Scenario Analysis with Recursive Utility: Dynamic Consumption Plans for Charitable Endowments

Stephen Satchell and Susan Thorp ()
Additional contact information
Stephen Satchell: University of Cambridge

No 209, Research Paper Series from Quantitative Finance Research Centre, University of Technology, Sydney

Abstract: We determine optimal consumption paths under a series of returns scenarios for charitable endowments with distinct tastes over investment risk and inter-temporal substitution. Charities typically prefer smooth consumption paths but are investment-risk tolerant. Using a recursive, Kreps-Porteus utility function, we model the optimal disbursement from an infinitely-lived charitable trust, then, allowing a general form for the returns density, we apply stochastic dominance relations to estimate income/substitution effects whereby a change in future returns influences the current consumption rate. The elasticity of intertemporal substitution rather than risk aversion is key: optimal consumption rises or falls as the elasticity diverges from one.

Keywords: recursive utility; stochastic dominance; inter-temporal choice (search for similar items in EconPapers)
JEL-codes: G00 D81 D91 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dge and nep-upt
Date: 2007-12-01
View list of references

Downloads: (external link)
http://www.business.uts.edu.au/qfrc/research/research_papers/rp209.pdf (application/pdf)

Related works:
Working Paper: SCENARIO ANALYSIS WITH RECURSIVE UTILITY: DYNAMIC CONSUMPTION PLANS FOR CHARITABLE ENDOWMENTS (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:uts:rpaper:209

Access Statistics for this paper

More papers in Research Paper Series from Quantitative Finance Research Centre, University of Technology, Sydney
Address: PO Box 123, Broadway, NSW 2007, Australia
Contact information at EDIRC.
Series data maintained by Duncan Ford ().