“Bid More, Pay Less” –Overbidding and the Bidder’s Curse ...

KIT – Karlsruhe Institute of Technology

Institute for Economics (ECON)

www.kit.edu

“Bid More, Pay Less” – Overbidding and the Bidder’s Curse in Teleshopping AuctionsLH1: Auctions – Stony Brook Center for Game Theory, NY, July 17th, 2017

Fabian OckerE-Mail: [email protected]

Fabian Ocker


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„Bid more, pay less“ – A German thing?

Fabian Ocker


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Outline

1 Introduction: 1-2-3.tv Auctions

2 Related Literature and Data Set

4 Hypotheses and Results

3 Theoretic Analysis

5 Summary and Outlook

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Introduction: General Information

Interactive auction-teleshopping channel.

Start of broadcast: October 1st, 2004.

Current broadcasting time: 365 days per year à 20 hours per day.

Broadcast is split into eight product categories, e.g. „Jewlery“,

“Beauty & Wellness”, “Household & Kitchen”.

Feature: Two sales channels.Customers bid in the auction or purchase for a fixed online shop price.

Consequently, an (objective) market price is available.

Distribution channels for auction broadcast:

Offline: TV & telephone,

Online: Website or App.

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Introduction: Applied Auction Mechanism

Auction form: Dutch (sell) AuctionBidding rule:

Auction price declines continuously until a bidder signalizes his willingness

to pay at the current price.

Implementation:

Current auction price is presented on an auction watch.

The auction terminates once a bidder signalizes his willingness to pay.

Scoring rule:

The signalizing bidder wins the auction.

Price rule:

The final price equals the price shown on the auction watch when the

winning bidder signalized his willingness to pay.

Feature: Multi-unit auctionUniform price auction (lowest accepted bid, LAB).

Homogeneous goods (complements possible).

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Related Literature (on Single-unit Auctions)

Amyx and Luehlfing (2006) with a data set of 416 online auctions.

First evidence for overbidding when simultaneously a fixed price is available.

9% of overbidding, 14% mean percentage of overbidding.

Malmendier and Lee (2011) with two data sets of 2,200 online auctions.

Name the overbidding phenomenon as “Bidder’s Curse”.

42%/48% of Bidder’s Curse, 2%/10% mean percentage of overbidding.

Best explanation approach for Bidder’s Curse is limited attention.

Schneider (2016) with a data set of 552 online auctions.

Limited attention is a ”premature” explanation approach.

Search costs for price information need to be considered.

23% of Bidder’s Curse.

Freeman, Kimbrough and Reiss (2017) conduct a laboratory experiment.

Overbidding increases when search costs for price information are high.

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Data Set

Auction outcomes from January 19th to March 23rd, 2016 (65 days).

Crawler (in C#) wrote data from www.1-2-3.tv in MS Excel.

Each submitted bid is reported (around 700,00 bids).

à Note: reported bid = sold good

Date, product, distribution channel, uniform price, online-shop price, etc.

Several contributions to existing literature:

Substantially greater data set.Systematic analysis across different product categories.

Extension of the analysis to multi-unit auctions.

Consideration of teleshopping auctions.

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Theoretic Analysis

IPV-model of the 1-2-3.tv auction:

Valuation of bidder depends solely on own signal.

Individual signal is known by each bidder before the auction.

Valuations of other bidders are unknown (distribution common knowledge).

Assumption: No transaction costs.

Analysis of bidding strategy (following Malmendier and Lee, 2011):

Extension of the multi-unit Dutch auction to a two-stage game:

First stage: Multi-unit auction with uniform pricing (HRB/LAB).

Second stage: Purchase of goods for a fixed price.

Furthermore: Distinction of single-unit and multi-unit demand.

Main result: Rational bidders do not overbid the online shop fixed price.

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Do bidders in the 1.2.3.tv auctions behave according to theory?

Hypothesis 1 (Overbidding in 1-2-3.tv auctions): Bidders do not submit bids higher than the simultaneously available online shop price for the same good.

Hypothesis 2 (Bidder’s Curse in 1-2-3.tv auctions): None of the final uniform auction prices exceed the simultaneously available online shop prices.

Hypotheses and Results (1/2)

Findings

Finding 1 (Overbidding in 1-2-3.tv auctions): In 25.55% of all auctions, bids are higher than the simultaneously available online shop price for the same good.

Finding 2 (Bidder’s Curse in 1-2-3.tv auctions): In 5.18% of all auctions, the final uniform auctions price is higher than the simultaneously available online shop price.

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What are influencing factors for overbidding and the Bidder’s Curse?

Finding 3 (Search cost in 1-2-3.tv auctions - overbidding): Offline-bidders overbid greater and more often than online-bidders:

Relative frequency of overbidding of 26.77% (19.88%) for offline (online) bidders,

Average percentage of overbidding of 9.67% (8.98%) for offline (online) bidders.

Finding 4 (Search cost in 1-2-3.tv auctions – Bidder’s Curse): Offline-bidders do not experience the Bidder’s Curse more often than online-bidders:

Relative frequency of Bidder’s Curse of 5.31% (4.66%) for offline (online) bidders,

Average percentage of Bidder’s Curse of 5.84% (5.61%) for offline (online) bidders.

Finding 5 (Learning effect in 1-2-3.tv auctions): The Top 10 most frequent customers do not experience a learning effect,but overbid greater and more often than the average 1-2-3.tv customer.

The most frequent customer submitted 488 bids with total expenses of 37,625€.

Hypotheses and Results (2/2)

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We find that overbidding and the Bidder’s Curse are also present in

multi-unit teleshopping auctions.

However, the frequency of the Bidder’s Curse is (far) lower than in

studies on single-unit auctions.

We argue that this is due to multi-unit auctions with uniform pricing.

Here, overbidding does not mandatorily result in the Bidder’s Curse.

In other words, overbidding is less risky.

We find that offline-bidders overbid greater and more often than online-bidders, and reason – in line with recent scientific work – that

this is linked to different search costs of these two types of bidders.

Further research could focus on …

… empirical investigation of other formats of teleshopping auctions.

… other shops that offer two sales channels.

Summary and Outlook

Fabian Ocker


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Thank you for your attention!

16.07.17

M.Sc. Fabian Ocker

Institute for Economics (ECON)Karlsruhe Institute for Technology (KIT)

[email protected]://games.econ.kit.edu

“Bid More, Pay Less” –Overbidding and the Bidder’s Curse ...

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