[[Reference class forecasting]] was developed to reduceincrease forecastforecasting erroraccuracy andby increaseframing forecastthe accuracyforecasting problem so as to take into account available distributional information.<ref>[http://www.sbs.ox.ac.uk/centres/bt/Documents/Curbing%20Optimism%20Bias%20and%20Strategic%20Misrepresentation.pdf Flyvbjerg, B., 2008, "Curbing Optimism Bias and Strategic Misrepresentation in Planning: Reference Class Forecasting in Practice." European Planning Studies, vol. 16, no. 1, January 2008, pp. 3-21.]</ref> Daniel Kahneman, winner of the Nobel Prize in economics, calls the use of reference class forecasting "the single most important piece of advice regarding how to increase accuracy in forecasting.”<ref>Daniel Kahneman, 2011, Thinking, Fast and Slow (New York: Farrar, Straus and Giroux), p. 251</ref>
