Behavioral Economics custom-MADE

1. Behavioral Economics custom-MADE Michał Krawczyk University of Warsaw

2. Homo oeconomicus: the extinct species? • Choices maximize certain objective function… • … which is stable • Expected value maximized under uncertainty • Such rationality is „common knowledge” • The theory is mute about: • Capacity constraints • Cognitive limitations • Emotions • Biases • Heuristics • Impact of labels…

3. Behaviorial Economics • A booming industry • Aiming at descriptive accuracy… • …yet in-keeping with rigorous economic modeling standards • Allows for a number of deviations from the mainstream model of a rational decision maker… • … but assumes that these deviations follow certain patterns

4. A handfull of key ideas 1. Heuristics and biases 2. Framing 3. Myopia 4. Overconfidence 5. Fairness/reciprocity NB: not that incentives do not matter!

5. Behavioral Economics: Some research tools

6. He? Isn’t it just psychology? • Different methods: • Rigorous mathematical modeling • Experimentation with monetary incentives and without deception • Econometric analysis of field data • Different philosophy: • At least aimed at arriving at a single paradigm • Different focus/research questions • Ultimately, focus on policy applications

7. ExampleBeauty contest: an experiment Write down any integer between 1 and 100 2/3 of the mean will be computed Whoever is closest to this number is the winner

8. Beauty contest: analysis The mean cannot be higher than 100 So the winning number cannot be higher than 67 So nobody should pick any number above 67 So the mean cannot be higher than 45 So nobody should pick any number above 30 etc. Everybody should pick 1!

9. Beauty contest: analysis Everybody should pick 1! But that never happens So it’s a bad idea to do that! John Maynard Keynes’ allegory of the stock market Participants asked to choose the ``most beautiful’’ face out of 6 pictured. Those who picked the most popular face are eligible for a prize So you should not pick the prettiest but what you think others think that other think… Stock price can be far away from the fundamental because the assumption that rationality is kommon knowledge fails

10. For Starters: Heuristics and biases (Kahneman and Tversky) • heuristics and biases: • Heuristics: easy solutions to complex problems • (ABC group: „fast and frugal”) • Biases: systematic errors

11. Experiment Write down a ``random’’ series of 20 zeros and ones (as if it resulted from tossing a fair coin) Now, count the number of ``runs’’ (e.g. 1,1,0,1,0,0,1 has 5 runs) Statistically, there should be about (n-1)/2 runs in a series of length n. Typically, there are many more runs

12. Why is it so? Representativeness • An object should be representative of its class or process that generated it • 1,0,1,0,0,1 looks ``more random’’ than 1,1,0,0,0,1 although they are equally likely • Gives rise to ``gambler’s fallacy’’ • „Steve is shy and withdrawn…helpful…need for order… passion for detail…” Is Steve more likely to be a farmer or a librarian? • Base rate neglect • Sample size neglect • Insensitivity to predictability

13. Representativeness on the market • Efficient market hypothesis: no extra systematic profit • Empirical puzzle: companies with low P/E yield higher returns (are underpriced) • Explanation using RH: Investors overreact to current information • For instance, low present-day earnings make people think that this will continue

14. Availability heuristic • Judging frequency by the ease of retrieval • Famous men vs non-famous women & vv • Are „r........” or „..r……..” words more common? • Bias of imaginability

15. Anchoring • Insufficient adjustment: roulette wheel and African countries in the UN • 1x2x3x…x8 greater than 8x7x6x…x1 • Miscalibration & overconfidence: give a confidence interval for Dow Jones • Is the Nile more or less than 200 (2000) miles? How long is it? Results 300 (1500)

16. Anchoring and adjustment • conjunctive events (A  B) are overestimated; • disjunctive events (AB) are underestimated (how many people are needed for the probability that they share a birthday to be > 50%?)

17. mini-summary • Judgment is based on a limited set of heuristics (just as perception) • leads to biases which are systematic and hence predictable (at least in principle) • Imperfect or irrational they may be, but still useful, most of the time • Some biases may be adaptive in combination with other ones

18. Overconfidence • Overtrading (Barber, Odean: ``Boys will be boys’’) • Excessive entry (Camerer, Lovallo, AER `99) • Overshooting in corporate investments (Malmendier and Tate, JoF `05) • Stock picking • On average, US workers report that their own employer’s stock is less risky than a diversified mutual fund. • Enron employees thought so, too

19. Status Quo Bias • Decision-makers generally prefer to stick with the status quo • even when this means foregoing large profits • even when told that the default is suboptimal • Examples: retirement savings, insurance deductibles, organ donation…

20. The Harvard Know-It-Alls are Status Quo-Biased too Samuelson andZeckhauser (1988) In the 1980s, Harvard University added several plans to its choice of health plans, Existing employees “chose” the older plans app. 3 times more often than the new ones. In other words, incumbent employees made the easiest choice of all: to do nothing.

21. OLD Default Contribution: Must actively sign up Default Allocation: None NEW Default Contribution: 3 percent of compensation deducted for plan Default Allocation: Money Market Fund Example: Brigitte Madrian and Dennis Shea (2001)• Design: A Fortune 500 Company Switched 401(k) default on April 1, 1998. Madrian and Shea examine behavior of new hires.

22. 401(k) Participation IncreasesPercent at Specified Contribution Rate Contribution Rate Source: Madrian and Shea (2001).

23. 401(k) Asset Allocation Also Changed Percent of Assets Source: Madrian and Shea (2001).

24. Impact of Automatic Enrollment in 401(k) Before, During and After Source: Choi, Laibson, Madrian, Metrick (2004)

25. Is More (Choice) Always Better? Adding more complex options: • delays choice, strengthens the Status Quo bias (O’Donoghue and Rabin, 2004). • biases choice, complex options avoided (Shafir and Tversky, 1994; Iyengar and Kamenica, 2006). • 1/N rule – Add a second fund and many investors divide portfolio 50-50; add a third fund and 1/3 placed in each. • (several other examples of menu dependance)

26. Myopia • Would you rather have: $100 right now or $101 in a week? • How about $100 a year from now or $101 in a year+a week from now • We are impatient in the short run, patient in the long run. • (referred to as „(quasi)hyperbolic discounting”) • U=u0+βδu1+ βδ2u2+βδ3u3+… • McClure et al. (Sci. 2004) claim to have found separate neural circuits primarily associated with, resp., β and δ

27. Real Consequence of Hyp. Discounting • A typical American has an outstanding credit card debt of $6,000 • Pretty costly • Yet few people can pay off such amounts • And immediate pleasure of purchase hard to resist

28. Inconsistent Choices Due to Impatience • Eat chocolate today with delayed health consequences but immediate gratification, or eat fruit today with less gratification but better long-term health consequences. • What do you choose today for you to eat next week? What do you choose today to eat today? • Research by Daniel Read and Barbara van Leeuwen (1998)

29. Choosing fruit vs. chocolate Choosing Today Eating Next Week Time If you were deciding today, would you choose fruit or chocolate for next week?

30. Patient choices for the future: Choosing Today Eating Next Week Time Today, subjects typically choose fruit for next week. 74% choose fruit

31. Impatient choices for today: Choosing and Eating Simultaneously Time If you were deciding today, would you choose fruit or chocolate for today?

32. Impatient choices for today: Choosing and Eating Simultaneously Time For Today, theygenerally go forchocolate 70% choose chocolate

33. Impatience: education in developing countries Probe report on basic education in India: • 85 percent of the parents agreed thatit was important for children to be educated. • 57 percent of parentsresponded that their sons should study “as far as possible.” In fact, only a small minority obtains substantial education levels. This is becuase education requires instant sacrifice and offers delayed rewards Sporadic attendence: enrollment, attendence, drop-out, renewed enrollment etc. Salience matters (Akerlof 1991): e.g. beggining of the school year

34. Policy implications Continuous low fees Efforts to make schooling more attractive to students Properly timed information campaigns

35. Do you know that you’re biased? Sophisticates and naives (O’Donoghue, Rabin; AER ‘99) Suppose that β=.5, δ=1 (everything that does not happen now is discounted 50% Naives think that their β is 1. Suppose you have to do the assignment on one of the four days: Mon, Tue, Wed, Thu The costs are 3, 5, 8, 13 Temp. Cons: (Y, Y, Y, Y) → will work on Mon Naives: (N, N, N, Y) → will work on Thu Sophisticates: (N, Y, N, Y) → will work on Tue

36. Does sophistication always pay? β=.5, δ=1 Suppose now you can go for a party on one of the four days The rewards are: 3, 5, 8, 13 Temp. Cons: (N, N, N, Y) → will party on Thu Naives: (N, N, Y, Y) → will party on Wed Sophisticates: (Y, Y, Y, Y) → will party on Mon Sometimes it’s better to be naive!

37. Ulysses and the Sirens:Commitment devices

38. Commitment devices Gym memberships Christmans clubs Fat farms Voluntary casino bans Disulfiram: „[with even small amounts of alcohol] produces flushing, throbbing in head and neck, throbbing headache, respiratory difficulty, nausea, copious vomiting, sweating, thirst, chest pain, palpitation, dyspnea, hyperventilation, tachycardia, hypotension, syncope, marked uneasiness, weakness, vertigo, blurred vision, and confusion”

39. Commitment devices: cont’d „Quitting Smoking is Easy, I’ve Done It Hundreds of Times” Taxes on cigarettes can play the role of a commitment device Gruber andMullainathan (2002) find that higher taxes on cigarettes make those prone to smoking better off Ariely andWertenbroch (2002): students volunteered to self-impose essay submission deadlines

40. Commitment devices in developing countries • Roscas: • Small contributions, large pay-out • Self-imposed social pressure to continue contributing • Helps overcome self-control problems • Holding wealth in non-liquid assets • Less access to banking makes it more difficult to overcome temptation

41. Researchers go bankers Ashraf, Karlan, and Yin (2005) Offered an account with a commitment device to 842households in the Philippines Access constrained to reaching a self-specified savings goal or a self-specifiedtime period. A control group of 466 households from the same sample is offered averbal encouragement to save but with no commitment. A sizeable demandfor commitment observed And an impact of commitment on savings.

42. Time inconsistence in maize farmers Duflo, Kremer, and Robinson (2005) savings for fertilizer use for maize crop in Western Kenya many farmers plan to use fertilizer in the next season but very few end up doing it SAFI: Saving and Fertilizer Initiative—safi means “pure” in Swahili) Each season at harvest a farmer is offered to buy a voucher for fertilizer Transportation costs saving is the only advantage

43. SAFI: results • SAFI offered to a group of 420 farmers. • In addition, 293 farmers visited at fertilizer application time, made an offer equivalent with SAFI or 50% discount • Results: acceptance: • SAFI: 40 percent • Subsidy: 45 percent • No subsidy, no commitment: 21 percent

44. Loss Aversion • Losses loom larger than equivalent gains • Kahneman, Knetsch and Thaler’s (1990) mug experiment: WTP/WTA discrepancy • Attributed to loss aversion: owners’ loss of the mug loomed larger than buyers’ gain of the mug. • cf: „Endowment effect”

45. Additional Evidence on Endowment Effect • John List’s field experiment with sports card collectors • Endowment effect seems to go away with experience

46. Field evidence of loss aversion Odean (1998) showed the disposition effect: (small) investors in the stock market tend to sellstocks they have made money on… … and keep the ones they have lost money on. Inconsistent with standard theory and actually contrary to tax incentives. Genesove and Mayer (2001) found thatindividuals who have taken a loss on their house set far higher prices when it comes time tosell.

47. Loss aversion? A field experiment (submitted to Econoics Letters) • Run during a mid-term Microeconomics test • Two supposedly different scoring rules used: 3 points for each correct answer 1 point for no answer 0 for each incorrect answer 55 points to pass • OR: 2 points for each correct answer 0 point for no answer -1 for each incorrect answer 45 points to pass

48. A field experiment on LA: findings Hypothesis: less risk taking with explicit penalty points less In fact, with N=93 we see little evidence of loss aversion Re-run with app. 400 subjects, no evidence again

49. Examples of policy implications Favor policies that preserve benefits, rather than compensate for the loss thereof Ensure property rights are well defined: it may deter violence becuase the owner will be more motivated to prevent a loss than the challenger to pursue a gain (A new view on the well-known problem pertinent to many developing countries)

50. Combining it all together: SMaRT • A program created by Thaler and Benartzi (2003) • Aimed at nudging people to save more • The crucial idea: people commit to saving more out of their pay next pay rise Why is it smart? Foregone gain, not in an effort to get people • Lack of free will → precommitment • Loss aversion → foregone gain rather than loss • Status quo bias → opt-out rather than opt-in