Assessing Uncertainty from Point Forecasts

References

• Alpert M, Raiffa H (1982) A progress report on the training of probability assessors. Kahneman D, Slovic P, Tversky A, eds. Judgment Under Uncertainty: Heuristics and Biases (Cambridge University Press, Cambridge, UK), 294–305.Crossref, Google Scholar
• Armstrong JS (2001) Principles of Forecasting: A Handbook for Researchers and Practitioners (Springer Science and Business Media, New York).Crossref, Google Scholar
• Ashton RH (1986) Combining the judgments of experts: How many and which ones? Organ. Behav. Human Decision Processes 38(3):405–414.Crossref, Google Scholar
• Bansal S, Palley AB (2017) Is it better to elicit quantile or probability judgments? A comparison of direct and calibrated procedures for estimating a continuous distribution. Kelley School of Business Research Paper No. 17-44, https://ssrn.com/abstract=2981840.Crossref, Google Scholar
• Bansal S, Gutierrez GJ, Keiser JR (2017) Using experts’ judgments to quantify risks: Theory and application to agribusiness. Oper. Res. 65(5):1115–1130.Link, Google Scholar
• Bernardo JM, Smith AF (1994) Bayesian Theory (John Wiley & Sons, New York).Crossref, Google Scholar
• Bimpikis K, Markakis MG (2016) Inventory pooling under heavy-tailed demand. Management Sci. 62(6):1800–1813.Link, Google Scholar
• Bolger F, Rowe G (2015) The aggregation of expert judgment: Do good things come to those who weight? Risk Anal. 35(1):5–11.Crossref, Google Scholar
• Brown RV, Lindley DV (1986) Plural analysis: Multiple approaches to quantitative research. Theory and Decision 20(2):133–154.Crossref, Google Scholar
• Bunn DW (1985) Statistical efficiency in the linear combination of forecasts. Internat. J. Forecasting 1(2):151–163.Crossref, Google Scholar
• Chevalier J, Goolsbee A (2003) Measuring prices and price competition online: Amazon.com and barnesandnoble.com. Quant. Marketing Econom. 1(2):203–222.Crossref, Google Scholar
• Chhibber S, Apostolakis G (1993) Some approximations useful to the use of dependent information sources. Reliability Engrg. System Safety 42(1):67–86.Crossref, Google Scholar
• Clemen RT (1989) Combining forecasts: A review and annotated bibliography. Internat. J. Forecasting 5(4):559–583.Crossref, Google Scholar
• Clemen RT, Winkler RL (1985) Limits for the precision and value of information from dependent sources. Oper. Res. 33(2):427–442.Link, Google Scholar
• Clemen RT, Fischer GW, Winkler RL (2000) Assessing dependence: Some experimental results. Management Sci. 46(8):1100–1115.Link, Google Scholar
• Fisher M, Raman A (1996) Reducing the cost of demand uncertainty through accurate response to early sales. Oper. Res. 44(1):87–99.Link, Google Scholar
• Fisher M, Raman A (2010) The New Science of Retailing: How Analytics Are Transforming the Supply Chain and Improving Performance (Harvard Business Press, Boston).Google Scholar
• Fujikoshi Y, Mukaihata S (1993) Approximations for the quantiles of Student’s t and f distributions and their error bounds. Hiroshima Math. J. 23(3):557–564.Crossref, Google Scholar
• Gaba A, Tsetlin I, Winkler RL (2017) Combining interval forecasts. Decision Anal. 14(1):1–20.Link, Google Scholar
• Gaffeo E, Scorcu AE, Vici L (2008) Demand distribution dynamics in creative industries: The market for books in Italy. Inform. Econom. Policy 20(3):257–268.Crossref, Google Scholar
• Garthwaite PH, Kadane JB, O’Hagan A (2005) Statistical methods for eliciting probability distributions. J. Amer. Statist. Assoc. 100(470):680–701.Crossref, Google Scholar
• Gaur V, Kesavan S, Raman A, Fisher M (2007) Estimating demand uncertainty using judgmental forecasts. Manufacturing Service Oper. Management 9(4):480–491.Link, Google Scholar
• Geisser S (1965) A Bayes approach for combining correlated estimates. J. Amer. Statist. Assoc. 60(310):602–607.Crossref, Google Scholar
• Gneiting T, Balabdaoui F, Raftery AE (2007) Probabilistic forecasts, calibration and sharpness. J. Roy. Statist. Soc. Ser. B Statist. Methodol. 69(2):243–268.Crossref, Google Scholar
• Gokhale DV, Press SJ (1982) Assessment of a prior distribution for the correlation coefficient in a bivariate normal distribution. J. Roy. Statist. Soc. Ser. A General 145(2):237–249.Crossref, Google Scholar
• Hammond JH, Raman A (1994) Sport Obermeyer, Ltd. (Harvard Business School, Boston), HBS Case 695-022.Google Scholar
• Hoff PD (2009) A First Course in Bayesian Statistical Methods (Springer Science and Business Media, New York).Crossref, Google Scholar
• Johnson NL, Kotz S, Balakrishnan N (2002) Continuous Multivariate Distributions, Volume 1, Models and Applications (John Wiley & Sons, New York).Google Scholar
• Jose VRR, Grushka-Cockayne Y, LLichtendahl KC Jr (2013) Trimmed opinion pools and the crowd’s calibration problem. Management Sci. 60(2):463–475.Link, Google Scholar
• Keefer DL, Bodily SE (1983) Three-point approximations for continuous random variables. Management Sci. 29(5):595–609.Link, Google Scholar
• Kremer M, Siemsen E, Thomas DJ (2015) The sum and its parts: Judgmental hierarchical forecasting. Management Sci. 62(9):2745–2764.Link, Google Scholar
• Kunda Z, Nisbett RE (1986) The psychometrics of everyday life. Cognitive Psych. 18(2):195–224.Crossref, Google Scholar
• Lichtendahl KC Jr, Grushka-Cockayne Y, Pfeifer PE (2013a) The wisdom of competitive crowds. Oper. Res. 61(6):1383–1398.Link, Google Scholar
• Lichtendahl KC Jr, Grushka-Cockayne Y, Winkler RL (2013b) Is it better to average probabilities or quantiles? Management Sci. 59(7):1594–1611.Link, Google Scholar
• Lichtenstein S, Fischhoff B, Phillips LD (1982) Calibration of probabilities: The state of the art. Kahneman D, Slovic P, Tversky A, eds. Judgment Under Uncertainty: Heuristics and Biases (Cambridge University Press, Cambridge, UK), 306–334.Crossref, Google Scholar
• Lindley DV (1986) The reconciliation of decision analyses. Oper. Res. 34(2):289–295.Link, Google Scholar
• Meyer MA, Booker JM (2001) Eliciting and Analyzing Expert Judgment: A Practical Guide (Society for Industrial and Applied Mathematics, Philadelphia).Crossref, Google Scholar
• Moder JJ, Phillips CR, Davis EW (1995) Project Management With CPM, PERT and Precedence Diagramming (Blitz Publishing Company, Middleton, WI).Google Scholar
• Palley AB, Soll JB (2016) Eliciting and aggregating forecast when information is shared. Working paper, Duke University, Durham, NC.Google Scholar
• Poirier DJ (1995) Intermediate Statistics and Econometrics: A Comparative Approach (MIT Press, Cambridge, MA).Google Scholar
• Raju JS, Roy A (2000) Market information and firm performance. Management Sci. 46(8):1075–1084.Link, Google Scholar
• Rao CR (1973) Linear Statistical Inference and its Applications (John Wiley & Sons, New York).Crossref, Google Scholar
• Ren Y, Croson R (2013) Overconfidence in newsvendor orders: An experimental study. Management Sci. 59(11):2502–2517.Link, Google Scholar
• Ren Y, Croson D, Croson R (2017) The overconfident newsvendor. J. Oper. Res. Soc. 68(5):496–506.Crossref, Google Scholar
• Rudi N, Drake D (2014) Observation bias: The impact of demand censoring on newsvendor level and adjustment behavior. Management Sci. 60(5):1334–1345.Link, Google Scholar
• Schmittlein DC, Kim J, Morrison DG (1990) Combining forecasts: Operational adjustments to theoretically optimal rules. Management Sci. 36(9):1044–1056.Link, Google Scholar
• Schweitzer ME, Cachon GP (2000) Decision bias in the newsvendor problem with a known demand distribution: Experimental evidence. Management Sci. 46(3):404–420.Link, Google Scholar
• Seifert M, Siemsen E, Hadida AL, Eisingerich AB (2015) Effective judgmental forecasting in the context of fashion products. J. Oper. Management 36:33–45.Crossref, Google Scholar
• Vives X (1984) Duopoly information equilibrium: Cournot and Bertrand. J. Econom. Theory 34(1):71–94.Crossref, Google Scholar
• Wallsten TS, Shlomi Y, Nataf C, Tomlinson T (2016) Efficiently encoding and modeling subjective probability distributions for quantitative variables. Decision 3(3):169–189.Crossref, Google Scholar
• Winkler RL (1981) Combining probability distributions from dependent information sources. Management Sci. 27(4):479–488.Link, Google Scholar
• Winkler RL, Clemen RT (1992) Sensitivity of weights in combining forecasts. Oper. Res. 40(3):609–614.Link, Google Scholar
• Winkler RL, Clemen RT (2004) Multiple experts vs. multiple methods: Combining correlation assessments. Decision Anal. 1(3):167–176.Link, Google Scholar