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Making Descriptive Use of Prospect Theory to Improve the Prescriptive Use of Expected Utility Peter P. Wakker (& Bleichrodt & Pinto); Oct. 3, 2003 2003.

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Presentation on theme: "Making Descriptive Use of Prospect Theory to Improve the Prescriptive Use of Expected Utility Peter P. Wakker (& Bleichrodt & Pinto); Oct. 3, 2003 2003."— Presentation transcript:

1 Making Descriptive Use of Prospect Theory to Improve the Prescriptive Use of Expected Utility Peter P. Wakker (& Bleichrodt & Pinto); Oct. 3, 2003 2003 decision analysis publication award. This powerpoint file will be on my homepage on coming Monday. p? 1p1p  Perf. Health artificial speech ~ EU = U = p Analysis is based on EU!?!? Standard gamble question: p  1 + (1–p)  0 = p Don’t forget to make this invisible. Already appeared two years ago. This conference already saw two follow-up studies. Hence, I speak about it for only 10 minutes. Rest of my time I use for a general discussion, about why I think that people have difficulties in using our corrections. I think, frankly, that people rather “look the other way” than face the biases.

2 2 Common justification: EU is normative (von Neumann-Morgenstern) We agree that EU is normative. But not that this would justify SG-analysis. SG measurement is descriptive. EU is not descriptive. A better descriptive theory: Prospect theory!

3 3 EU: U(x) = p. PT: U(x) = p p + (1  p) w + ( ) ww We: is wrong !!

4 p w+w+ 1 1 0 1/3 Figure. The common weighting fuction w + (1/3) = 1/3; 4 = 2.25 w  is similar;

5 Standard Gamble Utilities, Corrected through Prospect Theory, for p =.00,...,.99. 00. 01. 02. 03. 04. 05. 06. 07. 08. 09.0.00.0000.0250.0380.0480.0570.0640.0720.0780.0850.091.1.10.0970.1020.1080.1130.1180.1230.1280.1330.1380.143.2.20.1480.1520.1570.1620.1660.1710.1760.1800.1850.189.3.30.1940.1990.2030.2080.2130.2170.2220.2270.2310.236.4.40.2410.2460.2510.2560.2610.2660.2710.2760.2810.286.5.50.2920.2970.3030.3080.3140.3200.3250.3310.3370.343.6.60.3500.3560.3630.3690.3760.3830.3900.3970.4050.412.7.70.4200.4280.4360.4450.4540.4630.4720.4810.4910.502.8.80.5120.5230.5350.5470.5600.5730.5870.6010.6170.633.9.90.6500.6690.6890.7100.7340.7600.7890.8220.8610.911 5 E.g., if p =.15 then U = 0.123

6 0 0.2 0.4 0.6 0.8 1 0 0.20.40.60.81 U p Corrected Standard Gamble Utility Curve 6

7 U SG  U CE ( at 1 st = CE(.10), …, at 5 th = CE(.90) ) 5 th 3d3d 1 st 2 nd 4 th *** * ** * *** 0.25 0.00  0.10 0.10 0.20  0.05 0.05 0.15 * Corrected (Prospect theory) U SG  U TO ( at 1 st = x 1, …, at 5 th = x 5 ) U CE  U TO ( at 1 st = x 1, …, 5 th = x 5 ) Classical (EU) 7

8 SG(EU) CE 1/3 SG(PT) SP TO Utility functions (for mean values). 0 1/6 2/6 3/6 4/6 5/6 1 7/6 t 0 = FF5,000 FF U 8 t 6 = FF26,068 Abdellaoui, Barrios, & Wakker (2003)

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