Essays on economics of network industries [Elektronische Ressource] : mobile telephony / vorgelegt von Lukasz Grzybowski

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Essays on Economics of NetworkIndustries:Mobile TelephonyInaugural-Dissertationzur Erlangung des GradesDoctor oeconomiae publicae (Dr. oec. publ.)an der Ludwig-Maximilians-Universit at Munc hen2005vorgelegt vonLukasz GrzybowskiReferent: Professor Stefan Mittnik, Ph.D.Korreferent: Dietmar Harho , Ph.D.Promotionsabschlussberatung: 13. Juli 2005AcknowledgementsFirst and foremost, I would like to thank Toker Doganoglu, for his continued encourage-ment in my research. Throughout the last few years, Toker has always been availablefor me with his excellent advice. He always pushed me to strive for good quality re-search. We wrote two chapters of this dissertation jointly. I will be always indebted tohim for everything and not just in this area.I would like also to thank my supervisor Professor Stefan Mittnik for his support.Because of him, I was able to continue my economic education at the universities inKiel and Munich. I am grateful to Professors Dietmar Harho and Joachim Winter fortheir willingness to participate in my dissertation committee.Thanks also to Professor Gerd Hansen and other employees at the Departmentof Statistics and Econometrics at the University of Kiel for an unforgettable friendlyworking atmosphere, and Farid Toubal for his support and the great times we spenttogether. I am grateful to Olivier Godard, Matthias Deschryvere and other friends Igot to know at the University of Kiel.

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Essays on Economics of Network
Industries:
Mobile Telephony
Inaugural-Dissertation
zur Erlangung des Grades
Doctor oeconomiae publicae (Dr. oec. publ.)
an der Ludwig-Maximilians-Universit at Munc hen
2005
vorgelegt von
Lukasz Grzybowski
Referent: Professor Stefan Mittnik, Ph.D.
Korreferent: Dietmar Harho , Ph.D.
Promotionsabschlussberatung: 13. Juli 2005Acknowledgements
First and foremost, I would like to thank Toker Doganoglu, for his continued encourage-
ment in my research. Throughout the last few years, Toker has always been available
for me with his excellent advice. He always pushed me to strive for good quality re-
search. We wrote two chapters of this dissertation jointly. I will be always indebted to
him for everything and not just in this area.
I would like also to thank my supervisor Professor Stefan Mittnik for his support.
Because of him, I was able to continue my economic education at the universities in
Kiel and Munich. I am grateful to Professors Dietmar Harho and Joachim Winter for
their willingness to participate in my dissertation committee.
Thanks also to Professor Gerd Hansen and other employees at the Department
of Statistics and Econometrics at the University of Kiel for an unforgettable friendly
working atmosphere, and Farid Toubal for his support and the great times we spent
together. I am grateful to Olivier Godard, Matthias Deschryvere and other friends I
got to know at the University of Kiel.
I would like to thank the Munich Graduate School of Economics for the opportunity
to nalize my dissertation in Munich. I am indebted to my friends at the Center of
Information and Network Economics, Martin Reichhuber, Daniel Cerquera and Katha-
rina Sailer for all the study and things we did together. Professor Monika Schnitzer
deserves a special mention for encouraging me to apply for the Marie Curie Fellowship.
I am grateful to Professor Marc Ivaldi and Professor Bruno Jullien for giving me
the opportunity to participate in the graduate program at GREMAQ at the Universite
Toulouse 1. It was a stimulating experience.
I am indebted to all the institutions which nanced my education, in particularii
the Volkswagen Stiftung for nancing my research at the Center for Information and
Network Economics and Deutsche Forschungsgemeinschaft, which supported my ed-
ucation in Munich. I am grateful to the European Commission for the Marie Curie
Fellowship I received for my stay at the Universitat Pompeu Fabra in Barcelona and
to GREMAQ for supporting my stay at the Universite Toulouse 1.
The Volkswagen Stiftung and the Munich Graduate School of Economics supported
my participation in numerous excellent workshops and conferences: 29th EARIE Con-
ference in Madrid 2002, 30th EARIE Conference in Helsinki 2003, Summer School
on Industrial Dynamics in Cargese 2003, 2nd International Industrial Organization
Conference in Chicago 2004, 19th Annual Congress of the EEA in Madrid 2004, 7th
Workshop on Economics of Information and Network Economics in Kloster Seeon 2004
and European Doctorate Group in Economics Jamboree in Dublin 2004. I would like to
thank participants at these events and those at the seminars at the University of Kiel,
University of Munich, Universitat Pompeu Fabra in Barcelona and IDEI in Toulouse
for helpful comments.
Most important, I would like to thank my parents for their faith in me, which I
often lack. Without them I would not have been able to nalize this work.Contents
Acknowledgements i
1 Introduction 1
2 Dynamic Duopoly Competition with Switching Costs and Network
Externalities 7
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 The Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.3 The Two-Period Game . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.3.1 The Second Period . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.3.2 The First Period . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.3.3 The Monotone Comparative Statics . . . . . . . . . . . . . . . . 27
2.3.4 The Case without Rigid Consumers . . . . . . . . . . . . . . . . 31
2.3.5 Switching Taxes: A Policy Suggestion . . . . . . . . . . . . . . 32
2.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.5 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3 Estimating Network E ects in Mobile Telephony in Germany 46
3.1 Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.2 Mobile Telephony in Germany . . . . . . . . . . . . . . . . . . . . . . . 51
3.2.1 Development of the Industry . . . . . . . . . . . . . . . . . . . . 51
3.2.2 Market Structure . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.3 Empirical Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54iv
3.3.1 Network E ects in Mobile Telephony . . . . . . . . . . . . . . . 56
3.4 The Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.4.1 Instrumental Variables . . . . . . . . . . . . . . . . . . . . . . . 59
3.5 Estimation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.7 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
4 Estimating Switching Costs in Mobile Telephony in the UK 67
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
4.2 Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.3 Mobile Telephony in the UK . . . . . . . . . . . . . . . . . . . . . . . . 71
4.4 Empirical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.4.1 Estimation Methodology . . . . . . . . . . . . . . . . . . . . . . 72
4.4.2 The Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
4.4.3 Choice Determinants . . . . . . . . . . . . . . . . . . . . . . . . 77
4.5 Estimation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
4.5.1 MNL and Mixed Logit . . . . . . . . . . . . . . . . . . . . . . . 79
4.5.2 Logistic Regression . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.7 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5 The Competitiveness of Mobile Telephony across the EU 89
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
5.2 Mobile services in the European Union . . . . . . . . . . . . . . . . . . 93
5.2.1 Development of the Mobile Industry . . . . . . . . . . . . . . . 93
5.2.2 Regulation of the Mobile Industry . . . . . . . . . . . . . . . . . 94
5.2.3 Prices of Mobile Services . . . . . . . . . . . . . . . . . . . . . . 97
5.2.4 Mode of Competition . . . . . . . . . . . . . . . . . . . . . . . . 99
5.3 Empirical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
5.3.1 The Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
5.3.2 The Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103v
5.3.3 Marginal Cost and Markup . . . . . . . . . . . . . . . . . . . . 105
5.3.4 The Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
5.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
5.4.1 The Reduced Form . . . . . . . . . . . . . . . . . . . . . . . . . 109
5.4.2 The Structural Form . . . . . . . . . . . . . . . . . . . . . . . . 113
5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
5.6 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
Bibliography 133Chapter 1
Introduction
During the last two decades, network industries have been going through a tremendous
transformation. Many countries worldwide started to liberalize traditionally monop-
olized network industries, such as telecommunications, electricity, railways and the
airline industry. Technological progress stimulated the development of new industries
and products, a decline in production costs and a rise in quality. New technologies, such
as personal computers, the Internet, mobile telephony, CD players and many others
experienced dramatic growth rates. For instance, at the end of 2004, about 83% of EU
citizens were connected to mobile telephone networks, just one decade after the startup
of digital cellular services. Also Internet penetration in many countries worldwide has
exceeded 60% of households within one decade.
This transformation process and the establishment of new industries have a critical
impact on lifestyle, working methods and the economy as a whole, through the rising
share in GDP and the creation of new jobs. It is extremely important to understand
the mechanisms, which determine the competition and consumers’ behavior in network
industries. In this way, an appropriate support could be provided for the regulatory and
competition policy, which should facilitate the creation of competitive and innovative
network industries. The key determinants of equilibrium outcomes in many network
industries, such as computers, the Internet and telecommunications, are network e ects
and consumer switching costs.
Network e ects and switching costs introduce di erences in the nature of compe-Introduction 2
tition, such as ’competition for the market’ or ’life-cycle competition’, as compared to
traditional industries. When switching costs are present, rms enjoy ex post market
power over their own consumers. Network e ects extend this power to future genera-
tions of buyers. Eventually, socially ine cien t market outcomes are possible, such as
unreasonable high prices, high industry concentration, entry barriers, standardization
on inferior technology. Thus, switching costs and network e ects have been a central
issue in many antitrust cases, for instance, in the US and the European Microsoft
case. The regulatory and competition policy must be appropriately adjusted in or-
der to deal with network technologies, where the dynamic perspective of competition
becomes critical for the nal assessment. Apart from theoretical justi cations, there
is also a crucial role of empirical studies, which may provide decisive arguments on
whether or not policy intervention is needed.
There is a large body of theoretical literature on switching costs and network e ects.
Their impacts on consumer choice and competition are well known (see Farrell and
Klemperer (2004)). However, there are still some interesting questions, which may be
addressed by economic theory. Empirical research is even more in demand. Network
externalities and switching costs in the mobile telecommunications industry are the
key focus of this dissertation. In this chapter, I shortly set out the contributions of
this dissertation to the literature on switching costs and network externalities. Each
subsequent chapter includes a detailed motivation and a review of related literature.
One should note, that network externalities have no dynamic consequences when
switching costs are nil. In such a case, it is completely optimal for consumers to be
myopic, as they can switch between brands as they please in every period. However,
all existing dynamic models of network e ects presume lock-in, that is su cien tly
high switching costs, which prevent consumers from switching between brands. It is
curious whether parallels drawn in the literature between the results of models with
switching costs and those with network e ects are due to genuine similarity between
switching costs and network e ects, or are just an artifact of presumption of lock-in
in network e ects models. In Chapter 2, written jointly with Toker Doganoglu, we
conduct a theoretical analysis of competition between network technologies. We buildIntroduction 3
on Klemperer (1987) and analyze competition in a two-period di eren tiated-products
duopoly in the presence of both switching costs and network externalities. We show
that they have opposite implications on the demand. While the former reduces demand
elasticities, the latter increases them. Increases in marginal network bene ts imply
lower prices in both periods while the e ects of switching costs are ambiguous. When
network e ects are strong, and switching costs are moderate, prices in both periods
may be lower than those in a market without network e ects and switching costs.
Moreover, we show that the rst period prices are quadratic-convex functions of the
level of switching costs, therefore for certain parameter values increasing switching costs
may reduce equilibrium prices. This point is very important, as the common message
in the literature about fully dynamic models is that switching costs unambiguously
increase steady state prices.
Usually, the theoretical results may be used only as logical arguments for the policy
design. In many cases the theory provides ambiguous results, which depend on para-
meter values. For instance, in the model mentioned above, the levels of equilibrium
prices depend on the magnitude of switching costs and network externalities. This
emphasizes the importance of empirical studies in support for the theory. In the fol-
lowing chapters, I carry out three empirical analyzes of mobile telephony to identify
and quantify the determinants of competition and consumers’ choices.
In Chapter 3, also written jointly with Toker Doganoglu, we analyze the impact
of network e ects on the di usion of mobile services in Germany using monthly data
from January 1998 to June 2003. We use a random utility framework, discussed com-
prehensively in Anderson, de Palma and Thisse (1992) and Berry (1994), to estimate
demands for mobile services provided by competing network operators. In the ana-
lyzed period, we observe the explosive growth in the subscriber base and the rather
moderate decrease in prices. Our conjecture is that prices alone cannot account for
such rapid di usion. We explore the possible contribution of network e ects to indus-
try growth. In the estimation, we use publicly available market share data and price
indices generated from data that we have collected. Our results suggest that network
e ects played a signi can t role in the di usion of mobile services in Germany. In theIntroduction 4
absence of network e ects, if prices remained as observed, the penetration of mobiles
could be lower by at least 50%. Current penetration levels could be reached without
network e ects only if prices were drastically lower. Furthermore, assuming that ob-
served prices are the result of pure strategy Nash equilibrium, we compute marginal
costs and markups. The Lerner index for all network operators increased over time
from about 13% in January 1998 to about 30% in June 2003. This increase is due to
the fact that the margins remained almost constant while the prices decreased.
This analysis required collecting a unique database on pricing mobile services in
Germany. We use monthly price listings published in telecommunications magazines
and on the Internet, which include all tari s of network operators and independent
service providers in the time period January 1998 { June 2003. This database could
be potentially used for further studies, such as an analysis of welfare e ects from entry
to mobile telephony or a study of the pricing strategies of mobile service providers.
Chapter 3 provides some information which may be helpful for policy design. The
extremely high cost of licences in the UMTS auctions provoked a debate on the ability of
rms to cover sunk costs and make further investments in consumer acquisition. As the
widespread use of 3G technology is an important social objective, it is crucial to know
to what extend the di usion of 3G technology could be stimulated by network e ects.
Thus, the knowledge of price elasticities and network bene ts in the 2G telephony
could be some basis for projections onto 3G technology.
Chapter 4 presents an empirical analysis of switching costs in mobile telephony in
the UK. The presence of switching costs may have negative consequences on social
welfare because rms which have large market shares have incentives to charge higher
prices and exploit locked-in consumers rather than compete for new ones. Therefore, it
is important to provide measurements of switching costs. The empirical literature on
switching costs is scarce. This is due to the lack of appropriate detailed data sets on
individual choices. In this study, I use survey data on British households to estimate
the magnitude of switching costs in mobile telecommunications industry. I employ the
random utility framework, as developed by McFadden (1974). I estimate multinominal
and mixed logit models to identify state dependence in the choices of network opera-