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Consumers and behavioral IO Prof Colin Camerer

Consumers and behavioral IO Prof Colin Camerer. What happens in industrial structure and consumer choice if agents are limited in rationality or willpower? Ellison (07): A. Firms are limitedly rational B. Consumers are limitedly rational, firms respond

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Consumers and behavioral IO Prof Colin Camerer

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  1. Consumers and behavioral IOProf Colin Camerer • What happens in industrial structure and consumer choice if agents are limited in rationality or willpower? • Ellison (07): • A. Firms are limitedly rational • B. Consumers are limitedly rational, firms respond • C. Scope for regulation? (e.g. consumer protection) • Evidence from household finance, etc.

  2. Behavioral IOProf Colin Camerer • Firms are limitedly rational • Cyert and March 56 • Business entry (Camerer-Lovallo 99) • Corporate finance (e.g. overconfident CEO’s Malmendier, mergers) • ε-equilibrium in Cournot, Bertrand competition • Fairness and learning in price matching experiments

  3. Firms: Limits on firm rationality • Behavioral theories of the firm (50s) • Largely died out. Why? • Did not have agency theory etc. to work with • Why wouldn’t bad managers be replaced? • Poor sparse data • What is an “organizational routine”? • Due for revisit? • “routines” of organizations are cognitive, correlating devices (Kreps 90) • Does appear that firms get stuck repeating success of the past, have trouble changing (e.g. GM, Sears) • Poor governance can explain non-profit-max’n • Better data

  4. Limits on firm rationality • Managerial overconfidence • High rate of business failure. Why? • Business entry experiments (Cam-Lovallo 99) • Top c+5 entrants share $50. Others get -$10 • Ranked by random numbers or skill (trivia)

  5. Exps 1-4 typical recruiting, exps 5-8 self selection for skill

  6. ε-equilibrium and pricing: Small ε can have large IO effects • ε-equilibrium, approximate best responses • Bertrand duopoly: Set prices, consumer buys cheapest •  both sellers price at marginal cost • But there are mixedε-equilibrium (Baye-Morgan 04 RAND) • Can earn (2επm)1/2-ε from deviating (p>cost) • e.g. if ε=.01πm industry profit is .26πm •  mild deviations produce strong pressure away from perfect competition • Cournot quantity competition, D(p)=1-p • Quantities in range (1/3)±(2/3)(ε)1/2 are ε-equil. (q=1/3 is comp.) • Includes monopoly (q=1/4 each) for ε>1/64

  7. Bertrand price matching with loyalty rewards (Capra, Goeree, Gomez, Holt AER ‘99) • Players 1, 2 pick integer prices [80,200] ¢ Price is P=min(P1,,P2) Low price firm earns P+R (R>1) High price firm earns P-R • What happens?

  8. Example: Price matching with loyalty rewards (Capra, Goeree, Gomez, Holt AER ‘99) • Players 1, 2 pick prices [80,200] ¢ Price is P=min(P1,,P2) Low price firm earns P+R High price firm earns P-R • What happens? • Rational theory: competition  prices go to 80 • Always want to undercut by 1 unit

  9. Intuition: Suppose p uniform Move from p to p+1 1/121 lose R were tied, now high 1/121 lose R+1 Were low, now tied (200-(P+1))/121 gain 1 by raising price Pays iff p<200-2R-2 Pressure away from Nash QRE for various R

  10. Cognitive hierarchy model(Camerer, Ho, Chong QJE 04) • 0-step thinkers randomize • K-step thinkers respond to 0…k-1 play • Distribution f(k) is Poisson(τ) • Pricing: Step k chooses 200-2R-(k-1) • Prices approximately 187-1.56R (τ=1.5)

  11. Price matching data over time CH predictions • R=5 179 • R=10 171 • R=20 156 • R=25 148 • R=50 109 • R=80 62

  12. Influence of low (79) and high advice (119) with R=5 (Cabrera-Capra-Gomez 04) • No advice (median 100) • Low advice (79) • Median 81 • High advice (119) • Median 114

  13. B. Consumers are limitedly rational, firms anticipate or respond 1. Rules of thumb in following other consumers 2. Search costs/impatience (old sales models reinterpreted) (no work on this) 3. Procrastination (gyms, Wertenbroch) 4. Hidden fees 5. Reference-dependence & sticky pricing 6. Learning 7. Regulation

  14. 1. Rules of thumb • Smallwood-Conlisk QJE 79 • rational confirmity is “a massive game theory problem with all other consumers”, too difficult • rule is a shortcut for consumers…and theorists (don’t have to endogenize it) • K brands, breakdown probability bk (quality measure), switches to h with probability mh(t)s • s=0 random • s=1 “ask one friend” • s ∞ always pick most popular (brand obsession) • Results: • s<1 better products become more popular, but all survive • s=1 better product dominates in the long run • s>1 bad product can dominate if initial m(0) is high • Typical of results: Sensitive to nature of word of mouth

  15. 3. Pricing procrastinators • Blockbuster…huge profit from late fees, forecasting error + loss-aversion? • Credit card “teaser rates” (Ausubel AER 91, Shui + Aus.) • Only 70% pay off balance, average household balance $5,000 • Netflix– pay a monthly fee for movies…but don’t get around to watching them! •  Per movie fee may be large (data?) • Price discrimination through impatience • Discriminate by demand based on impatience • Movie openings (Star Wars) (now DVD sales > box office gross) • hardcover books • Rebates • Consumers plan to cash in rebates, only 50% do so (FTC) • 10% of rebate checks never cashed!

  16. Pricing virtuous goods: Gyms I • Health clubs (Della Vigna & Malmendier, 04 QJE 05 AER) • Nonlinear two-part monopoly pricing: Membership F, per-use fee p, user cost c distributed cdf G(c) Firm (F,p)….consumer acc pay F, choose Ex pay c,p…… earn b , choose N pay 0 …….. earn 0 rej earn time 0………............time 1…............……………………………..time 2 • Consumers hyperbolic with parameters Naïve hyp =1 :Plans to choose E, earns cutoff But when t=1, E is cutoff is

  17. Gyms II • Cutoffs on cost that generate gym attendance + G(c)  probability of going • E.g. p(going) is • forecasting error is • Firm’s optimization problem: Max profits while forecasting participation

  18. Gyms III • Pricing exponential discounters (β=1) • p*=a (price=marginal cost), F* makes participation constraint bind • Pricing hyperbolic discounters (β<1) • p*<a and F* above exponential case • Two types love this contract for different reasons: • Sophisticates like low p* to induce them to go • They prefer a high F, low p* contract to buy self-control • (May prefer high F to create “sunk cost fallacy”, not in model) • Naifs like low p* because they think they will go a lot • Naifs cross-subsidize sophisticates. How to skim naifs? • Moneyback guarantee with high unrefundable payment? • Evidence: F around $300/yr, per-visit fee=$15 • Average visits cost $19/visit. Indicates some naifs

  19. 4. Why hasn’t internet created price wars? Obfuscation & hidden fees (G+S Ellison2 04) • Similar to product differentiation

  20. Hidden “shrouded” add-ons (Gabaix-Laibson QJE 06) • Bank fees, mutual fund mgt fees, hotels, printers • Base good (p) + add-ons (a) + substitutes (e) (e.g. bring water to hotel). Price a<b, e<b. • Firms hide/show…. Consumers buy……….observe a, buy add-on prices p,a…….........……………………………………………………… time 0 time 1 time 2 • Sophisticates (α%) update about hidden a, can substitute e • Myopes (1- α%) when visible λ% anticipate price a, 1- λ% do not notice

  21. Hidden add-ons II • D(x) is probability of buying for relative surplus x • Define α† =1-e/b and μ=D(0)/D’(0) • μ=0 corresponds to perfect competition (D’(0) sensitivity to x) • μ--> ∞ insensitivity ( high profit) • Prop 1: • Case 1: α<α† not many sophisticates • firms hide add-on price a • p*= μ-(1- α)b, a*=b charge highest add-on price, subsidize base good • Sophisticates know, buy substitute e. Welfare loss because e is costly • Case 2: α>α†many sophisticates • p*= μ-e, b=e sophisticates police the market, everyone substitutes

  22. Hidden add-ons: Why doesn’t competition work? • Making customers sophisticated isn’t always profitable • (Case 1) sophisticates like hidden add-ons! They get a base-good subsidy and save p*-e. Naïve don’t perceive add ons (or optimistically don’t think they will need them)

  23. 5. Loss-aversion & pricing(Heidhues & Koszegi, 04) • Personal equilibrium(Rabin & Koszegi 04): • Consumers create reference point (matches expected purchase) • Loss-averse (λ) toward loss of money or goods (value v) • Timing Firms pick F(p)……..consumer forms beliefs…. price p, cost c realized….shock realized…consumer buys • Shock h(w) to consumer value unique-fies demand (Prop 2)

  24. Loss-aversion results • Price stickiness (Prop 3) • For substantial loss-aversion, firms choose discrete prices • Prices don’t vary smoothly with cost c (surprising) • “menu costs” empirics, Kayshap et al QJE 02? • Intuition: At a price p, consumers dislike foregoing a lower price, dislike paying more; incentivizes firms to lump prices together • Cf. “kinked” demand curve (1930’s econ) to explain sticky prices…but in this model it is derived endogeneously • Countercyclical markups (shrink in booms, grow in busts) • Explains puzzle of fixed consumer prices and wages shortages in recession, excess supply in booms

  25. 6. Learning • Perhaps consumers can learn • Time scale of learning, and forgetting, are crucial • Agarwal, Driscoll, Laibson, Gabaix (07) • 128,000 credit card customers, 3 yrs, 100M transactions • Three kinds of fee “mistakes” • Late ($30-35 + can trigger APR increase) • Over limit ($30-35 +) • Cash advance (max($5, 3%X, APR 16%)

  26. People learn in 3-4 yrs

  27. Learning and forgetting (reinforcement) • Stock of past fees Ft-1 • Learning (β) is 20%/mo • extra late fee reduces p(late) 20% • Forgetting (δ) is 15%/mo • 1/γ is “saturation” (limit of F/(1+ γF)), around 15

  28. Phone calling plans • Miravete AER 03 • Data from 1986 Texas • Flat fee ($18.70/mo) vs linear rate • Generally underestimate usage • 90% do not switch across three months • 60% on linear plan see they could pay less on flat fee, switch (save $5) • Rational switching occurs because few make mistakes, and mistakes are transparent • Grubb 06 • College cell phone plans • Narrow confidence intervals–- are sometimes surprised at how much they talk • Result: Overconfidence  choose the wrong contract and pay high overage

  29. 7. Regulation • What about consumer protection? • Private solutions • Learning • May be slow • Some decisions are early and irreversible or rare (durables, houses, education, wedding & children, funeral homes…) • Advice • Informal (need to understand “wisdom of crowds”) • Professional (agency problem: High fees, kickbacks, etc.) • Reputation • Competition • Depends on bundling education & products (e.g. Palm Pilot) • Depends on fighting status quo bias and value of negative ads • Class action lawsuits (for many small-harm cases) • Media reporting

  30. My (our) view • I am not an advocate for frequent changes in laws and constitutions. But laws and constitutions must go hand in hand with progress of the human mind. -- Thomas Jefferson

  31. Public solutions: • Taxation • “Sin” taxes to reduce internalities from temptation • Alcohol, cigarettes, gambling,… fatty food? • Restricting contract terms • Cooling off • Must opt in to auto-renew (negative option) • Judicious use of the “best” default option • Consumer education • Teach high school economics!

  32. Central empirical questions • Heterogeneity • Interaction of naïve & sophisticated (Camerer-Fehr Sci 06l) • Do sophisticated protect naïve or do firms sort them? • Endogeneity of thinking • Will consumers gather more information when they think they might make mistakes? • Not if low knowledge is correlated with low self-knowledge (e.g. Dunning et al psychology) • Disclosure • How to disclose simply without confusing consumers further? • Moral hazard • Will public regulation crowd out private consumer sophistication? • E.g.? Adjustment post-communist regimes (North Koreans, East Germans after reunification)

  33. Crowding out of consumer vigilance • “In a regulated industry, however, there’s a tendency for consumers to let up on their vigilance. They mistakenly believe that the government is looking out for them, and that’s simply not possible all the time…Rogue [web] sites can’t be stopped through regulation. They can only be stopped through the adherence of caveat emptor” – Calvin Ayre, CEO Bodog (Costa Rican online gambling site)

  34. FTC concerns • Sect. 5 of the FTC Act • “…unfair or deceptive acts or practices in or affecting commerce are declared unlawful” • Deception • Fraud/false claims • Misleading claims (overstatement, implied…) • Usually clear (e.g. magnet bracelet to lose weight, permanent hair dye) • “Unfair” • “representation, omission or practice that is likely to mislead the consumer acting reasonably in the circumstances, to the consumer’s detriment” • Scientific/regulatory challenge: What is “acting reasonably”? System 1 or does it require system 2?

  35. Conclusion: Behavioral IO • Recipe: • A. Pick a consumer pattern– optimism, loss-aversion, inertia, limited attention... • E.g. optimism about phone minutes  fixed minutes calling plans • Analyze: Does competition erase it? • B. Pick a market pattern (e.g. $9.99 pricing, high cosmetics markups) • Explain. Can it be derived as optimal?

  36. Where do behavioral IO assumptions come from? • Reduced-form assumptions (Ellison) • Rule of thumb about social learning • Computational complexity of states • Fershtman-Kalai 93, Rubinstein 86+ • * Psychological empirical regularities • Quasi-hyp’ic and gyms, business entry, consumer search… • Opinion: Empirical basis * is better. Why? • Have to pass an empirical test eventually • Models with correct assumptions more likely to make correct market predictions • Empirics guides which of many modelling directions to go

  37. Open questions • Can firms always create new hidden add-ons? • Markets for rare purchases (houses) • Viral marketing/word of mouth • How well do experts/advice/supershoppers. • Positive legal role for standardization to fight obfuscation? • Legal: How to regulate? Forcing disclosure has two effects • i. Informs consumers • ii. Penalizes firms who profit by exploitation • Simple disclosure is challenging though

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