This paper consistently estimates the structural properties of a fishery resource extraction technology. We overcome two ubiquitous features of fisheries data generating processes that invalidate classical estimators: unobservability by the researcher (but partial observability by fishermen) of the fish stock, and endogenous production decisions that vary with private information about stock abundance and economic variables. We adopt methods used in fisheries stock assessment to control for unobserved stock effects on productivity. A nonlinear instrumental variables estimator controls for endogenous choices of the output mix. The approach is applied to the US Gulf of Mexico commercial reef fish fishery. Comparison with an estimator that ignores latent stock abundance and endogeneity in production indicates substantial bias which can be linked to past fishery management failure.
Original Release Date: December 20, 2018
Revisions: February 2, 2019; February 27, 2019
Latest Revision: November 11, 2019
Department of Economics, Iowa State University
Weninger, Quinn; Perruso, Larry; and Bunzel, Helle, "Identification of resource extraction technologies when the resource stock is unobservable" (2019). Economics Working Papers: Department of Economics, Iowa State University. 18015.