Three essays on stated choice experiments for nonmarket valuation of landslide protection

This thesis consists of three essays that improve the general understanding of the public demand for safety programmes in the context of natural hazards. With the growing importance of this topic around the world, this study provides a practical and methodological contribution to the literature on Environmental Economics and Policy, especially local policy. In particular, this research examines people’s preferences and their willingness-to-pay for landslide mitigation programmes. The primary aim is to assess how the residents of and visitors to a mountain valley in the Alps value and trade off the multiple attributes of protection programmes for landslide risk reduction by applying Discrete Choice Modelling methodology. To address the current needs of local decision-makers, the investigation of the determinants of preference heterogeneity is the central theme of the research. The study is based on a panel choice dataset created from a Discrete Choice Experiment, based on full ranking, administered in person by the author to 250 respondents in the Boite Valley, Italy. The first essay examines the stability of preferences, investigating to what extent additional information has an impact on estimated values. Specifically, it studies whether respondents adjust their preferences based on scientific information provided on one specific attribute. A mixed logit model in willingness-to-pay space is implemented to account for preference heterogeneity. The findings suggest that respondents perceive the existing protection measures as insufficient. The provision of information affects only the attribute subject to additional information and the consideration of the current status of protection. Preferences for the other attributes remained stable. Preliminary evidence of spatial heterogeneity is also detected. The second essay addresses the issue of the stability of parameter estimates obtained through simulation using choice models with latent variables. Specifically, it ana