...

The Expectation-Maximization (EM) algorithm is a well-established estimation procedure which is used in many domains of econometric analysis. Recent application in a discrete choice framework (Train, 2008) facilitated estimation of latent class models allowing for very exible treatment of...

We examine various and different approaches for the prediction of economic crisis periods of US economy. We examine the traditional econometric discrete choice Logit and Probit models then a feed-forward neural network (FFNN) model and finally we apply an Adaptive Neuro-Fuzzy Inference System...