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Bibliothèque Making Informed Investment Decisions in an Uncertain World : A Short Demonstration

Making Informed Investment Decisions in an Uncertain World : A Short Demonstration

Making Informed Investment Decisions in an Uncertain World : A Short Demonstration

Resource information

Date of publication
Mars 2014
Resource Language
ISBN / Resource ID
oai:openknowledge.worldbank.org:10986/17310

Governments invest billions of dollars
annually in long-term projects. Yet deep uncertainties pose
formidable challenges to making near-term decisions that
make long-term sense. Methods that identify robust decisions
have been recommended for investment lending but are not
widely used. This paper seeks to help bridge this gap and,
with a demonstration, motivate and equip analysts better to
manage uncertainty in investment decisions. The paper first
reviews the economic analysis of ten World Bank projects. It
finds that analysts seek to manage uncertainty but use
traditional approaches that do not evaluate options over the
full range of possible futures. Second, the paper applies a
different approach, Robust Decision Making, to the economic
analysis of a 2006 World Bank project, the Electricity
Generation Rehabilitation and Restructuring Project, which
sought to improve Turkey's energy security. The
analysis shows that Robust Decision Making can help decision
makers answer specific and useful questions: How do options
perform across a wide range of potential future conditions?
Under what specific conditions does the leading option fail
to meet decision makers' goals? Are those conditions
sufficiently likely that decision makers should choose a
different option? Such knowledge informs rather than
replaces decision makers' deliberations. It can help
them systematically, rigorously, and transparently compare
their options and select one that is robust. Moreover, the
paper demonstrates that analysts can use the same data and
models for Robust Decision Making as are typically used in
economic analyses. Finally, the paper discusses the
challenges in applying such methods and how they can be overcome.

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Authors and Publishers

Author(s), editor(s), contributor(s)

Bonzanigo, Laura
Kalra, Nidhi

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