Working Paper: NBER ID: w28732
Authors: Jose Pizarro; Eduardo S. Schwartz
Abstract: The literature on the optimal harvest of fisheries has concentrated on a single fishing area with biomass uncertainty and to a lesser degree also with price uncertainty. We develop and implement a stochastic optimal control approach to determine the harvest that maximizes the value of a fishery participating in a global market, where all the considered harvesting zones sell their production. This market is characterized by an inverse demand function, which combines an exogenous demand shock and the aggregate harvesting of all zones. Accordingly, a fishery's harvest will be affected by the global demand shocks and the harvesting in all the competing zones through the global selling price. In addition, we decompose the biomass uncertainty into local and global biomass shocks. Through global biomass shocks, the model provides enough flexibility to acknowledge for correlation in the biomass shocks faced by the multiple perhaps adjacent areas. When we compare our global framework with an alternative where the individual zones are aggregated into a single optimizing fishery we find that competition will increase the global harvest and consequently reduced the resource price.
Keywords: No keywords provided
JEL Codes: G10; G13; G31; Q20; Q22
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| local biomass shocks (Q33) | optimal harvest of a fishery (Q22) |
| global biomass shocks (Q43) | optimal harvest of a fishery (Q22) |
| global biomass shocks (Q43) | correlation in biomass changes across zones (Q57) |
| competition among fisheries (Q22) | global harvest (Q10) |
| competition among fisheries (Q22) | resource prices (Q31) |
| expected harvest of others (Q19) | optimal harvest of a fishery (Q22) |
| global demand shocks (F69) | harvesting decisions of individual fisheries (Q22) |
| harvesting decisions of competing zones (P32) | global price (P22) |