Bidding behavior, seller strategies, and the utilization of information in auctions for complex goods [Elektronische Ressource] / vorgelegt von Arno Robin Schmöller

Arno Schmoeller

Informations

• Publié par: ludwig-maximilians-universitat_munchen
• Publié le: 01 janvier 2009
• Nombre de lectures: 14
• Langue: English
• Poids de l'ouvrage: 4 Mo

Extrait

Bidding Behavior, Seller Strategies,
And The Utilization of Information
in Auctions For Complex Goods
Inaugural-Dissertation
zur Erlangung des Grades
Doctor oeconomiae publicae (Dr. oec. publ.)
an der Ludwig-Maximilians-Universit¨ at Munc¨ hen
Volkswirtschaftliche Fakult¨ at
2009
vorgelegt von
Arno Robin Schm¨ oller
Erstgutachter: Prof. Dr. Klaus M. Schmidt
Zweitgutachter: Prof. Dr. Martin Kocher
Datum der mundlic¨ hen Prufung:¨ 18. Januar 2010
Promotionsabschlussberatung: 10. Februar 2010To my parentsAcknowledgements
First and foremost I want to thank my thesis supervisor Klaus M. Schmidt. He was not
only most helpful in inspiringly discussing ideas, insightfully commenting early drafts of
my papers, and encouraging me, but also willingly wrote numerous reference letters for
scholarships and summer schools.
I am also deeply indebted to Martin Kocher for agreeing to serve as second supervisor on
my committee and for the insightful comments and suggestions he provided on numerous
occasions. Ray Rees completes my thesis committee as third examiner, which I gratefully
acknowledge, as well as his encouragement, helpful comments, and the numerous reference
letters he provided for me. I also want to thank him for always being welcome at his chair
during the time of my doctorate.
I am particularly grateful to my co-author Florian Englmaier for working as a team in three
research projects, which are all part of this thesis. His economic thinking and creativity
are outstanding. I am grateful to him for being always available for vivid discussions and
insightful comments and for supporting and encouraging me throughout the last four years.
During the course of writing this dissertation, I enjoyed inspiring discussions with many
people. I have benefited greatly from the professional help and insightful feedback of Philippe
Aghion, David Laibson, Ulrike Malmendier, Sander Onderstal, Matthew Rabin, Sven Rady,
Monika Schnitzer, Stefan Trautmann, and Joachim Winter. Furthermore, I am indebted to
my colleagues Tobias B¨ ohm, Georg Gebhardt, Florian Heiß, Susanne Hoffmann, Karolina
Kaiser, Joachim Klein, and Anton Vasilev who provided a lot of impulse and feedback
in countless discussions. From the remaining faculty I want to thank Jan Bender, Rene
Cyranek, Matthias Fahn, Nico Klein, Sandra Ludwig, Elisabeth Meyer, Julius Pahlke, Felix
Reinshagen, Ludwig Reßner, Linda Rousova, Nicolas Sauter, Christina Straßmair, Martin
Watzinger, and Hans Zenger for their valuable input. Matthias Dischinger deserves a special
place for all those vivid debates and his encouragement, motivation, and helpful comments
and suggestions. I was lucky to have colleagues whom I also count to my closest friends.Acknowledgements II
It has been an honor to belong to the Munich Graduate School of Economics and I also
gratefully acknowledge the financial support granted by the German Research Foundation
(DFG) that supported my research in various ways and enabled me to attend several
international conferences and workshops.
I also owe gratitude to Silke Englmaier, Brigitte Gebhard, and Irmgard von der Herberg for
their indispensable and hearty help in handling all kinds of administrative issues.
For the individual papers I owe gratitude to numerous people.
For Does Bidding for Complex Goods Reflect All Relevant Information? Field Evidence
From Online Gaming, the second chapter of this dissertation, which is joint work with
Florian Englmaier, we are indebted to Hattrick Ltd. for their cooperation and giving us the
opportunity to conduct this project. We are especially obliged to Ron Brandes for his great
support, interest, and valuable hints and to Siegfried Muller¨ for helping us to establish this
contact. We thank Jan Bender, Tobias B¨ ohm, Matthias Dischinger, Florian Heiß, Ulrike
Malmendier, Klaus Schmidt, Stefan Trautmann, Joachim Winter, and seminar participants
at the Munich Research Workshop “Empirical Economics”, the Annual Meeting of the EEA
2008 in Milan, and the conference Economics and Psychology of Football 2008 in Innsbruck
for their comments and suggestions. Very special thanks go to Hans Zenger for inspiration.
For Determinants and Effects of Reserve Prices in Hattrick Auctions, the third chapter
of this dissertation, which is joint work with Florian Englmaier, we thank Tobias B¨ ohm,
Matthias Dischinger, Stefan Trautmann, and the participants at the Research Workshop
“Empirical Economics” in Munich and at the IMEBE 2009 in Granada, and two anonymous
referees for their helpful comments and suggestions. Ines Helm provided excellent research
assistance. An earlier version of this paper is circulated as CESifo Working Paper No. 2374
under the title Reserve Price Formation in Online Auctions.
For The Evaluation of Complex Goods - Evidence From Online Car Sales, the fourth chapter
of this dissertation, which is also joint work with Florian Englmaier, we thank Matthias
Dischinger and Klaus Schmidt for their helpful comments and suggestions. We are especially
grateful to Anton Vasilev for his great support with the dataset and his valuable feedback.
For Strategic Seller Actions in Auctions with Asymmetric Bidders, the fifth chapter of this
dissertation, I am deeply indebted to Florian Englmaier, Ray Rees, Klaus Schmidt, and
Monika Schnitzer. Furthermore I benefited from comments by Tobias B¨ ohm, Matthias
Dischinger, Susanne Hoffmann, Elisabeth Meyer, and the participants at the Theory
Workshop in at the University of Munich.Acknowledgements III
Most importantly, I am deeply indebted to my parents, Katharina and Gun¨ ther Schm¨ oller,
my family, and my friends for their inexhaustible love and support, their motivation and
trust in my decisions.
Arno R. Schm¨ oller
Munich, September 2009Contents
1 Introduction 1
2 Does Bidding for Complex Goods Reflect All Relevant Information?
Field Evidence From Online Gaming 7
2.1 Introduction .................................... 7
2.2 Institutional Background and Sample Selection................. 12
2.2.1 Background on the Game and its Mechanics .............. 12
2.2.2 Transactions: The Transfer Market ................... 14
2.2.3 Goods: The Virtual Players ....................... 16
2.2.4 Sample Selection ............................. 18
2.3 Data Description ................................. 20
2.4 Empirical Analysis ................................ 23
2.4.1 Estimation Model 23
2.4.2 Multivariate Regression Results ..................... 27
2.4.3 Robustness of Results .......................... 30
2.5 Possible Explanations for the Birthday Effect ................. 37
2.5.1 Search Costs 38
2.5.2 Other Explanations - Heuristic Decision Making............ 46
2.6 Discussion and Conclusion ............................ 46
2.7 Appendix ..................................... 50
2.7.1 Comparing Estimates Across Samples.................. 50
2.7.2 Additional Tables and Figures ...................... 51Contents V
3 Determinants and Effects of Reserve Prices in Hattrick Auctions 56
3.1 Introduction .................................... 56
3.2 Data Description ................................. 61
3.2.1 Institutional Background about Hattrick ............... 61
3.2.2 Goods: The Virtual Players ....................... 62
3.2.3 Transactions: The Transfer Market ................... 65
3.2.4 Sample Selection and Data Description ................. 66
3.3 Analysis and Results ............................... 69
3.3.1 Estimation Model and Predictions.................... 70
3.3.2 Results................................... 73
3.4 Suboptimal Reserve Price and Foregone Revenue ............... 83
3.4.1 Estimation of the Optimal Reserve Price ................ 83
3.4.2 Expected Revenue at Optimal and Actual Reserve Prices ....... 88
3.5 Conclusion..................................... 91
3.6 Appendix 93
4 The Evaluation of Complex Goods - Evidence From Online Car Sales 96
4.1 Introduction .................................... 96
4.2 Data Description ................................. 100
4.2.1 Institutional Background......................... 100
4.2.2 Sample selection ............................. 103
4.2.3 Data description 105
4.3 Empirical Analysis ................................ 109
4.3.1 Estimation Model and Predictions.................... 109
4.3.2 Hedonic Regression Results ....................... 112
4.3.3 Robustness of Results .......................... 116
4.4 Discussion and Conclusion ............................ 120
4.5 Appendix ..................................... 123Contents VI
5 Strategic Seller Actions in Auctions with Asymmetric Bidders 128
5.1 Introduction .................................... 128
5.2 Model Setting and Effect of Asymmetries.................... 131
5.3 Scenario I: A Simple Model of Seller Interference................ 136
5.3.1 A Cake of Size x to Distribute...................... 137
5.3.2 A Real World Application ........................ 142
5.4 Scenario II: Bidders with Diverging Tastes ................... 144
5.5 Conclusion..................................... 149
5.6 Appendix 152
5.6.1 Proofs and calculations.......................... 152
5.6.2 Simulations with Truncated Normal Distributions ........... 155
References 166
List of Figures 168