Individual and social discounting in a viscous population
Sozou, Peter D.. (2009) Individual and social discounting in a viscous population. Proceedings of the Royal Society B: Biological Sciences, Vol.276 (No.1669). pp. 2955-2962. ISSN 0962-8452Full text not available from this repository.
Official URL: http://dx.doi.org/10.1098/rspb.2009.0401
Social discounting in economics involves applying a diminishing weight to community-wide benefits or costs into the future. It impacts on public policy decisions involving future positive or negative effects, but there is no consensus on the correct basis for determining the social discount rate. This study presents an evolutionary biological framework for social discounting. How an organism should value future benefits to its local community is governed by the extent to which members of the community in the future are likely to be its kin. Trade-offs between immediate and delayed benefits to an individual or to its community are analysed for a modelled patch-structured iteroparous population with limited dispersal. It is shown that the social discount rate is generally lower than the individual (private) discount rate. The difference in the two rates is most pronounced, in ratio terms, when the dispersal level is low and the hazard rate for patch destruction is much smaller than the individual mortality rate. When decisions involve enforced collective action rather than individuals acting independently, social investment increases but the social discount rate remains the same.
|Item Type:||Journal Article|
|Subjects:||Q Science > QH Natural history > QH301 Biology|
|Divisions:||Faculty of Medicine > Warwick Medical School|
|Journal or Publication Title:||Proceedings of the Royal Society B: Biological Sciences|
|Publisher:||The Royal Society Publishing|
|Official Date:||22 August 2009|
|Number of Pages:||8|
|Page Range:||pp. 2955-2962|
|Access rights to Published version:||Restricted or Subscription Access|
|Funder:||London School of Economics|
Actions (login required)
Downloads per month over past year