Inevitable Disappointment in Projects Selected on the Basis of Forecasts
- Authors
- Min Chen (University of Texas at Austin) | James Dyer (University of Texas at Austin)
- DOI
- https://doi.org/10.2118/107710-PA
- Document ID
- SPE-107710-PA
- Publisher
- Society of Petroleum Engineers
- Source
- SPE Journal
- Volume
- 14
- Issue
- 02
- Publication Date
- June 2009
- Document Type
- Journal Paper
- Pages
- 216 - 221
- Language
- English
- ISSN
- 1086-055X
- Copyright
- 2009. Society of Petroleum Engineers
- Disciplines
- 7.10 Capital Budgeting and Project Selection, 4.3.4 Scale
- Downloads
- 1 in the last 30 days
- 439 since 2007
- Show more detail
- View rights & permissions
SPE Member Price: | USD 12.00 |
SPE Non-Member Price: | USD 35.00 |
Summary
Investors often select projects whose estimated performance measures meet or exceed a hurdle value. At the time of decision making, the true performance of a project is unknown but uncertain forecasts are available. Decision makers (DMs) often ignore the prediction errors when they use these forecasts to choose projects. To the disappointment of the DMs, many selected projects result in smaller actual yields than those that were forecasted.
Some have attributed the cause of this to the optimistic bias of the predictions. This paper shows that this disappointment can occur even if the prediction is unbiased. In this case, a bias can be introduced by the selection process that will allow more unattractive (overestimated) projects to be accepted than attractive (underestimated) ones. Although a similar phenomenon has been noted in statistics and finance research, it is not well understood in the context of project selection by DMs.
We present a solution method based on Bayesian updating and demonstrate its effectiveness in eliminating the disappointment in project selection with realistic data from oil exploration and production projects.
File Size | 1 MB | Number of Pages | 6 |
References
Brown, K.C. 1974. A note on theapparent bias of net revenue estimates for capital investment projects.The Journal of Finance 29 (4):1215-1216.doi:10.2307/2978396.
Brown, K.C. 1978. The rate ofreturn of selected investment projects. The Journal of Finance33 (4): 1250-1253. doi:10.2307/2326956.
Capen, E.C., Clapp, R.V., and Campbell, W.M. 1971. Competitive Bidding in High-RiskSituations. J. Pet Tech 23 (6):641-653. SPE-2993-PA.doi: 10.2118/2993-PA.
Harrison, R.J. and March, J.G. 1984. Decision making and postdecisionsurprises. Administrative Science Quarterly 29 (1):26-42. doi:10.2307/2393078.
Horner, D. 1980. On the theory of inevitable disappointment. TheoreticalNote No. 21 (unpublished).
Kagel, J.H. and Levin, D. 2002. Common Value Auctions and the Winner'sCurse. Princeton, New Jersey: Princeton University Press.
Miller, E.M. 1978. Uncertaintyinduced bias in capital budgeting. Financial Management7 (3): 12-18. doi:10.2307/3665005.
Miller, E.M. 1987. Thecompetitive market assumption and capital budgeting criteria. FinancialManagement 16 (4): 22-28. doi:10.2307/3666105.
Miller, E.M. 2000. Capital budgeting errors seldom cancel. FinancialPractice & Education 10 (2): 128-135.
Pinches, G.E. 1982. Myopia,capital budgeting and decision making. Financial Management11 (3): 6-19. doi:10.2307/3664993.
Pruitt, S.W. and Gitman, L.J. 1987. Capital budgeting forecast biases:Evidence from the Fortune 500. Financial Management 16(1): 46-51. doi:10.2307/3665549.
Schuyler, J. and Nieman, T. 2007. Optimizer's Curse: Removing theEffect of This Bias in Portfolio Planning. SPE Proj Fac & Const3 (1): 1-9. SPE-107852-PA. doi: 10.2118/107852-PA.
Smidt, S. 1979. A Bayesiananalysis of projects selection and of post audit evaluations. TheJournal of Finance 34 (3): 675-688. doi:10.2307/2327434.
Smith, J.E. and Winkler, R.L. 2006. The optimizer's curse:Skepticism and post-decision surprise in decision analysis. ManagementScience 52 (3): 311-322. doi: 10.1287/mnsc.1050.0451.
Statman, M. and Tyebjee, T.T. 1985. Optimistic capital budgetingforecasts: An experiment. Financial Management 14 (3):27-33. doi:10.2307/3665056.