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If you are planning to buy a used car

If you are planning to buy a used car. Start. Logon to. Examine. No. Buy. Yes. End. How to decide: It could be a lemon. Earlier people would take it to a mechanic for a careful examination. Overview. The model Characterizing optimal strategies for t he searcher t he expert

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If you are planning to buy a used car

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  1. If you are planning to buy a used car

  2. Start Logon to Examine No Buy Yes End

  3. How to decide: It could be a lemon Earlier people would take it to a mechanic for a careful examination

  4. Overview • The model • Characterizing optimal strategies for • the searcher • the expert • Market design

  5. Sequential Model Reject & Start again Noisy signal Buy & Terminate Search Cost: The Searcher Query an Expert for fee

  6. The Model • Expert and Searcher: Rational Agents • Expert sets profit maximizing fee • Searcher formulates utility maximizing strategy • Stackelberg game

  7. Notation = Search cost, = Expert’s fee per query : distribution of signals : conditional distribution of values given signal : Expected value of Searcher’s Utility : Expected value of Expert’s profit

  8. Distributions fv(x) fv(y|s) fs(y|v) fs(x)

  9. Overview • The model • Characterizing optimal strategies for • the searcher • the expert • Market design

  10. If having no expert… • … but rather just noisy signals: • S – signals for which we buy

  11. HSGN • restriction that higher signal values are “good news" in the sense that when s1> s2, the conditional distribution of v given s1first-order stochastically dominates that of v given s2(Wright 1986, Milgrom 1981): • if , then, • The condition requires that the probability that the actual value is greater than any particular value v is greater for the case where the searcher received signal s1.

  12. Main Claim The proof is based on showing that, if according to the optimal search strategy the searcher should resume her search given a signal s, then she must necessarily also do so given any other signal s’ < s Use V to denote the expected value of continuing the search

  13. Main Claim (cont.) If better to resume search given s: Given HSGN: Therefore: Now: Optimize according to t to get part (a) of the theorem

  14. Now with the expert… • General Strategies: • Reject some (without consulting the expert) • Accept some (without consulting the expert) • Consult the expert and then decide if to reject or accept

  15. Theorem • Claim – given HSGN, the optimal strategy for the searcher is based on (tl,tu,v)

  16. Bottom Line • For satisfying the HSGN assumption, the optimal search strategy can be described by the tuple • where: • : search should be resumed; • search should be terminated • : Query the expert and accept and terminate if the value obtained from the expert is above the expected value of resuming the search,, otherwise search should resume

  17. Expert’s Profit

  18. AN Example s

  19. Effect of cs on signal Threshold keeping constant Query & decide Accept Reject

  20. Effect of ce and de

  21. Overview • The model • Characterizing optimal strategies • the searcher • the expert • Market design

  22. Social welfare • Social welfare = Searcher’s Utility + Expert’s profit • Expert’s Profit : • Searcher’s Utility :

  23. Market design Does it make sense for market designer to subsidize the query cost of an expert

  24. Market design pays lump-sum amount b to the expert to reduce the query cost from to and new social welfare W’

  25. Effect of ON SUBSIDY • At social welfare maximizing subsidy: • Digital services with close to zero marginal cost should be provided for free.

  26. Claim The optimal level of subsidy for an additive measure of social utility is the level that forces the buyer to exactly fully internalize the cost of provision of expert services

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