Optimal control theory has been extensively used to determine the optimal harvesting policy for renewable resources such as fish stocks. In such optimisations, it is common to maximise the discounted utility of harvesting over time, employing a constant time discount rate. However, evidence from human and animal behaviour suggests that we have evolved to employ discount rates which fall over time, often referred to as “hyperbolic discounting”. This increases the weight on benefits in the distant future, which may appear to provide greater protection of resources for future generations, but also creates challenges of time-inconsistent plans. This paper examines harvesting plans when the discount rate declines over time. With a declining discount rate, the planner reduces stock levels in the early stages (when the discount rate is high) and intends to compensate by allowing the stock level to recover later (when the discount rate will be lower). Such a plan may be feasible and optimal, provided that the planner remains committed throughout. However, in practice there is a danger that such plans will be re-optimized and adjusted in the future. It is shown that repeatedly restarting the optimization can drive the stock level down to the point where the optimal policy is to harvest the stock to extinction. In short, a key contribution of this paper is to identify the surprising severity of the consequences flowing from incorporating a rather trivial, and widely prevalent, “non-rational” aspect of human behaviour into renewable resource management models. These ideas are related to the collapse of the Peruvian anchovy fishery in the 1970’s.<\/p>\n
Duncan, S., Hepburn, C., and Papachristodoulou, A. January 2011. Optimal harvesting of fish stocks under a time-varying discount rate<\/em>. Journal of Theoretical Biology, v.269, pp.166-173.<\/p>\n\n","protected":false},"excerpt":{"rendered":"\n Abstract Optimal control theory has been extensively used to determine the optimal harvesting policy for renewable resources such as fish…<\/p>\n\n","protected":false},"author":43,"featured_media":0,"template":"","tags":[866,863,865,864,867,862],"publication-type":[436],"topic_area":[4698,4709],"class_list":["post-3141","publication","type-publication","status-publish","hentry","tag-behavioral-economics","tag-bio-economics","tag-dynamical-systems","tag-optimal-control","tag-peru","tag-resource-management","publication-type-research-articles","topic_area-behavioural-responses","topic_area-critical-minerals-and-resources"],"acf":{"downloads":{"ref_value":"field_52f16cc1a80f2","value":false,"type":"repeater","post_type":""},"profile_link":{"ref_value":"field_52f164b5189e9","value":["cameron-hepburn"],"type":"relationship","post_type":"profile"},"article_link":{"ref_value":"field_52eee3c7f0586","value":"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0022519310005308","type":false,"post_type":""},"article_link_title":{"ref_value":"field_5322399d89d42","value":"Journal of Theoretical Biology.Volume 269, Issue 1, 21 January 2011, Pages 166\u2013173","type":false,"post_type":""},"spotlight":{"ref_value":"field_52f80896506d3","value":"","type":false,"post_type":""},"exclude_from_sync":{"ref_value":"field_560538b0e7350","value":"0","type":false,"post_type":""},"rss_newsletter":{"ref_value":"field_54f5c2c1544d8","value":"","type":false,"post_type":""}},"yoast_head":"\n