New Paradoxes of Risky Decision Making that Refute Prospect Theories Michael H. Birnbaum Fullerton, California, USA.

Slides:



Advertisements
Similar presentations
New Paradoxes of Risky Decision Making that Refute Prospect Theories Michael H. Birnbaum Fullerton, California, USA.
Advertisements

Among those who cycle most have no regrets Michael H. Birnbaum Decision Research Center, Fullerton.
Science of JDM as an Efficient Game of Mastermind Michael H. Birnbaum California State University, Fullerton Bonn, July 26, 2013.
This Pump Sucks: Testing Transitivity with Individual Data Michael H. Birnbaum and Jeffrey P. Bahra California State University, Fullerton.
1 Upper Cumulative Independence Michael H. Birnbaum California State University, Fullerton.
Components of Source Credibility Michael H. Birnbaum Fullerton, California, USA.
1 Lower Distribution Independence Michael H. Birnbaum California State University, Fullerton.
True and Error Models of Response Variation in Judgment and Decision Tasks Michael H. Birnbaum.
Evaluating Non-EU Models Michael H. Birnbaum Fullerton, California, USA.
Who are these People Who Violate Stochastic Dominance, Anyway? What, if anything, are they thinking? Michael H. Birnbaum California State University, Fullerton.
Random variable Distribution. 200 trials where I flipped the coin 50 times and counted heads no_of_heads in a trial.
Decision making and economics. Economic theories Economic theories provide normative standards Expected value Expected utility Specialized branches like.
Testing Lexicographic Semi- Order Models: Generalizing the Priority Heuristic Michael H. Birnbaum California State University, Fullerton.
Testing Heuristic Models of Risky Decision Making Michael H. Birnbaum California State University, Fullerton.
1 A Brief History of Descriptive Theories of Decision Making Kiel, June 9, 2005 Michael H. Birnbaum California State University, Fullerton.
Some New Approaches to Old Problems: Behavioral Models of Preference Michael H. Birnbaum California State University, Fullerton.
1 Distribution Independence Michael H. Birnbaum California State University, Fullerton.
1 Upper Tail Independence Michael H. Birnbaum California State University, Fullerton.
Evaluating Hypotheses Chapter 9. Descriptive vs. Inferential Statistics n Descriptive l quantitative descriptions of characteristics.
Testing Models of Stochastic Dominance Violations Michael H. Birnbaum Decision Research Center California State University, Fullerton.
1 Upper Distribution Independence Michael H. Birnbaum California State University, Fullerton.
Ten “New Paradoxes” Refute Cumulative Prospect Theory of Risky Decision Making Michael H. Birnbaum Decision Research Center California State University,
Violations of Stochastic Dominance Michael H. Birnbaum California State University, Fullerton.
Testing Critical Properties of Models of Risky Decision Making Michael H. Birnbaum Fullerton, California, USA Sept. 13, 2007 Luxembourg.
Ten “New Paradoxes” Refute Cumulative Prospect Theory of Risky Decision Making Michael H. Birnbaum Decision Research Center California State University,
1 The Case Against Prospect Theories of Risky Decision Making Michael H. Birnbaum California State University, Fullerton.
Testing Transitivity (and other Properties) Using a True and Error Model Michael H. Birnbaum.
Web-Based Program of Research on Risky Decision Making Michael H. Birnbaum California State University, Fullerton.
Web-Based Program of Research on Risky Decision Making Michael H. Birnbaum California State University, Fullerton.
1 A Brief History of Descriptive Theories of Decision Making: Lecture 2: SWU and PT Kiel, June 10, 2005 Michael H. Birnbaum California State University,
1 Gain-Loss Separability and Reflection In memory of Ward Edwards Michael H. Birnbaum California State University, Fullerton.
I’m not overweight It just needs redistribution Michael H. Birnbaum California State University, Fullerton.
1 Ten “New Paradoxes” of Risky Decision Making Michael H. Birnbaum Decision Research Center California State University, Fullerton.
1 Gain-Loss Separability Michael H. Birnbaum California State University, Fullerton.
Is there Some Format in Which CPT Violations are Attenuated? Michael H. Birnbaum Decision Research Center California State University, Fullerton.
1 Lower Cumulative Independence Michael H. Birnbaum California State University, Fullerton.
Stochastic Dominance Michael H. Birnbaum Decision Research Center California State University, Fullerton.
Web-Based Program of Research on Risky Decision Making Michael H. Birnbaum California State University, Fullerton.
Testing Transitivity with Individual Data Michael H. Birnbaum and Jeffrey P. Bahra California State University, Fullerton.
1 Restricted Branch Independence Michael H. Birnbaum California State University, Fullerton.
Review for Exam 2 Some important themes from Chapters 6-9 Chap. 6. Significance Tests Chap. 7: Comparing Two Groups Chap. 8: Contingency Tables (Categorical.
Descriptive Statistics
Chapter 9 Title and Outline 1 9 Tests of Hypotheses for a Single Sample 9-1 Hypothesis Testing Statistical Hypotheses Tests of Statistical.
Presidential Address: A Program of Web-Based Research on Decision Making Michael H. Birnbaum SCiP, St. Louis, MO November 18, 2010.
Hypothesis Testing.
Chapter 5 Sampling and Statistics Math 6203 Fall 2009 Instructor: Ayona Chatterjee.
Behavior in the loss domain : an experiment using the probability trade-off consistency condition Olivier L’Haridon GRID, ESTP-ENSAM.
Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 17 Inferential Statistics.
Hypothesis Testing Quantitative Methods in HPELS 440:210.
Hypothesis Testing: One Sample Cases. Outline: – The logic of hypothesis testing – The Five-Step Model – Hypothesis testing for single sample means (z.
Stochastic choice under risk Pavlo Blavatskyy June 24, 2006.
A Stochastic Expected Utility Theory Pavlo R. Blavatskyy June 2007.
Ellsberg’s paradoxes: Problems for rank- dependent utility explanations Cherng-Horng Lan & Nigel Harvey Department of Psychology University College London.
Testing Transitivity with a True and Error Model Michael H. Birnbaum California State University, Fullerton.
Axiomatic Theory of Probabilistic Decision Making under Risk Pavlo R. Blavatskyy University of Zurich April 21st, 2007.
Chapter 10 The t Test for Two Independent Samples
Allais Paradox, Ellsberg Paradox, and the Common Consequence Principle Then: Introduction to Prospect Theory Psychology 466: Judgment & Decision Making.
Can a Dominatrix Make My Pump Work? Michael H. Birnbaum CSUF Decision Research Center.
Lec. 19 – Hypothesis Testing: The Null and Types of Error.
Logic of Hypothesis Testing
Introduction to Hypothesis Test – Part 2
Chapter 9: Inferences Involving One Population
Mohan Pandey 56th Edwards Bayesian Research Conference March 1-3, 2018
9 Tests of Hypotheses for a Single Sample CHAPTER OUTLINE
Behavioral Finance Economics 437.
Introduction to Hypothesis Testing
Chapter Nine Part 1 (Sections 9.1 & 9.2) Hypothesis Testing
Hypothesis Testing.
Introduction to Hypothesis Testing
New Paradoxes of Risky Decision Making that Refute Prospect Theories
Presentation transcript:

New Paradoxes of Risky Decision Making that Refute Prospect Theories Michael H. Birnbaum Fullerton, California, USA

Outline I will review tests between Cumulative Prospect Theory (CPT) and Transfer of Attention eXchange (TAX) model. Emphasis will be on critical properties that test between these two non- nested theories.

Cumulative Prospect Theory/ Rank-Dependent Utility (RDU)

“Prior” TAX Model Assumptions:

TAX Parameters For 0 < x < $150 u(x) = x Gives a decent approximation. Risk aversion produced by  

TAX CE with delta = 0

TAX: Effect of Delta

TAX Model

TAX and CPT nearly identical for binary (two-branch) gambles CE (x, p; y) is an inverse-S function of p according to both TAX and CPT, given their typical parameters. Therefore, there is no point trying to distinguish these models with binary gambles.

Non-nested Models

CPT and TAX nearly identical inside the prob. simplex

Testing CPT Coalescing Stochastic Dominance Lower Cum. Independence Upper Cumulative Independence Upper Tail Independence Gain-Loss Separability TAX:Violations of:

Testing TAX Model 4-Distribution Independence (RS’) 3-Lower Distribution Independence 3-2 Lower Distribution Independence 3-Upper Distribution Independence (RS’) Res. Branch Indep (RS’) CPT: Violations of:

Stochastic Dominance A test between CPT and TAX: G = (x, p; y, q; z) vs. F = (x, p – s; y’, s; z) Note that this recipe uses 4 distinct consequences: x > y’ > y > z > 0; outside the probability simplex defined on three consequences. CPT  choose G, TAX  choose F Test if violations due to “error.”

Violations of Stochastic Dominance 122 Undergrads: 59% two violations (BB) 28% Pref Reversals (AB or BA) Estimates: e = 0.19; p = Experts: 35% repeat violations 31% Reversals Estimates: e = 0.20; p = 0.50 Chi-Squared test reject H0: p violations < 0.4

Pie Charts

Aligned Table: Coalesced

Summary: 23 Studies of SD, 8653 participants Large effects of splitting vs. coalescing of branches Small effects of education, gender, study of decision science Very small effects of probability format, request to justify choice. Miniscule effects of event framing (framed vs unframed)

Lower Cumulative Independence R: 39% S: 61%.90 to win $3.90 to win $3.05 to win $12.05 to win $48.05 to win $96.05 to win $52 R'': 69% S'': 31%.95 to win $12.90 to win $12.05 to win $96.10 to win $52

Upper Cumulative Independence R': 72% S': 28%.10 to win $10.10 to win $40.10 to win $98.10 to win $44.80 to win $ to win $110 R''': 34% S''': 66%.10 to win $10.20 to win $40.90 to win $98.80 to win $98

Summary: UCI & LCI 22 studies with 33 Variations of the Choices, 6543 Participants, & a variety of display formats and procedures. Significant Violations found in all studies.

Restricted Branch Indep. S ’:.1 to win $40.1 to win $44.8 to win $100 S:.8 to win $2.1 to win $40.1 to win $44 R ’ :.1 to win $10.1 to win $98.8 to win $100 R:.8 to win $2.1 to win $10.1 to win $98

3-Upper Distribution Ind. S ’ :.10 to win $40.10 to win $44.80 to win $100 S2 ’ :.45 to win $40.45 to win $44.10 to win $100 R ’ :.10 to win $4.10 to win $96.80 to win $100 R2 ’ :.45 to win $4.45 to win $96.10 to win $100

3-Lower Distribution Ind. S ’ :.80 to win $2.10 to win $40.10 to win $44 S2 ’ :.10 to win $2.45 to win $40.45 to win $44 R ’ :.80 to win $2.10 to win $4.10 to win $96 R2 ’ :. 10 to win $2.45 to win $4.45 to win $96

Gain-Loss Separability

Notation

Wu and Markle Result

Birnbaum & Bahra--% F

Allais Paradox Dissection Restricted Branch Independence CoalescingSatisfiedViolated SatisfiedEU, PT*,CPT*CPT ViolatedPTTAX

Summary: Prospect Theories not Descriptive Violations of Coalescing Violations of Stochastic Dominance Violations of Gain-Loss Separability Dissection of Allais Paradoxes: viols of coalescing and restricted branch independence; RBI violations opposite of Allais paradox.

Summary-2 PropertyCPTRAMTAX LCINo ViolsViols UCINo ViolsViols UTINo ViolsR ’ S1Viols LDIRS2 ViolsNo Viols 3-2 LDIRS2 ViolsNo Viols

Summary-3 PropertyCPTRAMTAX 4-DI RS ’ Viols No Viols SR ’ Viols UDIS ’ R2 ’ Viols No ViolsR ’ S2 ’ Viols RBI RS ’ ViolsSR ’ Viols

Results: CPT makes wrong predictions for all 12 tests Can CPT be saved by using different formats for presentation? More than a dozen formats have been tested. Violations of coalescing, stochastic dominance, lower and upper cumulative independence replicated with 14 different formats and thousands of participants.

Implications Results indicate that neither PT nor CPT are descriptive of risky decision making. Editing rules of combination, cancellation, & dominance detection refuted. TAX correctly predicts the violations of CPT. CPT implies violations of TAX that either fail or show the opposite pattern from predicted by CPT.