We elicit homeowners' marginal willingness to pay (MWTP) for energy efficiency and low-carbon technologies in the context of replacement heating appliances. We exploit a novel within-between subject design that involves manipulating information in a two-stage discrete choice experiment (DCE) and...

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...

Empirical models of demand for -- and, often, supply of -- differentiated products are widely used in practice, typically employing parametric functional forms and distributions of consumer heterogeneity. We review some recent work studying identification in a broad class of such models. This...

How to deal with the risks associated with nuclear energy is a major policy issue. This paper investigates the effect of an individual's distance from nuclear power plants on its willingness to pay for increased insurance coverage against nuclear accidents (MWPC) as well as on willingness to pay...

Previous literature on the distribution of willingness to pay has focused on its heterogeneity distribution without addressing exact interval estimation. In this paper we derive and analyze Bayesian confidence sets for quantifying uncertainty in the determination of willingness to pay for carbon...