Scale-dependency in discrete choice models: A fishery application

Modeling the spatial behavior of fishers is critical in assessing fishery management policies and has been dominated by discrete choice models (DCM). Motivated widespread availability micro-data on fishing vessel locations, this paper examines complexity associated with scale a DCM locations. Our empirical approach estimates standard at varying resolutions using both simulated data monitoring system from Gulf Mexico longline fishery. We assess model performance goodness-of-fit, predictive capacity, parameter estimates, assessment response to hypothetical marine protected area. Results show that, even when specification decision-making process correct, can be structurally biased because aggregation that neglects value many The extent such biases only detected considering various levels.