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Properties of the Stochastic Distance Function and its Role in Fisheries Analyses


In this work we examine the ability of the normalized stochastic output distance function to properly approximate the curvature properties of different underlying production technologies. The distance function is a natural tool for fishery production models in that it does not require cost data (only data on input and output quantities are necessary), which is often unavailable, and it can accommodate multi-input, multi-output relationships (common in fisheries). However, Monte Carlo experiments have indicated that data characterized by certain characteristics may not be properly approximated by the normalized stochastic distance function. Thus, one could erroneously conclude that there are economies of scope in a multi-species fishery, when in fact vessels may have lower marginal costs targeting only one species (but restrictive TACs on one species or trip limits lead vessels to target several species to recover fixed costs). This work is being conducted jointly with Dan Holland at the University of Massachusetts, Dartmouth.

Source: Unpublished

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