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Making informed investment decisions in an uncertain world : a short demonstration, Volume 1
Author:Bonzanigo, Laura; Kalra, Nidhi; Country:World;
Date Stored:2014/02/03Document Date:2014/02/01
Document Type:Policy Research Working PaperSubTopics:Energy Production and Transportation; Non Bank Financial Institutions; Climate Change Economics; Climate Change Mitigation and Green House Gases; Debt Markets
Language:EnglishMajor Sector:Energy and mining; Transportation
Rel. Proj ID:1W-Sdnce: Managing Uncertainty In Investmen -- -- P146701;Region:The World Region
Report Number:WPS6765Sub Sectors:Urban Transport; Other Renewable Energy
Collection Title:Policy Research working paper ; no. WPS 6765Volume No:1

Summary: 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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