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Neuroeconomics & Experimental Economics: What They Can Tell us about Human Risk & Decision Making

Neuroeconomics & Experimental Economics: What They Can Tell us about Human Risk & Decision Making. Kevin A. McCabe Professor of Economics, Law, and Neuroscience Director, Center for the Study of Neuroeconomics George Mason University kmccabe@gmu.edu www.neuroeconomics.net ( Center).

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Neuroeconomics & Experimental Economics: What They Can Tell us about Human Risk & Decision Making

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  1. Neuroeconomics & Experimental Economics: What They Can Tell us about Human Risk & Decision Making • Kevin A. McCabe • Professor of Economics, Law, and Neuroscience • Director, Center for the Study of Neuroeconomics • George Mason University • kmccabe@gmu.edu • www.neuroeconomics.net (Center)

  2. THE CENTER FOR THE STUDY OF NEUROECONOMICS AT GEORGE MASON UNIVERSITY Allegra 3T Scanner LAN Brain Imaging Virtual Worlds

  3. First Wave 1960 Siegel And Fouraker, Bargaining and Group Decision Making 1962 Smith, “An Exp. Study of Competitive Market Behavior” 1959 Sauermann and Selten, “Ein Oligopolexperiment.” • Santa Monica Seminar: The Design of Experiments in Decision Processes • sponsored by the Ford Foundation

  4. Inducing Individual Demand 1962 Smith, “An Exp. Study of Competitive Market Behavior” Buyer 1 Unit Value 1st $9 2nd $6 3rd $3 If you buy your first unit for $6 you earn $9 - $6 = $3. B1 B1 At a price of $4.50, how many units is Buyer 1 willing to purchase? B1

  5. Inducing Individual Supply 1962 Smith, “An Exp. Study of Competitive Market Behavior” Seller 1 Unit Cost 1st$1 2nd $4 3rd $7 B1 If you sell your first unit for $6 you earn $6 - $1 = $5. S1 At a price of $4.50, how many units is seller 1 willing to sell? S1 S1

  6. Smith, 1962 Aggregate Supply and Demand

  7. What is Missing? 1962 Smith, “An Exp. Study of Competitive Market Behavior” Every Institution Consists of Four Elements (1)A message space. • A set of message sending rules indicating • who gets to send what messages when. (3) A set of message processing rules indicating how messages update information (4) A set of production rules which translates messages into outcomes.

  8. The Double Auction 1962 Smith, “An Exp. Study of Competitive Market Behavior” (1)Message space: Bid, Ask, Buy, Sell. • Message sending rules: Buyers Bid & Buy; • Sellers Ask & Sell; Improvement Rule; • Starting and Stopping rules. (3) Message processing rules:Update book; Determine standing bid and ask. • (4) Production rules: Buy or Sell: results in • Buyer sending Seller cash and Seller • sending Buyer a unit.

  9. Double Auction in Practice 1962 Smith, “An Exp. Study of Competitive Market Behavior” ID BID ASK ID B1 7 B2 7.5 B1 7.75 B1 Accepts 8.5 S3 8.25 S2 8 S3

  10. Smith, 1962 First Data Point

  11. Smith, 1962 Testing Robustness: Comparative Statics

  12. “I am still recovering from the shock of the experi-mental results.” Written by Smith in 1981, “Experimental Economics at Purdue.” Smith, 1962

  13. Second Wave 1960 Siegel And Fouraker, Bargaining and Group Decision Making 1962 Smith, “An Exp. Study of Competitive Market Behavior” 1973 Plott @ Cal. Tech & 1975 Smith @ Arizona 1979 Kahneman and Tversky, “Prospect Theory” 1982 Smith, “Microeconomic Systems as an Experimental Science” 1976 Smith, “Induced Value Theory” 1959 Sauermann and Selten, “Ein Oligopolexperiment.” • Santa Monica Seminar: The Design of Experiments in Decision Processes • sponsored by the Ford Foundation

  14. 18 14 10 6 2 0 8 16 24 32 12 10 8 6 4 ID BID ASK ID 2 B1 7 B1 7.5 B3 7.75 B1 Accepts 8.5 S5 8.25 S1 8 S5 B1 0 0 4 8 12 16 Microeconomic System 1982 Smith, “Microeconomic Systems as an Experimental Science” Environment Outcomes (p,q) Institution: DA Governs Computes Messages

  15. Stock Market Bubbles

  16. Experimental Design 9 Traders Assigned to One of Three Classes Example: Class One: Cash = $2.25 Assets = 3 Class Two: Cash = $5.85 Assets = 2 Class Three: Cash = $9.45 Assets = 1 Dividend Distribution {0, 8, 28, 60}, p =1/4, Ed = 24 cents Fifteen Period Double Auction Everyone is a Trader (buy and sell) Random Dividend Draw After Each Period

  17. Typical Bubble

  18. Parallels to Natural World What happened here

  19. Third Wave 1960 Siegel And Fouraker, Bargaining and Group Decision Making 1962 Smith, “An Exp. Study of Competitive Market Behavior” 1973 Plott @ Cal. Tech & 1975 Smith @ Arizona 1979 Kahneman and Tversky, “Prospect Theory” 2002 Nobel Prize in Exp. Econ. 1998 Experimental Economics J. 1986 Economic Science Assoc. Founded 1982 Smith, “Microeconomic Systems as an Experimental Science” 1976 Smith, “Induced Value Theory” 1959 Sauermann and Selten, “Ein Oligopolexperiment.” • Santa Monica Seminar: The Design of Experiments in Decision Processes • sponsored by the Ford Foundation

  20. The Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel 2002 "for having integrated insights from psycho-logical research into economic science, …” Daniel Kahneman "Daniel Kahneman - Diploma". Nobelprize.org. 21 Jul 2010 http://nobelprize.org/nobel_prizes/economics/laureates/2002/kahneman-diploma.html "for having established laboratory experiments as a tool in empirical economic analysis, …” "Vernon L. Smith - Diploma". Nobelprize.org. 21 Jul 2010 http://nobelprize.org/nobel_prizes/economics/laureates/2002/smith-diploma.html

  21. A Microeconomic Systems Perspective Experimenter would like to improve performance. Performance Environment (E) Outcomes (Q) Institution (I) Governs Computes Behavior Messages bi: E X I  M i = 1 , …, n (M) Experimenter would like to predict behavior. Daniel Kahneman

  22. Smith’s Interest: Control For Preferences Q2 x2* = h2(p1, p2, I) u3 u2 u1 Q1 x1* = h1(p1, p2, I) 1976 Smith, “Induced Value Theory”, AER

  23. K & T’s Interest: Study Preferences Daniel Kahneman Floris Heukelom, “Kahneman and Tversky and the Origin of Behavioral Economics”, TI 2007-003/1 Tinbergen Institute Discussion Paper

  24. Effect of Increasing Variance On Expected Utility: Measures Risk Aversion Utility m1 p g U(m) 1-p m2 M1 EU(g) p EU(f) f 1-p M2 Money M1 m1 EV m2 M2

  25. Measuring Risk Preferences Risk Aversion and Incentive Effects Charles A. Holt and Susan K. Laury The American Economic ReviewVol. 92, No. 5 (Dec., 2002), pp. 1644-1655

  26. Decision Tasks EVA EVB 118.5 480 202 470 305.5 460 399 450 492.5 440 586 430 679.5 420 773 410 866.5 400 960

  27. Risk Neutral Prediction

  28. Making Risky Decisions for Others

  29. Data From The Experiment

  30. Decision Task for Judges’ Experiment EVA EVB 14.70 3.80 14.40 6.60 14.10 9.40 13.80 12.20 13.50 15.00 13.20 17.80 12.90 20.60 12.60 23.40 12.30 26.20 12.00 29.00

  31. Judges’ Experiment (in progress) Fraction Choosing Safe Option A

  32. But are preferences over risk independent of context? Joyce Berg, John Dickhaut, and Kevin McCabe, “Risk preference instability across institutions: A dilemma,” PNAS, 2005, 102(11), pp. 4209-4214.

  33. A Technology Time Line Computerized DA on Plato IBM/360 WWW LANs micro 1960 1980 MS-Dos VB BASIC JAVA Python 1960- 1980- Markets and Games. Economic Systems Design

  34. Resources z-Tree

  35. Resources http://econwillow.sourceforge.net/

  36. An Approx. Technology Time Line Computerized DA on Plato IBM/360 WWW LANs Micro computer fMRI 1960 1980 2000 MS-Dos VB BASIC JAVA Python 1960- 1980- 2000- Markets, Behavioral, and Games. ESD Neuroeconomics, Internet field experiments

  37. Neuroeconomics Environment Outcomes (q) Institution Governs Computes Sensors Homeostatic Condition Messages Neuronal Assemblies Governs Computes Effectors Neural Activity

  38. The Dopamine System MPFC NA

  39. Bubbles in the Scanner Terry Lohrenz; Kevin McCabe; Colin Camerer; P. Read Montague. “Neural signature of fictive learning signals in a sequential investment task,” Proceedings of the National Academy of Sciences, May 29th, 2007, 104(22), pp. 9493-9498. Early Edition (Open Access)

  40. Task Price History Amount in market Change in portfolio Portfolio Value

  41. Fictive Learning Signal The fictive learning signal looks at what could have been achieved if you had made your earlier choice with updated information. If prices go up how much gain would you have made if you were 100% in the market.

  42. Fictive Error Predicts Change in Investment

  43. Separation of Fictive and Temporal Difference Learning

  44. An Approx. Technology Time Line Computerized DA on Plato Z-Tree Web 2.0 Virtual Worlds IBM/360 WWW LANs fMRI micro 1960 1980 2000 2010 MS-Dos VB BASIC Human Genome Sequenced JAVA Python 1960- 1980- 2000- 2010- Markets, Behavioral, and Games. ESD Virtual Worlds, Web 2.0 Experiments, and Genetics Experiments Neuro-economics, Internet Field experiments

  45. TerraEcon in Second Life Second Life is 3D, Visualize immersive, Feels real user-created, Build once use often persistent, Start where you left off and, online. On your computer

  46. Importance of Collaboration Kitt Peak for Astronomers

  47. Virtual Worlds Colloboration for Experimental Economists

  48. Differences Between Virtual Worlds SecondLife Online: 62,100 Cost: $8,040 Support: High Control: Low Difficulty: Medium OpenSim 16 Snapshot $2,018 Annual Low User Based High High

  49. Some Things We Can Push With Virtual Worlds Experiments Bridge Lab and Field. Role of Context and Language. Emergence of Norms and Rules. Formation of Social Networks and Organizations. Larger Scale and Longer Time Horizons. Persistence. .

  50. Heterogeneous Dispositions to Cooperate and the Effects of Communication in a Second Life Collective Action Dilemma Kevin McCabe, Peter Twieg, JaapWeel

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