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Last Minute Bidding and the Rules for Ending Second-Price Auctions: Theory and Evidence from a Natural Experiment on the Internet. Alvin E. Roth – Harvard University Axel Ockenfels – Harvard University & University of Magdegurg. Abstract.

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Last Minute Bidding and the Rules for Ending Second-Price Auctions: Theory and Evidence from a Natural Experiment on the Internet

Alvin E. Roth – Harvard University

Axel Ockenfels – Harvard University & University of Magdegurg


Abstract l.jpg
Abstract Auctions:

  • Great deal of late bidding on internet second price auctions.

  • This phenomena does not result from irrational behavior, And can occur at equilibrium.

  • Very late bids have a positive probability of not being successfully submitted.


Abstract3 l.jpg
Abstract Auctions:

  • Natural Experiment – Amazon vs.. eBay.

  • Auctions in Amazon – does not have a fixed end time.

  • Strategic differences in the ending rules of the auctions cause significantly more late bidding on eBay.

  • Experienced bidders on eBay bid late. The effect goes opposite on Amazon.

  • Scale independence in the distribution over time: Last bids are distributed according to a power law.


Internet second price auctions l.jpg
Internet Second Price Auctions Auctions:

  • High bidder wins, but pays a price equal to a small increment above the second highest bid.

  • Auctions typically run for 7 days.

  • Proxy bid - allows the user to submit a reservation price (max. price) used to bid for him by proxy.


Dominant strategy l.jpg
Dominant Strategy Auctions:

It has been suggested that it is a dominant strategy for bidders simply to bid their true reservation price.

But …


Sniping l.jpg
Sniping Auctions:

Observing an auction house like eBay, will show two facts:

  • many bidders submit multiple bids in the course of the auction

  • a non-negligible fraction of bids are submitted in the closing seconds of an auction – Sniping.


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Sniping Auctions:

  • Observed behavior might preliminary be due to naïve, inexperienced or plain irrational behavior.

  • Inexperienced behavior - false analogy with first price auctions.


Common value l.jpg
Common Value Auctions:

  • Bidders can get information from others’ bids that cause them to revise their willingness to pay.

  • We will show that the observed behavior is consistent with equilibrium, perfectly rational behavior in both public and private value auctions.


The key l.jpg
The Key Auctions:

  • Danger of sniping – the key feature of this model will be that bids placed very near the deadline have some probability of not being successfully transmitted.


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Rational late bidding Auctions:

  • Multiple and Late bidding cannot, by themselves, be taken as evidence for private or common value nor for rational or irrational behavior.

  • Rational late bidding is sensitive to the rules of how the auction ends. This will motivate the empirical part of the presentation.


The intuition l.jpg
The intuition Auctions:

  • There is a cost to relying on the last minute bid, since it has a positive probability to fail to register.

  • So there is an incentive to bid early.

  • But there will be an incentive not to bid too high when there is time for other bidders to react. (to avoid a bidding war)


The intuition12 l.jpg
The intuition Auctions:

  • At equilibrium buyers may bid both early and at the very last moment.

  • The incentive for mutual delay comes from the probability that another bidder’s last minute bid will not be successfully transmitted.

  • At this equilibrium, expected value of bidders will be higher (and seller’s lower) than at the equilibrium at which everyone bids true values early.


The strategic model the ebay game form l.jpg
The strategic model Auctions: (the eBay game-form)

  • There are n bidders, N = {1,_,n}.

  • There is a minimum initial bid m, and a smallest increment s > 0 by which subsequent bids must be raised.

  • The “current price” (or “high bid”) in an auction with at least two bidders equals the minimum increment over the second highest reservation price.

    There are two exceptions to this:

eBay


The strategic model the ebay game form14 l.jpg
The strategic model Auctions: (the eBay game-form)

  • If more than one bidder submitted the highest reservation price, the bidder who submitted his bid first wins at a price equal to the reservation price.

  • If the current high bidder submits a new, higher bid, the current price is not raised, although the number of bids is incremented.

eBay


The strategic model the ebay game form15 l.jpg
The strategic model Auctions: (the eBay game-form)

  • Each submitted reservation price must exceed both the current high bid and the bidders last submitted reservation price (a bidder cannot lower his own previous reservation price)

eBay


The strategic model the ebay game form16 l.jpg
The strategic model Auctions: (the eBay game-form)

  • A player can bid at any time t{1}. A player has time to react before the end of the auction to another player’s bid at time t’ < 1, but the reaction cannot be instantaneous, it must be after time t’, at an earliest time tn, such that

    t’ < tn < 1.

  • At t = 1, everyone knows the bid prior to t and has time to make exactly one more bid, without knowing what other last minute bids are being placed.

eBay


The strategic model the ebay game form17 l.jpg
The strategic model Auctions: (the eBay game-form)

  • If two bids are submitted simultaneously at the same instant t, then they are randomly ordered, and each has equal probability of being received first.

  • Bids submitted before time t = 1 are successfully transmitted with certainty.

  • At time t = 1, the probability that a bid is successfully transmitted is p < 1.

eBay


Theorem l.jpg
Theorem Auctions:

  • There does not exist a dominant strategy at which each bidder j bids his true value vj at some time t<1. There can exist equilibria in undominated strategies in which bidders strictly prefer to make multiple bids, and not to bid their true values until the last moment, t=1, when there is only probability p<1 that the bid will be transmitted.

eBay


Proof l.jpg
Proof Auctions:

  • Two bidders, N = {1,2}

  • True values v1 , v2, independently, with probability ½, equal to either L or H, with m+s < L<H.

eBay


Proof equilibrium path l.jpg
Proof – Equilibrium Path Auctions:

  • Bidders i’s strategy is to bid m at t=0, and to bid vi at t=1, unless the other bidder deviates from this strategy.

eBay


Proof off equilibrium path l.jpg
Proof – Off Equilibrium Path Auctions:

  • If player j places a bid at some 0<t’<1, or if the high bid at t0 is greater then m, then player i bids viat some t’<t<1.

  • Either of these deviations, starts a price war at which the equilibrium calls for a player to respond by promptly biding his true value.

eBay


Proof payoffs to player i on the equilibrium path l.jpg
Proof- Payoffs to player Auctions: i on the equilibrium path

eBay


Proof23 l.jpg
Proof Auctions:

  • To calculate the value of p for which this is not a profitable deviation consider i’s payoff when he deviates by bidding H at t=0.

  • Player i will be detected only when his bid is selected to come in second.

  • Once detected i’s expected payoff is

    ½( H-L-s) + ½ (H-H) = ½(H-L-s)

eBay


16 possible states by a player i with value h l.jpg
16 possible states By a player Auctions: i with value H

  • The true value of the other bidder ( H / L )

  • First / second at t=0

  • Successful bid by player i at t=1 (successful or not)

  • Successful bid by player j at t=1 (successful or not)

eBay


Proof comparison to the equilibrium path l.jpg
Proof – comparison to the equilibrium path Auctions:

  • Bidder i with vi=H gains from his deviation in the state at which he is first at t=0, vj=L, and the other bidder j successfully submit a bid at t=1.

  • But, if he played the equilibrium,i would have been unsuccessful at t=1. In this case the deviating bidder i earns H-L-s instead of 0.

eBay


Proof comparison to the equilibrium path26 l.jpg
Proof – comparison to the equilibrium path Auctions:

  • Bidder i with vi=H similarly gains in the state in which his bid is second at t=0, if he would have been successful at t=1, and if the other bidder has vj=L. the expected gain is ¼(1-P)(H-L-s).

eBay


Proof comparison to the equilibrium path27 l.jpg
Proof – comparison to the equilibrium path Auctions:

  • But bidder I with vi=H strictly loses compared to equilibrium play in two cases (both coming in second at t=0).

  • When v=L, and the other player would have been unsuccessful at t=1 but I would have been successful. Thus earning H-L-s instead of H-m-s in equilibrium.

eBay


Proof comparison to the equilibrium path28 l.jpg
Proof – comparison to the equilibrium path Auctions:

2. When vj=H and the other bidder j would have been unsuccessful at t=1, and I would have been successful. Thus the deviation earns H-H=0 instead of H-m-s in equilibrium.

  • Both these state occur with probability

    ¼p(1-p) ….

eBay


Proof comparison to the equilibrium path29 l.jpg
Proof – comparison to the equilibrium path Auctions:

  • So the potential loss is:

    ¼ p(1-p)[(H-L-s)-2(H-m-s)]

  • Thus this kind of deviation is unprofitable so long as the payoff from deviation is less then the payoff from equilibrium, which occurs iff

    p > ½[H-L-s]/[L-m-s]

eBay


Proof the end l.jpg
Proof – the end Auctions:

  • The indicated strategies constitute an equilibrium whenever p>½[H-L-s]/[L-M-s]

    i.e. whenever the probability p of being able to bid successfully at the last moment is not to small.

    this complete the proof.

eBay


To sum up l.jpg
To sum up.. Auctions:

  • The proof shows that even in private value auctions, bidders may have reasons to refrain from bidding their true values as long as there is time for others to react, since otherwise they can cause a bidding war that raises the expected transaction price.

eBay


Break l.jpg

Break Auctions:


A common value equilibrium model of late bidding in ebay l.jpg
A common-value equilibrium model of late-bidding in eBay Auctions:

  • The bidders get information about the(ir) value for the good through the bids of the other bidders.

  • The motivation for late bidding – asymmetric information:

    • Collect information

    • Hide information

eBay


Dealer expert model antiques l.jpg
“dealer/expert” model – antiques Auctions:

  • The object for sale has one of two conditions: “Fake” –probability pf

    “Genuine”–probability pg=(1-pf)

eBay


Dealer expert model antiques35 l.jpg
“dealer/expert” model – antiques Auctions:

  • There are n=2 bidders:

  • u- uninformed, values genuine more highly then fake but cannot distinguish them:

    Vu(F)=0 < Vu(G) = H

  • i – Informed, perfect knowledge of the state of the world, and values:

    Vi(F)=0 < Vi (G) = H-c , with m<H-c<H.

  • That is - Vu(G) > Vi(G)

eBay


The strategic problem l.jpg
The strategic problem Auctions:

  • If the informed bidder reveals a genuine good (by bidding at any time t<1) then the uninformed bidder has an incentive to outbid him.

  • The uninformed bidder, if he bids H without knowing if the object is genuine, might loose by paying m>0 for a fake.

eBay


Theorem37 l.jpg
Theorem Auctions:

  • When the probability that the object is fake is high at any rational equilibrium in undominated strategies, the uninformed bidder u does not bid and the informed bidder i bids only if the object is genuine, in which case he bids vi(G)=H-c at t=1. If i deviates and makes a positive bid at any t<1 then u bids H at t’: t<t’<1.

eBay

back


Proof38 l.jpg
Proof Auctions:

  • An informed player will not bid his true value at any time t<1, because if he ever makes a positive bid the uninformed player can conclude that the object is genuine (and so over bid him).

  • However, as long as pf/pg>H/m, it never pays for u to bid at t=1 if i has not already bid.

eBay


Proof39 l.jpg
Proof Auctions:

  • When no player has bid at t<1, it is a dominant strategy for i to bid his true value for a genuine object in the sub game that begins when t=1.

  • Note that late bidding is not by itself an evidence for a private value auction.

eBay


Bidding on amazon l.jpg
Bidding on Amazon Auctions:

  • There is no time at which a bidder can submit a bid to which other will not have an opportunity to respond.

  • The times t at which a bid can potentially be made are:

    [0,1){1} (1,2) … (n-1,n) {n} …

Amazon


Private value amazon auctions l.jpg
Private value Amazon auctions Auctions:

  • Each bidder j has a true willingness to pay vj.

  • There is some value vmax such that

    Pr{vj<vmax}for all bidders j.

  • “willingness to bid” in case of indifference.

Amazon


Theorem42 l.jpg
Theorem Auctions:

  • At a sequential rational equilibrium in undominated strategies of an Amazon private value auction, the auction is not extended. All bidders bid their true value before t=1.

Amazon


Sketch of proof l.jpg
Sketch of proof Auctions:

  • No bidder ever bids above his value.

  • The auction must end by stage

    (n*-1,n*){n*}, with n* defined by

    sn*vmax< s(n*+1).

  • If the auction gets to stage (n*-1,n*){n*}, any remaining bidders who are not already the current high bidder and who have a value greater then the current price will bid their true value at some t<n* (at a time when p=1).

Amazon


Sketch of proof cont l.jpg
Sketch of proof cont. Auctions:

  • Inductive step. Suppose at some stage

    (n-1,n){n}, it is known that at the next stage any remaining bidders who are not the current high bidder and who have a value greater then the current price will bid their true value at a time when p=1.

Amazon


Sketch of proof cont45 l.jpg
Sketch of proof cont. Auctions:

  • Then any strategy profile that calls for a bid at t=n, is not part of an equilibrium, since that bidder gets a higher expected return by bidding his value at t<n.

  • The auction ends in the first stage: all bidders their true value by t<1.

Amazon


Common value auction on amazon l.jpg
Common value auction on Amazon Auctions:

  • One bidders information conveys information to other bidders.

  • We will show that some kinds of late bidding that occur at equilibrium on eBay will not occur at Amazon equilibrium.

Amazon


Theorem47 l.jpg
Theorem Auctions:

  • In the “expert/dealer model”, at a sequentially rational equilibrium in undominated strategies, the dealer never wins an auction on Amazon.

Amazon


Sketch of proof48 l.jpg
Sketch of proof Auctions:

  • The dealer values Fakes at 0, and values Genuine less than the uninformed bidder. If the object is Fake, no dealer buys it, since a strategy at which the dealer bids a positive amount for Fake is dominated by an otherwise identical strategy at which he does not.

Amazon


Sketch of proof cont49 l.jpg
Sketch of proof cont. Auctions:

  • So, if a dealer bids at some time t, he reveals the object is Genuine, and atequilibrium is subsequently, out bid with p=1 by the uninformed bidder.

Amazon





Cumulative distributions over time of bidders last bids53 l.jpg
Cumulative distributions over time of bidders’ last bids Auctions:

  • In both auction houses a considerable share of last bids is submitted in the very last hour of the auction.

  • However, late bidding is substantially more prevalent in eBay than in Amazon.

  • 20% vs. 7%


Cumulative distributions over time of auctions last bids l.jpg
Cumulative distributions over time of auctions’ last bids Auctions:

  • In more than 75% of all eBay auctions at least One bidder is still active in the last hour. Compare to 25% on Amazon.

  • Also, within the last hour, eBay bids are much more concentrated at the end then Amazon-bids.


To conclude l.jpg
To conclude Auctions:

  • It is safe to conclude that last minute bidding is not simply due to naïve time-dependent bidding.

  • It responds to the strategic structure of the auction rules in a predictable way.


The survey l.jpg
The Survey Auctions:

  • 91% of the responders confirm that late bidding is typically part of their early planned bidding strategy.

    • To avoid a bidding war/ keep prices down.

    • To avoid sharing valuable information.

  • 86% of all bidders testify, that it happened at least once to them that they started to make a bid, but the auction was closed before the bid was received.


Conclusions l.jpg
Conclusions Auctions:

  • Multiple and late bidding in Internet auctions has aroused a good deal of attention.

  • eBay’s hard close gives more reasons to bid late in private value auction, in common value auction and against naïve incremental bidders.


Conclusions58 l.jpg
Conclusions Auctions:

  • A strong correlation between late bidding and the type of good

    (antiques vs. computers)

  • The presence of multiple causes for the same phenomena means that it remains difficult to unambiguously assess the effects of the different auction designs.


The end l.jpg

The End Auctions:


Appendix sequential rationality l.jpg
Appendix – Sequential Rationality Auctions:

כל החלטה צריכה להיות חלק מאסטרטגיה דומיננטית לגבי המשך המשחק. במשחקים שבהם המידע מוגבל, בכל צומת החלטה, האסטרטגיה הבאה, צריכה להיות אופטימאלית בהתחשב בהערכת ההיסתברויות של כל האירועים האי-וודאיים, כולל כל צעדים קודמים, אך סמויים, שבוצעו ע"י השחקנים האחרים.

Back


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back Auctions:



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