Suchergebnisse

AbstractWe investigate the problem of endogeneity and measurement bias arising from incorporating indicator variables (e.g., measures of attitudes) into discrete choice models. We demonstrate that although a hybrid choice framework can resolve both endogeneity and measurement problems, the former requires explicit accounting for in the model, which has not typically been done in applied studies to date. By conducting a Monte Carlo experiment, we demonstrate the extent of the bias resulting from measurement and endogeneity problems. We propose two novel solutions to address the endogeneity problem: explicitly accounting for correlation between structural and discrete choice component error terms (or with random parameters in a utility function), or introducing additional latent variables. Using simulated data, we demonstrate that these approaches work as expected, i.e. they successfully recover the true values of all model parameters.

AbstractThe coast plays a significant recreational role in the nine countries around the Baltic Sea. More than 70% of the population of these countries visit the coast, representing some 80 million recreational visits annually. Understanding the values associated with coastal recreation, and the potential welfare changes resulting from improvements in the state of environmental and infrastructure conditions of the Baltic Sea coast is important for marine environment management in the region. We estimate a spatially explicit travel cost model for Baltic coast recreation to assess the welfare of accessing individual sites, identify recreational hot spots and simulate the welfare changes resulting from improvements in environmental and infrastructure conditions. The total benefits associated with Baltic Sea coast-based recreation amount to 27.5 billion EUR per year with significant variation across sites. Improving water quality and infrastructure boost the recreational value by nearly 6.2 billion EUR, an increase of about a fifth of the existing recreational benefits.