What drives the designation of protected areas? Accounting for spatial dependence using a composite marginal likelihood approach

Abstract

Previous research indicates that policymakers make biodiversity conservation decisions with the goal of mini-mizing opportunity costs, as opposed to balancing conservation benefits and opportunity costs. However, such research used coarse biodiversity data and did not consider spatial dependence in observed conservation de-cisions. The present study estimates conservation choice models for two European countries (Spain and Italy) that, for the first time, include fine-resolution indicators of biodiversity conservation benefits and opportunity costs, and that account for spatial dependence using a pairwise composite marginal likelihood approach. For the preferred model specifications, we find that a 1% increase in species richness levels is associated with increases in the probability of protection of 0.59% and 0.22% in Spain and Italy, respectively. We also find evidence of spatial correlation and that accounting for it substantially affects the elasticity effects implied by the logit regression models. Although our findings confirm that protected area designations are consistently negatively associated with the potential for productive land-uses, local biodiversity levels may have played a larger role in protected area location decisions than suggested previously.