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The Impact of the Philippine ISP Duopoly on Mobile
Broadband Adoption
March 13, 2017
Anton Vera
Department of Economics
Stanford University
Stanford, CA 94305
[email protected]
Under the direction of
Prof. Timothy Bresnahan
ABSTRACT
The Philippine telecommunications market is dominated by two firms. Despite this duopoly
structure, the country has been a fast adopter of mobile broadband and is home to one of the
largest connected populations in the world. This paper tests and provides evidence to confirm
the hypothesis that the Internet Service Provider (ISP) duopoly has not hindered Mobile
Broadband Adoption. Telecommunications market consolidation does not appear to have a
statistically significant effect on the Philippine’s rapid adoption of mobile broadband devices.
This paper then studies key innovations that may have allowed the Philippine market to
overcome the ISP duopoly and continue broadband adoption. Empirical analysis suggests that
the diffusion of foreign innovations is a significant driver of increased mobile broadband use.
Keywords: Philippines, Internet, Duopoly, Market Structure, Innovation, Mobile, Broadband
Acknowledgments: I am extremely indebted to my advisor, Professor Timothy Bresnahan, for
all his guidance and patience. I would also like to thank Marcelo Clerici-Arias for his in the
process of developing the thesis and Mark Tendall for his continued support as a major-adviser.
I am also grateful for my family and friends. Finally, and most importantly, I’m thankful to
Alyssa Elasin, whose love and support makes good broadband always worth having.
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Contents 1 – Introduction .............................................................................................................................................................................. 2
2 – Literature Review ..................................................................................................................................................................... 6
2.1 – Contextualizing National Technological Development .............................................................................................. 6
2.2 – Market Leading Firms and Innovation ......................................................................................................................... 7
2.2.1 – The Slow Adoption of New Technology ............................................................................................................... 8
2.2.2 – Defensive Behavior when Responding to Innovation ......................................................................................... 8
2.3 – Determinants of Mobile Broadband Adoption ............................................................................................................ 9
3 – Background: Mobile Broadband in the Philippines .......................................................................................................... 12
3.1 – A Dramatically Growing Number of Users, driven by Mobile ................................................................................ 12
3.2 – Slow but Expensive Connections ................................................................................................................................. 15
3.3 – The Data Duopoly .......................................................................................................................................................... 17
4 – Measuring the Data Duopoly’s Impact ............................................................................................................................... 20
4.1 – Data .................................................................................................................................................................................. 20
4.1.1 – The Observed Period ............................................................................................................................................. 20
4.1.2 – The Dependent Variable ........................................................................................................................................ 21
4.1.3 – Independent Explanatory Variables .................................................................................................................... 22
4.1.4 – Independent Control Variables ............................................................................................................................ 26
4.1.5 – Summary Statistics ................................................................................................................................................. 29
4.2 – Empirical Strategy .......................................................................................................................................................... 30
4.3 – Results.............................................................................................................................................................................. 32
4.4 – Discussion ....................................................................................................................................................................... 34
5 – Comparing Foreign and Domestic Innovations ................................................................................................................. 37
5.1 Data ..................................................................................................................................................................................... 37
5.1.1 – Independent Explanatory Variables .................................................................................................................... 37
5.1.2 – Independent Control Variables ............................................................................................................................ 43
5.2 – Empirical Strategy .......................................................................................................................................................... 44
5.3 – Results.............................................................................................................................................................................. 46
5.4 – Discussion ....................................................................................................................................................................... 47
5.4.1 – Adoption driven by Foreign Innovation ............................................................................................................. 47
5.4.2 – Why domestic innovation falls short ................................................................................................................... 49
6 – Discussion of Overall Results ............................................................................................................................................... 50
7 – Conclusion .............................................................................................................................................................................. 52
8 – Bibliography ........................................................................................................................................................................... 55
9 – Appendix ................................................................................................................................................................................ 57
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1 – Introduction
Sustained adoption of mobile broadband services is an extremely important
driver of economic growth. This is particularly true in developing nations that lack the
infrastructure to support traditional wired connections and are consequently heavily
dependent on mobile devices. By 2020, some estimate that online connections will
provide the Asia-Pacific region alone with up to 35 million new jobs, $1.2 trillion in
economic output, and 50,000 petabytes of data (Almqvist, Stewart, Reichi, Rangelova
2015, p.37). Given this significant impact, it is important to study the factors that
facilitate the adoption of mobile broadband devices.
One factor that heavily influences mobile broadband adoption is a country’s
internet service provider (ISP) market. Uncompetitive ISP markets have often been cited
as the culprit of poor broadband adoption due to some combination of underwhelming
connection speeds, disproportionately high service prices, and unreliable network
coverage. For example, a lack of competition in the UK ISP market has allowed carriers
like BT to overlook certain network standards, causing broadband outages that left
thousands in the UK without internet connections (Hollinger 2016, p.1). Similarly, some
regions in the US have suffered from disparities between advertised and actual
broadband speeds due to a lack of competition to hold ISPs accountable for their
performance (Romero, 2016, p.1). The apparent negative impact of highly consolidated
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ISP markets is only becoming more pronounced as the need for high quality internet
grows.
An apparent exception to the abovementioned trend is the Philippines, which
has a high mobile broadband adoption rate despite being home to an ISP duopoly. A
large, rapidly growing mobile broadband population of Filipinos is extremely curious
given the lack of competition in the ISP space. It is important to study the Philippines’
anomalous case as it may lead to greater insight on other factors that drive internet
adoption and facilitate efforts to increase internet development in less developed
nations. East Asian ISPs operating in uncompetitive markets are typically stubborn in
changing their practices as they can maintain profitability without the expense of
improving broadband services (Ono 2005, p.11). This lack of action by uncompetitive
ISPs can propagate expensive, low quality internet that is a notable headwind for
mobile broadband adoption and related economic growth. The OECD estimates that
continued mobile broadband access contributed $800 to annual Philippine household
income in 2015, a 16% increase (Agonoy 2015, p.1). Identifying and amplifying the
factors behind the Philippines’ broadband adoption would produce a multitude of
economic benefits throughout different sectors of mobile-dependent nations. This leads
to the paper’s main research questions: To what extent has an uncompetitive ISP market
affected mobile broadband adoption in the Philippines? This paper’s central contribution is to
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analyze whether an uncompetitive ISP market can be overcome as a culprit for poor
mobile connectivity.
The paper begins by describing the Philippine internet market – mobile and
wired – and then elaborates on the two duopolies that dominate it. This section is then
followed by a literature review that examines existing scholarship on ISP competition
and mobile broadband adoption. Key ideas, important to the subsequent empirical
investigation, are highlighted.
This study features a two-pronged analysis that attempts to answer the main
research question. First, the investigation tests the hypothesis that the Philippine ISP
duopoly has not had a material effect on mobile broadband adoption. This is done
through observing how the number of mobile broadband devices has been affected by:
the increasing market concentration in the ISP space; the investment of duopoly
companies; and, the quality of the duopoly’s network infrastructure. Findings indicate
that mobile broadband adoption is not markedly affected by any of the three listed
factors. Reasons behind this result are discussed and indicate that Philippine mobile
broadband adoption is propagated by a factor external to the ISP market.
Next, the paper analyzes other innovations in broadband use, distribution, and
network quality that may have allowed the Philippines to overcome the consequences
of the duopoly ISP market. This section analyzes both domestic changes spearheaded
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by the duopoly ISPs, such as the introduction of faster network equipment, and foreign
innovations, like the introduction of cheaper devices and social media. Interestingly, the
results indicate that foreign innovations, particularly social media, have a significant
effect on mobile broadband adoption while domestic factors do not. External innovation
seems to have a far greater influence of mobile adoption than any domestic actions
taken by the duopoly ISPs. The study concludes by assessing both the implications and
limitations of the empirical study.
The paper’s overall conclusion is that high levels of interest in external
innovations, such as social media and foreign phone brands, have driven mobile
broadband adoption. This result suggests that policymakers and regulators can take
measures to encourage the diffusion of broadband technology. Furthermore, the paper
sheds light on the role an uncompetitive ISP market, like the duopoly in the Philippines,
plays in mobile broadband diffusion. The presence of an ISP duopoly appears not to
have a statistically significant effect, positive or negative, on Philippine mobile
broadband adoption. This suggest that measures can be taken within the duopoly
structure to encourage greater mobile innovation.
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2 – Literature Review
This paper builds off previous scholarship in three main areas – contextualizing
technological development in a nation; the determinants of broadband adoption; and
the behavior of market leading firms with respect to innovation. Ideas from studies in
each of these three categories will be described and then applied to the topic of mobile
broadband in the Philippines.
2.1 – Contextualizing National Technological Development
A significant challenge in studying new technology in a developing country, like
Philippine broadband, is interpreting the available data. Information on broadband is
scarce since the technology is new and the Philippines does not keep records as
efficiently as more developed counterparts. Therefore, the area of contextualizing
national technological development becomes relevant. Information other than the
empirical data collected is necessary to adequately analyze the study’s observations and
determine which factors affected mobile broadband adoption.
Paul Romer (1996), through using industrial growth in 19th Century America as an
example, explores the roles of economic history and new growth theory in explaining
national technological development. Romer determines that historical and theoretical
evidence are complementary in the study of technological change. He uses
socioeconomic and historical sources to augment his data and conclude that America’s
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abundance in natural resources and large population were primary catalysts for 19th
Century industrialization.
Romer’s assertion that a hybrid of history and theoretical evidence is optimal in
analyzing technological change or is useful to the mobile broadband question.
Combining historical events provides context to the datasets being analyzed, especially
if the data is especially limited. For example, the paper relies on very specific measures
of market concentration and ISP behavior. These measures are only fully interpreted
when combined with information on company activity and historical consumer
behavior. However, the paper differs from Romer’s study in that it is analyzing an
ongoing process. 19th Century industrialization was long finished by the time Romer
had conducted his analysis; conversely, mobile broadband adoption continues today.
This imposes several limitations on the paper’s interpretations of the empirical results,
which are discussed later.
2.2 – Market Leading Firms and Innovation
One of the major focuses of the investigation is to what extent the Philippine ISP
duopoly has affected the adoption of mobile broadband. Therefore, it is important to
understand how market leaders, even in fields other than telecommunications, react to
new industry innovations – this might help explain Philippine ISPs’ approach to mobile
broadband. There are two particularly relevant traits – large firm’s slow adoption of
new technology and competition-reducing inclinations.
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2.2.1 – The Slow Adoption of New Technology
Shannon Oster (1982) underscores how large firms are generally slow to adopt
new technology in her analysis of the US steel industry and its foreign counterparts.
Oster concludes that larger steel companies were slower in adopting innovations than
smaller firms. She shows this through utilizing industry and historical pricing data,
which revealed that smaller firms were more compelled to take advantage of the cost
savings of certain innovations (1982, p. 49).
Oster’s assertion that size is a determinant of technological adoption is relevant to
the case of mobile broadband and the Philippine ISP duopoly. The suggestion that firms
in dominant positions become more complacent and less willing to adopt new
innovations help explain the results of the empirical study. However, there is a danger
in tying one’s interpretation of firm behavior so closely to size. Oster assumes that
production functions stayed stagnant from 1945 to the mid-1970s. Both of Oster’s
assumptions are dangerous, especially in a rapidly changing field like mobile
broadband. Furthermore, this study differs from Oster’s because it also observes other
influences on technological adoption besides firm behavior.
2.2.2 – Defensive Behavior when Responding to Innovation
Gilbert and Newberry (1984) highlight how large firms are generally defensive
towards innovation in their study of monopolies’ uses of practices such as preemptive
patenting to maintain market leadership. The authors created a model, showing the
conditions necessary for a monopoly, duopoly, or oligopoly firm to circumvent future
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competition with high barriers to entry. The model states that a large firm can create
significant barriers to entry if it has significant foresight, a mechanism to prevent
competitor entry, and first mover advantages (Gilbert, Newberry 1984, p.253).
Philippine ISPs possess these advantages. Thus, Gilbert and Newberry’s model
provides an excellent framework for studying the barriers to entry that protect the ISP
duopoly and allow it to thrive without promoting mobile broadband innovation and
adoption.
2.3 – Determinants of Mobile Broadband Adoption
The final area of literature to be analyzed is mobile broadband adoption.
Numerous papers have focused on studying the determinants that lead to widespread
broadband adoption but have generally centered on the United States and other
developed countries. Nevertheless, the conclusions drawn from these studies prove
useful in several ways throughout the subsequent investigation.
Sobee Shinohara, Hiroyuki Morikawa, and Masatugu Tsuji (2014) analyze the
factors that affect mobile broadband devices’ adoption in six developed countries. The
authors conclude that several factors including income, supporting infrastructure, and
ISP competition have material effects on mobile broadband’s diffusion.
There are obviously several key insights from Shinohara, Morikawa, and Tuji’s
work. First, the authors use mobile broadband device penetration as the dependent
variable that anchors their investigation. The first regression used in this investigation
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does the same thing since device penetration is the most accurate and accessible
measure of mobile broadband adoption. Another valuable contribution in “Empirical
Analysis of Mobile Broadband Adoption in Six Major Countries” is that it highlights
income and education as important factors in mobile broadband diffusion (Shinohara,
Morikawa, Tsujij 2014, p.10). These two factors are utilized as controls when the paper
tests the impact of the Philippine ISP duopoly on mobile broadband adoption.
However, there are some differences between this paper and Shinohara, Morikawa, and
Tuji’s work. First, the authors focus on multiple, developed countries that were
relatively early adopters of mobile broadband, giving them a larger dataset than the one
used in this study. The lack of data on Philippine broadband necessitates the second
regression performed, something not featured in Shinohara, Morikawa, and Tuji’s
work. Additionally, the authors do not seek to investigate one explanatory variable
unlike this paper, which focuses on the telecommunication market’s concentration.
David J. Yates, Grish J. Gulati, and Marco Marabelli (2015) are among the few to
focus on mobile broadband adoption in developing countries, although not in the
Philippines.The authors conclude that developing countries, when controlled for
income, are more likely to adopt mobile broadband when there is competition within
the telecommunication industry and a stable government (Yates, Gulati, Marabelli 2015,
p. 16). The paper follows many of the conventions used by Shinohara, Morikawa, and
Tuji but adds another control – government stability. The potential impact of political
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stability is used as a control in the Philippine investigation to make the first regression
more accurate. A key difference is that Yates, Gulati, and Marabelli’s work is inherently
comparative while this paper only focuses on the Philippines.
Michele Cincera, Lauriane Dewulf, and Antonio Estache (2015) provide another
important control in the investigation. The authors note that there is a clear substitution
effect between fixed and mobile broadband. Individuals are more likely to switch to
mobile broadband as fixed broadband quality diminishes and higher quality mobile
connectivity is achieved (Cincera, Dewulf, Estache 2015, p.14). This is substitution effect
is later used as a control when the paper tests the impact of the ISP duopoly on mobile
broadband adoption to ensure that the tendency to transition from fixed to mobile
connections is accounted for.
Chatchai Kongaut and Erik Bohlin (2015) provide one final insight that is
instructive in this investigation. The authors differ from the others mentioned above in
that they focus on the impact of external innovations like social media, video, and
messaging as well as domestic factors like income (Kongaut, Bohlin 2015, 750). The
authors conclude that social media, video, and online shopping affect mobile
broadband adoption in varying degrees. This analysis informs the paper’s second
regression, which focuses on how domestic and international innovations have
impacted Philippine mobile broadband.
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3 – Background: Mobile Broadband in the Philippines Mobile broadband in the Philippines can be characterized with three main
attributes – a rapidly growing number of users, especially compared to wired internet
users; slow but expensive service; and, an ISP duopoly. Each aspect has significant
implications on the impact the ISP duopoly has on mobile broadband adoption and is
important to the empirical analysis performed in this paper.
3.1 – A Dramatically Growing Number of Users, driven by Mobile
The Philippines has experienced a dramatic growth in internet users over the past
decade as displayed in Figure 1. Growth since 2010 has been particularly notable – the
number of users from 2010 to 2016 nearly tripled from 24 million to 66 million. This
number is on par with developed nations such as Britain, France, and Germany (Tandeo
2015, p.6). This mushrooming demand is largely driven by mobile broadband.
The Philippines has largely adopted mobile devices at a far greater pace than
computers and laptops. This trend has only been exacerbated by the emergence of
mobile broadband – access to the internet no longer required a computer of wired
internet subscription, technologies that were never popular to begin with (Budde 2016,
p. 27). Figure 1 highlights the profound disparity between mobile and fixed broadband.
Mobile broadband is clearly the main thrust behind the growth of Philippine internet.
This is largely in-line with the observation that developing countries are generally
‘mobile-first’ when it comes to broadband adoption (Yates, Gulati, Marabelli 2015, p. 3).
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Further underscoring the importance of studying mobile broadband is the fact that
Filipinos use the internet at a high rate. Figure 2 indicates that Filipinos use the internet
more than most other Asian citizens. This highlights how the Philippines is somewhat
of an anomaly in that it boasts high mobile broadband usage within a duopoly market.
0
20
40
60
80
100
2011 2012 2013 2014 2015 2016 2017 2018 2019
Sub
scri
ber
s (m
illio
ns)
Philippine Internet Subscriptions
Fixed Broadband Mobile Broadband Total Internet
Figure 1 - This chart shows the number of internet subscribers in the Philippines
from 2011-2016 and the projected number of subscribers from 2017-2019. The
chart also breaks down these subscribers into mobile broadband and fixed (wired)
broadband users. This establishes that mobile broadband has consistently been
utilized at a higher rate than fixed broadband.
Budde 2016, p.24; Tandeo 2015, p.4
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The high usage internet usage seems to have translated to the adoption of the latest
innovations in mobile broadband, especially smartphones. As figure 3 shows, Filipino
smartphone usage growth has surpassed similar adoption in East Asia and in High
Adoption Nations like the United States (Budde, 2016 p. 28). The impact of smartphones
on mobile broadband adoption is discussed later in the second part of the investigation.
Tandeo 2015, p.4
Figure 2 - This graph shows the number of hours the average internet user in different
Asia Pacific countries spent online in 2015. The chart shows that Filipinos generally
spend a high amount of time online compared to citizens of neighboring countries.
This highlights how the Philippines is somewhat of an anomaly – it features high
internet usage within a duopoly market.
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3.2 – Slow but Expensive Connections
Despite high mobile adoption, the Philippines has notoriously bad internet
connections. The Ookla Speedtest survey ranked Philippine internet as the worst in
Asia, slower than nations with smaller internet populations like Pakistan and Myanmar
(ITU 2015, p.188). This indicates that ISPs provided internet services that adequately
services consumers.
0
10
20
30
40
50
60
70
80
Philippines High Adoption Nations East Asia
Smar
tph
on
e D
ata
Ave
rage
An
nu
al
Gro
wth
Rat
e (
20
08
-15
)
Philippine and Asia Smartphone Data Usage
Budde 2016, p. 29
Figure 3 - The figure shows a comparison between the annual growth rates of
smartphone data usage in the Philippines, High Adoption Nations, and East Asia.
This is measured by the average annual growth rate in amount of mobile data
consumed (measured in gigabytes) from the years 2008-2015. ‘High Adoption
Nations’ refer to a select group of countries with populations that widely use
mobile phones (over a 75% adoption rate). These include the US, UK, Germany,
and Japan. The chart shows that the Philippines has adopted smartphones at a
markedly rapid rate, highlighting how high mobile internet usage has translated
to the adoption of the latest innovations in mobile broadband.
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Compounding the slow speeds is the expensive broadband prices: $18.18/Mbps,
more than triple the $5.21/Mbps global average (ITU 2015, p.190). These prices and poor
services have not dulled the increase in mobile broadband adoption. Figure 4 shows
how the Philippines is amongst the slowest and most expensive globally.
A popular culprit for the paradox of slow connection speeds and comparatively
high prices is the existence of the Philippine ISP duopoly. However, the uncompetitive
market does not seem to have dulled mobile broadband adoption. Filipinos appear to
gain such high utilities from mobile connections that it is optimal for them to utilize
broadband even if is subpar and expensive. One limitation with using Philippine
0
5
10
15
20
25
30
0
5
10
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20
Philippines Vietnam Malaysia Cambodia Globalaverage A
vera
ge in
tern
et s
pee
d (
mb
ps)
Mo
nth
ly In
tern
et C
ost
($
/mp
bs)
Average monthly internet cost ($/mpbs) and speed (mbps)
Price Speed
ITU 2015, p.12
Figure 4 - This chart shows the average monthly internet cost, measured in $/mbps,
and the average internet speed, measured in mbps (megabytes per second), of the
Philippines, Vietnam, Malaysia, and Cambodia in 2015. Also included is a global
average of the two above-mentioned values. This includes the monthly internet
cost and speed of all UN member countries. Figure 4 shows how the Philippines
suffers from internet that is not only slow but expensive.
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broadband prices and cost is that the data recorded refers to prices of both mobile and
wired connections. Therefore, the investigation uses other measures to more effectively
capture the issues of poor connectivity and high prices but only for mobile devices.
3.3 – The Data Duopoly
One final area of background is a description of the Philippine ISP duopoly. The
totality of the Philippine telecommunications market – from traditional landline
telephones to broadband services – are operated by two firms, the Philippine Long
Distance Telephone Company (PLDT) and Globe Telecommunications (Globe). Both are
publicly traded companies owned by two of the largest conglomerates in the
Philippines. Figures 5 and 6 highlight how the two firms have become the two
preeminent ISPs over the past decade through a series of acquisitions, culminating in
2011 when the last independent ISP was bought out by Globe.
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This duopoly structure is largely viewed as a significant inhibitor of broadband
innovation and efficiency. The damaging paradox of high prices and low quality
broadband services has been amplified under the duopoly system. The paper’s central
0%
25%
50%
75%
100%
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Globe and PLDT Market Share of Philippine Broadband Market (%)
Globe Market Share PLDT Market Share
0%
50%
100%
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Globe and PLDT Market Share of Philippine Broadband Market (%)
Globe + PLDT Market Share
Globe purchases the last
non-duopoly ISP provider
Tandeo 2015, p.11
Figures 5 and 6 - Figures 5 and 6 show the gradual consolidation of the Philippine
broadband market into a duopoly from 2005-2015. Both graphs measure the market
shares of the two duopoly companies in the broadband industry. Market share is
calculated by dividing a company’s ISP and broadband service sales by the entire amount
of sales in the Philippine broadband market. Figure 5 shows Globe and PLDT’s market
shares separately while Figure 6 shows the two company’s combined market shares.
Figure 6 also notes 2011, the date when Globe purchased the last remaining non-
duopoly ISP. One can observe that the combined market share increases to 100% in 2012
and stays at that level, highlighting the creation of the current ISP duopoly.
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study will try to determine how the ISP market consolidation that created duopoly and
its negative effects impacted Philippine mobile adoption.
Furthermore, knowledge of the ISP duopoly helps contextualize the results of this
paper’s empirical investigations. The duopoly’s impact, or lack thereof, on mobile
broadband adoption can potentially be explained by studying PLDT and Globe’s
historical behavior when it comes to innovation. Observed tendencies such as a lack of
incentives to innovate and an ability to maintain profitability prove to be useful in
explaining the paper’s final conclusions.
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4 – Measuring the Data Duopoly’s Impact
The first hypothesis the paper tests is the notion that that the ISP duopoly has not
had a material impact on rapid mobile broadband adoption in the Philippines. This will
be done by establishing whether the consolidation of the ISP market and the actions of
the duopoly companies have any statistically significant effect on Filipino mobile
broadband patterns.
4.1 – Data
The investigation uses data from two telecommunication focused surveys, the
BuddeComm “Philippine Telecom, Mobile, Bradband, and Digital Media” report and
the GSM Association (GSMA) “Philippine Telecom Market Data” report (2016).
Buddecomm is a telecommunications research and consultancy company while the
GSMA is a trade body that represents over 1,000 mobile operators worldwide.
4.1.1 – The Observed Period
Both the GSMA and BuddeComm began measuring Philippine mobile broadband
and telecommunications data in 2005 and have continued to do so annually. However,
the investigation’s dependent variable was only tracked from 2006. Therefore, each of
the variables described below fall in the period from 2006-2016. Each observation in the
investigation will include the dependent, explanatory, and control variables for a year
in the observed period.
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4.1.2 – The Dependent Variable
The dependent variable used is the mobile broadband penetration rate at a given t
(year from 2006-2016), denoted as Capablet. This number is the measure of all active
broadband capable mobile devices as a percentage of the entire Philippine population
as recorded by GSMA (2016). The rationale behind the calculation is that the act of
purchasing a device is a significant indication that a consumer is willing to adopt
mobile broadband services. Diffusion of mobile devices in the Philippine market
provides tangible evidence of changing preferences in broadband adoption. It would be
far more difficult to gauge adoption based on other measures like consumer surveys
because it may be difficult to come up with a definition for what constitutes a mobile
broadband ‘adopter’.
Previous studies of mobile broadband adoption like Shinohara, Morikawa, and
Tsuji’s utilized this as the measure of mobile adoption for several reasons (2014). Using
the raw number of mobile broadband capable phones does not account for the impact
of population growth on adoption. This is especially important in countries with large,
fast-growing, and relatively young populations like the Philippines. The penetration
rate allows one to capture the diffusion of mobile broadband relative to changes in
population.
Additionally, the mobile penetration rate avoids potentially problematic definition
issues associated with mobile broadband. Measuring adoption by using other attributes
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like Operating System is problematic because definitions of mobile connectivity can
differ depending on device manufacturer. Mobile broadband penetration is based on a
fixed term set by the International Telecommunications Union (ITU), which defines
mobile broadband capable phones as any mobile device capable of connecting to the
internet (2015, p. 3). Using a measurement based on the ITU definition allows devices of
different origins to be accounted for accurately.
4.1.3 – Independent Explanatory Variables
All independent variables used are lagged by one year relative to the corresponding
mobile broadband penetration rate. This due to the tendency of innovations, market
conditions, and socioeconomic factors to have “delayed… effects on mobile
broadband…. with respect to a given year” (Yates, Gulati, Marabelli 2015, p. 4). The
independent variables will now be explained.
The first regression analysis’ main purpose is to test the hypothesis that the ISP
duopoly does not have a material effect on mobile broadband adoption. Thus, two
characteristics of the ISP market need to be measured: increased market concentration
and overall efficiency in promoting mobile broadband adoption.
4.1.3.1 – The Herfindal-Hirschman index (HHI)
The Herfindahl-Hirschman index (HHI) related to the Philippine mobile broadband
market is used as one of the main explanatory variable related to market concentration.
HHI is a measure of market concentration calculated by squaring the market share of
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each firm in a market and then adding the resultant numbers together. The results can
range from 0, a perfectly competitive market, to 10,000, an absolute monopoly. The
index can also be displayed at a range of 0 to 1 by simply dividing all results by 10,000.
Markets with HHIs of 0.25 or higher are highly concentrated.
Figure 7 shows that Philippine broadband market has always been concentrated – it
has never had an HHI of less than 0.3. Furthermore, the Filipino broadband market’s
HHI has approached 0.5, the indicator of a perfect duopoly, since 2011, the year that the
last non-duopoly ISP was bought out (GSMA 2016, p. 12).
Year HHI 2005 0.32 2006 0.31 2007 0.29 2008 0.34 2009 0.39 2010 0.43 2011 0.56 2012 0.55 2013 0.52 2014 0.50 2015 0.50
HHI is an ideal indicator of market concentration because it focuses on firm size
relative to the industry it operates in. The Philippine broadband industry has
experienced swift overall growth over the last decade. However, the investigation is not
focused on overall market growth but firm consolidation. HHI captures how the two
Figure 7 GSMA 2016, p. 8
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duopoly firms increased their respective market shares amidst overall industry
expansion.
One frequent criticism of using HHI for telecommunications studies is that it does
not take geography into account when measuring a market. Previous studies have
struggled with HHI because different ISPs operated in different geographic markets
(Tandeo 2015, p. 5). This is not an issue for the Philippine duopoly because both Globe
and Smart operate across the entire country, are headquartered in the same city, and
directly compete in all regions. Another limitation of HHI is that it puts more weight on
larger firms and leaves out smaller companies because firms’ market share is used to
calculate the metric. This is not an issue for the Philippine broadband market since it
has historically been dominated by large firms, even before there was a duopoly.
4.1.3.2 – Capital Expenditure (CAPEX) to Revenue Ratio
The other explanatory variable used is the average Capital Expenditure (CAPEX) to
Revenue Ratio of the two duopoly ISPs, Globe and Smart. This is calculated by dividing
the companies’ mean Capital Expenditure by their mean Revenue in a year. The metric
is used to show how efficiently Philippine ISPs have promoted stable broadband
connections through investment in relevant equipment.
Capital Expenditure (CAPEX) refers to the funds used by a firm to acquire or
upgrade physical assets that help in the production of a good or the provision of a
service. In the case of the broadband industry, CAPEX refers to the creation or
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maintenance of structures and equipment that are necessary in providing stable
connections. The mobile broadband industry has historically required large amounts of
CAPEX– the combination of increased diffusion and demand for faster connections has
forced ISPs to spend more on equipment. In a rapidly developing broadband market
like the Philippines, ISPs must typically increase their CAPEX to accommodate higher
demand. Like all publicly listed companies, the two Filipino ISPs report their CAPEX
figures annually. However, CAPEX cannot be used by itself to highlight Philippine
ISPs’ investment in connection equipment as it does not take a firm’s economic
conditions into account.
Therefore, the CAPEX figure needs to be put into the context of an ISP’s financial
situation. This is done by comparing CAPEX to an ISP’s total revenue, all the funds
generated in a year for providing broadband services. The ratio contextualizes CAPEX
by pegging it to an ISP’s annual earnings.
The CAPEX to Revenue ratio highlights how aggressively an ISP invests in its
equipment and other capital assets. Figure 9 highlights this ratio from 2005-2015 (GSMA
2016, p. 8). This variable’s statistical significance on mobile broadband activity is an
indicator of how impactful the ISP duopoly’s investments are on mobile broadband
adoption. Ideally, increased CAPEX to Revenue levels should lead to more efficient
connections, which should translate into greater mobile broadband penetration.
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4.1.4 – Independent Control Variables
Three control variables shown to have an empirical link to mobile broadband
adoption by works mentioned in the literature review are included.
4.1.4.1 – Income measured by GNI per Capita
The first control variable is income, denoted as inc. Shinohara, Morikawa, and
Tuji’s work highlights how rising income has a positive effect on mobile broadband
adoption (2014, p. 12). Higher incomes translate to greater ability to buy a mobile device
and access to economic activities that benefit from broadband connections. Thus, the
potential impact income can have on mobile broadband penetration needs to be
accounted for.
Income is measured using GNI per capita. This is the dollar value of a country’s
annual income divided by its population. It is calculated through dividing the total
value of all resident activities by a country’s total population. GNI per Capita is
utilized instead of GDP to adjust for the large population of Filipinos who work abroad,
remit a cumulative annual average of $15 billion back home, and are the primary
Year CAPEX 2005 19.31 2006 19.39 2007 25.99 2008 28.32 2009 27.31 2010 18.08 2011 20.83 2012 26.77 2013 22.42 2014 25.45 2015 30.21
Figure 8 GSMA 2016, p. 12
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breadwinners of their families (Tandeo 2015, p. 17). Unlike GDP, GNI includes the
income paid into the country and excludes funds remitted out of the country. This
makes GNI per Capita more appropriate when controlling for Philippine income.
4.1.4.2 – Education measured by the UN Education Index
Another control variable is education, which was also found to have a positive
impact on mobile broadband adoption and is denoted as ed (Shinohara, Morikawa, Tuji
2014, p.12). Greater education typically leads to higher skilled jobs, which are more
likely to expose individuals to broadband connections. Furthermore, higher education
levels are also heavily correlated with greater income levels, which increase the ability
to purchase mobile broadband devices.
Education is measured by utilizing the UN education index, one of the human
development indices used to measure the standard of living in different countries. This
is calculated through a UN formula that utilizes the average citizen of a country’s mean
years of schooling and expected years of schooling. Other potential measures of
education such as government investment in public schools and college graduation
rates are harder to standardized – many local government offices and universities use
different academic measures.
4.1.4.3 – Political Stability, measured by the EIU Voice and Accountability Index
The next controlled variable used is a measure of political stability. Yates, Gulati,
and Marabelli observed that developing countries, controlled for income, are more
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likely to adopt mobile broadband when there is a stable government (2015, p. 16). This
is a particularly important control since the period being studied features two
Philippine presidential administrations and three legislative elections. Yates, Gulati,
and Marabelli used Unified Democracy Scores as the variable for political stability
(2015, p.16). Unfortunately, this metric is not available for certain years being studied.
As a substitute, the paper uses the Economist Intelligence Unit (EIU) Voice and
Accountability index. The EIU is a private research and analysis organization run by the
Economist Group. One of its focuses is identifying business opportunities in developing
countries, making it a useful source for information on the Philippines. The EIU Voice
and Accountability index is a measure of a country’s democratic stability, ability to
support a free market, and other political features. The metric takes in over 30 measures
of citizen satisfaction in fields such as freedom of expression, freedom of association,
and freedom to conduct business. The EIU Voice and Accountability index is ideal not
only because it has up-to-date information on the Philippines but because it focuses on
political stability in terms of economic development. The metric is denoted as v in the
study.
4.1.4.4 – Broadband Substitution Effect
A final controlled variable is a measure of the mobile broadband substitution
effect. Cincera, Lauriane, and Estache (2015) have indicated that one of the main
motivations for individuals to adopt mobile broadband is the inefficiency of a substitute
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service. For example, poor landline service in a region typically correlates with
increased mobile device penetration (Cincera, Lauriane, Estache 2015, p.13).
Given the Philippines’ high adoption rates, this factor must be accounted for in
the regression analysis. One of the chief harbingers of this effect is a declining fixed wire
service (Cincera, Lauriane, Estache 2015, p.11). Many of the functions of mobile
broadband are particularly useful for Filipinos who do not have access to wired
internet. Individuals without wired connections may be more willing to invest in a
mobile broadband device because they have no other method to take advantage of an
online service. Thus, the percentage of working broadband wires, denoted as work, is
used. A low percentage of working broadband wires leads to unreliable fixed
connections and slow speeds. One would expect this variable to have an inverse
relationship with mobile broadband adoption – greater wired service failures should
lead to greater mobile penetration.
4.1.5 – Summary Statistics
Below are the summary statistics for the dependent variable, capable, and the
independent variables – hhi, capex, inc, ed, v, and work. All observations of capable occur
from 2006-2016 while all independent variables are lagged by one year and occur from
2005-2015.
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4.2 – Empirical Strategy
To estimate the impact of the Philippine ISP duopoly on mobile broadband
adoption, the paper will observe changes in the Philippine broadband market’s HHI
and ISP’s CAPEX/Revenue ratio. If HHI changes make statistically significant effects on
mobile broadband penetration, subject to certain controls, it can be inferred that the
consolidation of the broadband market impacts diffusion. Similarly, if CAPEX changes
make statistically significant effects on mobile broadband penetration, subject to certain
controls, it can be inferred that duopoly ISPs’ investment decisions are affecting
broadband diffusion. To isolate the effect of the ISP duopoly – in market concentration
and investment choice – the paper uses the following equation:
1.) Capablet = B0 + B1 hhit-1 + B2 capext-1 + B3 inct-1 + B4 edt-1 + B5 vt-1 + B6 workt-1
where capablet represents the mobile broadband adoption rate at a given year, t, from
2006-2016. HHIt-1 is a measure of market concentration; capext-1 is a measure of the
average ISP Capital Expenditure/Revenue ratio; inct-1 is a measure of GNI per capita; edt-1
Figure 9 – Summary Statistics
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is a measure of the UN education index; vt-1 is a measure of the EIU Voice and
Accountability Index; and, workt-1 is a measure of the percentage of working broadband
wires. Each of the independent variables are lagged by one year.
The coefficients of interest are B1 and B2. B1 estimates the average difference in
changes in mobile broadband penetration as the ISP market became more concentrated
and settled in its current duopoly form. B2 estimates the average differences in changes
in mobile broadband penetration as the two ISP firms adjusted their investment on
assets related to broadband. Given the observed pattern of Philippine mobile
broadband adoption, the paper hypothesizes that neither HHI nor capex will have a
statistically significant impact on capable for a given t.
The key assumption of the research design is that all other market factors such as
economic changes, political influences, and consumer preferences are sufficiently
accounted for. Adoption-determining characteristics such as changing consumer tastes
and ISP behavior are assumed to have changed only minutely from the period from
2006-2016. This assumption could be wrong if a significant change occurred with the
one of the duopoly ISPs since market concentration and CAPEX investments are the
two observed variables. This risk is hopefully minimized by the fact that both Globe
and PLDT have been under the same ownership and management since 2002 (Tandeo
2015, p.3).
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4.3 – Results
Equation 2 highlights the results of the initial regression. The initial hypothesis
appears to have been correct – neither HHI nor CAPEX has a statistically significant
effect on Capable at the 95% level. Inc and work appear to have a statistically significant
relationship with Capable at the 95% level. An increase of $1 in GNI per capita leads to
an approximately 1.8% rise in mobile broadband device penetration. Conversely, an
increase of working wired lines by 1% reduces mobile broadband adoption by 1.14%.
This result makes sense intuitively and mirrors Cincera, Lauriane, and Estache’s
observation that fewer are compelled to adopt mobile broadband if wired services are
more efficient (2015, p.10). Surprisingly, Equation 2 also shows that v and ed do not
have statistically significant effects on Capable at the 95% level. Another issue that may
need to be addressed is the high R-squared value, although this may be a function of
having a very limited set of observations.
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(2)
VARIABLES capable
hhi -9.445
(21.59)
capex 0.124
(0.235)
inc 0.0270***
(0.00330)
ed -112.3
(214.2)
v -33.76
(46.67)
work -1.147**
(0.330)
Constant 95.92
(95.66)
Observations 11
R-squared 0.995
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
To ensure the robustness of the equation, the investigation modified several of
the control variables to see if the same result was achieved. Equation 3 shows the
regression without ed or v, the two controls that were not statistically significant.
Equation 4 highlights the equation with only income as the control – empirical evidence
suggests that income is the most important control in mobile broadband adoption
studies (Yates, Gulati, Marabelli 2015, p. 1). In both specifications, the result is the same
– neither hhi nor capex has a statistically significant effect on capable.
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(3) (4)
VARIABLES capable capable
hhi 21.13 -2.151
(43.98) (16.55)
capex 0.160 0.0503
(0.633) (0.234)
inc 0.0259*** 0.0237***
(0.00679) (0.00252)
work -1.168***
(0.173)
Constant -56.10** 18.28
(16.45) (12.56)
Observations 11 11
R-squared 0.930 0.992
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
4.4 – Discussion
The main observation that warrants discussion is the fact that the ISP duopoly –
through consolidation or investment – does not impact mobile broadband adoption
positively or negatively.
It makes intuitive sense that the ISP Duopoly does not have a positive impact on
mobile broadband device penetration. This duopoly structure is a significant inhibitor
of internet performance and accessibility. Instead of striving to provide the best possible
service, the duopoly ISPs are motivated to offer slow, subpar connections and charge
disproportionately high prices. Consumers, only given two internet options, are forced
to tolerate unreliable internet services. Figure 10 reflects this.
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The graph highlights that internet ISPs thrive in a duopoly. Both ISPs have managed
to increase the number of broadband subscribers, mobile and wired, despite stagnant
connection speeds. This underscores how the institution of a duopoly market creates
perverse incentives for incumbent ISPs and hurts broadband users. Ideally, a market
should force profit-maximizing firms to create the best possible product to attract
consumers. This is not the case in Philippine internet. The flawed nature of the ISP
duopoly suggests that another factor must be driving the adoption of Philippine mobile
0
0.5
1
1.5
2
0
5
10
15
2010 2011 2012 2013 2014
Inte
rne
t Sp
ee
d (
Mb
ps)
ISP
Su
bsc
rib
ers
(M
illio
ns)
Globe and PLDT Subscribers and Average Philippine Internet Speed
Globe Subscribers (Millions) PLDT Subscribers (Millions)
Average PH Internet Speed
Tandeo 2015, p.38
Figure 10 - Figure 10 shows the number of ISP subscribers – mobile and wired –
Globe and PLDT maintained from 2010-2014 and the average Philippine Internet
speed in that same period. Average internet speed was calculated by getting the
arithmetic mean of the speeds of the Philippines’ wired and mobile internet
connections in each year. ISP subscribers are annually reported by Globe and PLDT
although there is typically a 18-24 month lag, which is why subscriber numbers for
2015 and 2016 are not available. The graph shows that ISP subscribers have
increased despite stagnant internet speeds.
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broadband. A significant motivator is needed for Filipinos to overlook slow speeds and
adopt mobile broadband services.
The ISP Duopoly institution does not only propagate mediocre internet connections
but also rewards them. The lack of competition in the Philippine internet market allows
ISPs to charge disproportionately high prices for connection services. This further
cements a set of societally-damaging incentives where ISPs are permitted and even
encouraged with monetary reward to offer poor services. As noted earlier, Philippine
broadband is amongst the slowest and most expensive across Asia. However, this has
not stopped rapid adoption. Instead of punishing duopoly firms by choosing not to
purchase mediocre connections, Filipinos acquiesce to slow speeds and even reward
ISPs by paying high fees. This indicates that consumer internet demand is so strong that
they are willing to pay high prices for slow speeds. The ISP duopoly does not appear to
have a dulling effect on internet adoption as one might initially think, something that
the regression analysis appears to confirm. Therefore, it seems likely that other factors
are overcoming the negative effects of the ISP duopoly to continue mobile broadband
adoption. This idea is further strengthened by the fact that government and education
do not appear to have a significant impact on mobile broadband adoption. It is apparent
that another stimulus is driving the diffusion of mobile connectivity. This necessitates a
second empirical analysis.
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5 – Comparing Foreign and Domestic Innovations The paper’s second regression analysis is geared at determining if other
innovations in mobile broadband have allowed the Philippines to overcome the
consequences of the ISP duopoly.
5.1 Data
Data in the second regression analysis also uses information from the
BuddeComm “Philippine Telecom, Mobile, Bradband, and Digital Media” report and
the GSM Association (GSMA) “Philippine Telecom Market Data” report (2016).
Additionally, mobile broadband penetration rate at a given t (year from 2006-2016),
denoted as Capablet, is still used as the dependent variable and all independent variables
are lagged by one year relative to the corresponding broadband penetration rate. Lastly,
all independent variables are lagged by one year to take into account the fact that most
influences on broadband penetration take some time to materialize.
5.1.1 – Independent Explanatory Variables
The paper’s second regression analysis is geared at determining if other
innovations in mobile broadband have allowed the Philippines to overcome the
consequences of the ISP duopoly. This differs from the first section as the focus is now
on specific innovations and developments rather than on a market structure or a firm’s
investment decision like CAPEX/Revenue. Kongaut and Bohlin highlighted three main
areas of innovation that impact mobile broadband adoption: usage, distribution, and
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network quality (2015, p. 748). These three categories determine the nature of the
independent variables used in this portion of the paper.
5.1.1.1 – Social Media Usage
Social media usage, because of its profound popularity among Filipinos, is
selected as the main indicator of innovation in mobile usage. While social media
catalyzing mobile broadband adoption is not unique, the extent that social media
impacts Philippine diffusion is truly notable. Figures 11 and 12 crystalize this fact.
Tandeo 2015, p.7
Figures 11 and 12 - Figures 11 again shows the number of hours the average internet user in different
Asia Pacific countries spent online in 2015 (first displayed in Figure 3). This is compared with Figure 12,
which shows the average amount of time individuals in different countries spend on social media in
2015. ‘Time spent on social media’ is defined as an individual actively using a website or application
associated with a social network. Subsidiaries of social media groups, such as WhatsApp, count as ‘time
spent on social media’. Passive use, such as leaving a social media application open, is not counted. The
two charts highlight how social media is a major driver of a typical Filipino’s broadband usage habits.
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Figure 11 and 12 show that the average Filipino uses 68% of internet time on
social media, more than members of nearly all other nations. Currently, forty-one
million Filipinos, 62% of the population over the age of 14, have Facebook accounts.
Nearly nine million Filipinos, 13% of the population over 14 years old, have Twitter
accounts. These numbers make the Philippines Facebook’s 6th largest and Twitter’s 8th
largest markets (Tandeo 2015, p.7). Social media has clearly impacted broadband
adoption.
Though most Filipinos have accounts on different networks and platforms, the
number of Facebook subscribers in millions denoted as fb, is used as a measure of social
media adoption. A ‘Facebook subscriber’ is defined as an individual who has an
account on Facebook or one of the company’s other platforms. This data is collected
annually by local research firms and Facebook itself.
Facebook users is the most suitable measure of social media usage for several
reasons. First, Facebook is the by far the most popular social media platform in the
Philippines and was the first of its peers to enter and begin operations in the
Philippines. Furthermore, the company has the most readily available suitable data.
However, it is Facebook users’ propensity to access their content via mobile
device that truly makes them the most suitable measure of social media usage. 81% of
Filipino state that their mobile phone is the primary device used when perusing
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Facebook or its other platforms (Tandeo 2015, p. 3). This suggests that Facebook is a
prominent driver of innovation in Filipino mobile device usage.
5.1.1.2 – Foreign Smartphone retailers
Innovation in mobile distribution is represented by the increasing number of
foreign smartphone retailers, denoted as store. Until recently, most mobile phones were
sold by local establishments. However, foreign companies such as Apple and HTC
began to create and grow retail chains in 2007 to expand smartphone sales (EIS 2016, p.
32). This has been a significant innovation in distribution as individuals now have
access to a wider variety of devices, potentially increasing mobile adoption.
Other studies have focused on e-commerce to measure changes in mobile device
distribution (EIS 2016, p.40). This area is not as relevant as foreign smartphone retailers
in the Philippines because less than 0.5% of all consumers order their mobile devices
online (EIS 2016, p.2). Store-bought devices still dominate the market, which makes it
most useful to focus on foreign smartphone retailers when studying innovation in
mobile distribution.
The relative impact of foreign smartphone retailers on mobile broadband
penetration highlights what effect increased availability of devices has on Filipino
consumers. If foreign smartphone retailers have a statistically significant effect on
mobile device penetration, it can be concluded that innovations in foreign devices,
regardless of network quality, help drive broadband adoption.
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5.1.1.3 – Network Quality
The final area of mobile broadband innovation is network quality. Unlike the
two prior factors, network quality is an area that only domestic entities can contribute
to. Improved network quality is represented by the number of 4G connection base
stations, which are fixed devices that facilitate wireless network receiving and
transmission. This variable is denoted as g. The greater number and higher quality of
base stations, the more stable and widespread 4G connections are. The number of these
devices is an important measure increased network quality is a major contributor to
mobile broadband adoption (Kongaut and Bohlin 2015, p.747). Having reliable 4G
connections increases the capabilities of a mobile broadband device and makes it more
appealing to users.
5.1.1.2 – Foreign Smartphone retailers
Innovation in mobile distribution is represented by the increasing number of
foreign smartphone retailers, denoted as store. Until recently, most mobile phones were
sold by local establishments. However, foreign companies such as Apple and HTC
began to create and grow retail chains in 2007 to expand smartphone sales (EIS 2016, p.
32). This has been a significant innovation in distribution as individuals now have
access to a wider variety of devices, potentially increasing mobile adoption.
Other studies have focused on e-commerce to measure changes in mobile device
distribution (EIS 2016, p.40). This area is not as relevant as foreign smartphone retailers
in the Philippines because less than 0.5% of all consumers order their mobile devices
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online (EIS 2016, p.2). Store-bought devices still dominate the market, which makes it
most useful to focus on foreign smartphone retailers when studying innovation in
mobile distribution.
The relative impact of foreign smartphone retailers on mobile broadband
penetration highlights what effect increased availability of devices has on Filipino
consumers. If foreign smartphone retailers have a statistically significant effect on
mobile device penetration, it can be concluded that innovations in foreign devices,
regardless of network quality, help drive broadband adoption.
5.1.1.3 – Network Quality
The final area of mobile broadband innovation is network quality. Unlike the
two prior factors, network quality is an area that only domestic entities can contribute
to. Improved network quality is represented by the number of 4G connection base
stations, which are fixed devices that facilitate wireless network receiving and
transmission. This variable is denoted as g. The greater number and higher quality of
base stations, the more stable and widespread 4G connections are. The number of these
devices is an important measure increased network quality is a major contributor to
mobile broadband adoption (Kongaut and Bohlin 2015, p.747). Having reliable 4G
connections increases the capabilities of a mobile broadband device and makes it more
appealing to users.
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5.1.2 – Independent Control Variables
Two control variables shown to have empirical links to mobile broadband
penetration are included.
5.1.2.1 – Mobile Phone Quantity
The first control variable is the quantity of Filipino mobile phones, denoted as
mobile. Factors such as increased income and population growth lead to increases in the
raw number of mobile phones required to service a society, irrespective of any other
innovations in the market. Phone features like broadband capability inevitably improve
as manufacturers need to make devices that service all their markets, developed or
otherwise (EIS 2016, p.11). Therefore, it is important to account for the impact that rising
mobile phone quantity has on broadband diffusion.
Quantity of mobile phones is measured by mobile phone penetration rate, which
is the measure of all active mobile phones as a percentage off the entire Philippine
population (GSMA 2016, p. 35). Using the raw number of phones, as in the case of
mobile broadband penetration rate, is problematic as it does not account for the
Philippines’ fast population growth. Mobile phone penetration rate allows one to
capture the diffusion of mobile phones relative to population changes. Unlike mobile
broadband penetration, mobile phone penetration includes phones that cannot connect
to the internet.
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5.1.2.2 –Smartphone Price
The second control variable is smartphone price, denoted as smart. Like income,
device price is shown to have a positive effect on mobile broadband adoption
(Shinohara, Morikawa, and Tuji 2014, p.12). Lower device prices are becoming more
common as foreign manufacturers try to increase global market share by making
broadband more accessible to less affluent individuals. This strategy is in full-effect in
the Philippines, which has a large population with a relatively low average income
(Tandeo 2015, p.6).
Smartphone price is measured using the average retail price of a smartphone in
the Philippines. This number is calculated by taking the arithmetic mean of the selling
prices of the 50 most popular broadband capable devices during the calendar year
(GSMA 2016, p.4). Continuously updating the sample of smartphones used allows for
changing tastes, technologies, and brands to be considered when determining the
average retail price.
5.2 – Empirical Strategy
To estimate the impact of several important innovations on mobile broadband
adoption, the paper will observe three variables – Facebook users, foreign smartphone
retailers, and 4G connection base stations. If Facebook user changes make statistically
significant effects on mobile broadband penetration, subject to controls, it can be
inferred that social media propensity is a driver of mobile broadband diffusion.
Similarly, changes in foreign smartphone retailers and 4G base stations will be analyzed
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to see if they have significant effects on mobile broadband penetration. To isolate the
effect of the three observed innovations in broadband distribution, use, and
connectivity the paper uses the following equation:
1.) Capablet = B0 + B1fb t-1 + B2 store-1 + B3 g-1 + B4 mobile-1 + B5 smartt-1
where capablet represents the mobile broadband adoption rate at a given year, t, from
2006-2016. Fbt-1 is a measure of Facebook users; storet-1 is a measure of the percentage of
phone retail outlets operated by foreign smartphone manufacturers; gt-1 is the number of
4G base stations; mobilet-1 is the percentage of mobile phone ownership; and, smartt-1 is
the average retail price of a smartphone in the Philippines. Each of the independent
variables are lagged by one year.
The coefficients of interest are B1, B2, and B3. B1 estimates the average difference in
changes in mobile broadband penetration as Facebook users increase. B2 estimates the
average differences in changes in mobile broadband penetration as the number of
foreign smartphone manufacturer retailers increases. B3 estimates the average
differences in changes in mobile broadband penetration as the number of 4G base
stations increase. Given the observed pattern of Philippine mobile broadband adoption,
the paper hypothesizes that neither HHI nor capex will have a statistically significant
impact on capable for a given t.
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5.3 – Results
Equation 5 highlights the regression’s results. Both fb and store have a statistically
significant effect on Capable at the 95% level. An increase of 1 million Facebook raises
mobile broadband penetration by 1.21% while an increase of 1% in the quantity of
foreign smartphone manufacturer stores raises penetration by 2.95%. However, g does
not appear to have the same statistically significant effect at the 95% level on mobile
broadband penetration. The results seem to indicate that foreign innovations driven by
smartphone manufacturers are far more effective in increasing Philippine broadband
penetration than domestic efforts spearheaded by the ISPs. Again, there is a high R
squared value, although this may be a function of having a very limited set of
observations.
(5)
VARIABLES capable
fb 1.212**
(0.386)
store 2.950**
(0.793)
g 0.0319
(0.109)
mobile 0.373
(0.197)
smart 0.153**
(0.0459)
Constant -106.8**
(30.38)
Observations 11
R-squared 0.996
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
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To ensure the robustness of the equation, the investigation modified the control
variables to see if the same result was achieved. Equation 6 shows the regression
without mobile, the control that was not statistically significant. The result is the same
and the coefficients for fb and store are close in value to the result derived in Equation 5.
(6)
VARIABLES capable
fb 1.506**
(0.423)
store 3.527***
(0.876)
g -0.0944
(0.104)
smart 0.122*
(0.0514)
Constant -70.59**
(28.32)
Observations 11
R-squared 0.993
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
5.4 – Discussion
5.4.1 – Adoption driven by Foreign Innovation
Interestingly, the two innovations that appear to have the greatest positive
impact on mobile broadband penetration originate from foreign entities. Facebook and
the establishment of retail outlets by smartphone manufactures indicate that providing
Filipinos with access to foreign innovations is a powerful avenue to encourage mobile
adoption. A key example is the recent activity of Facebook, which has begun to take
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advantage of the Philippines’ reputation as one of the “social tech capitals of the world”
(Tandeo 2015, p. 35).
Figure 13 crystalizes that foreign technology companies’ innovations, such as
social media, are profound catalysts of mobile broadband adoption. One can observe a
strong relationship between Facebook and Internet users. This is likely due to the
propensity for social media and the subsequent need for connection. The growth rates
from 2013 to the 2017 projection are particularly high. This period marks the duration of
Facebook’s Philippine expansion where the firm intends to augment its operations and
0
10
20
30
40
50
60
70
80
90
100
0
10
20
30
40
50
60
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Ph
ilip
pin
e I
nte
rne
t U
sers
(M
illio
ns)
Face
bo
ok
Use
rs (
mill
ion
s)
Philippine Facebook Users vs. Philippine Internet Users
Facebook Users Philippine Internet Users
Facebook
sends full-
time staff
Completion
of Facebook
offices and
PH expansion
Figure 13 - Figure 13 shows the number of Philippine Facebook and Internet (mobile and wired)
users. The number of internet users is a projection derived from annual results published by the two
ISP duopoly companies. The amount of Facebook users is based on public company data and
projections made through an annual consumer telecommunications survey conducted in 2015.
Facebook’s two largest operational actions in the Philippines – the deployment of full-time staff and
the completion of new offices – are noted to show how the company is courting more Philippine
users. There appears to be a strong relationship between Facebook users and overall Internet users.
Tandeo 2015, p. 32
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further market its product (Tandeo 2015, p.53). Facebook’s strategy of augmenting its
innovation by establishing a physical presence in the Philippines mirrors the actions of
many firms such as Apple, HTC, Lenovo, and Google (Tandeo 2015, p.55). This trend
helps explain the results of the empirical analysis – social media and stores that sell
foreign devices increase mobile broadband adoption.
5.4.2 – Why domestic innovation falls short
The other notable observation from the second empirical analysis is that the
attempts at improving mobile networks through increased 4G base stations have fallen
short at encouraging mobile adoption. This is likely because the new connection
infrastructure still delivers inefficient service. Most Philippine broadband equipment,
including the machines used to deliver 4G services, are still made up of the same
components used for telephone lines, prone to damage and heavily inefficient (Budde
2016, p.6). The continued use of outdated technology even in the offering of new
services shows that domestic innovations are largely ineffective in promoting mobile
broadband adoption. This further cements the idea that the ISP duopoly is simply not
incentivized to effectively innovate.
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6 – Discussion of Overall Results When reviewing both empirical investigations, it becomes clear that mobile
broadband adoption in the Philippines is driven by consumer demand rather than the
availability of high quality connection services.
The independent explanatory variables that proved to be statistically significant
in impacting mobile broadband device penetration were Facebook users and the
presence of foreign smartphone retailers. Both these variables reflect demand of a
broadband related product. The fact that the number of Facebook users positively
influenced broadband penetration indicates that Filipinos’ demand for social media
access is so great that they are willing to tolerate the poor connection available.
Likewise, the positive influence foreign smartphone retailers have on broadband
penetration shows that Filipinos are highly motivated by their demand for
smartphones. The investigation suggests that demand for services that are facilitated
through broadband are more important to Filipino mobile consumers that the actual
quality of the broadband service.
This conclusion is further strengthened when one reviews the explanatory
variables that were not statistically significant to mobile broadband device penetration.
The variables that were not significant were HHI, CAPEX/Revenue, and 4G Network
Quality. Each of these metrics impacts the quality of the mobile broadband services
available to Filipinos. Increased HHI and CAPEX/Revenue not affecting mobile
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broadband penetration shows that the duopoly ISP’s actions – consolidating the
telecommunications market or investing in connection quality – does not markedly
affect consumers. This is augmented by the fact that even 4G Network quality does not
appear to influence individuals’ mobile adoption patterns. The quality of the mobile
connections available appears to be far less important than Filipinos’ demand for
broadband related services.
This insight suggests that Philippine innovation can somewhat overcome the
negative effects of the ISP duopoly. Governments and members of the mobile
technology community, such as Facebook, might benefit from promoting broadband
related services to Filipinos. The evidence of this investigation suggests that having an
affinity for a product, like smartphones, or a service, like social media, can compel
Philippine consumers to adopt broadband regardless of quality. While Globe and PLDT
are likely too powerful within the telecommunications market to pressure into
providing cheaper, more efficient connections, there are still demand-related methods
to promote mobile broadband adoption.
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7 – Conclusion The paper provides evidence that confirms the notion that Philippine mobile
adoption is not hindered by the ISP duopoly. An analysis of Philippine broadband’s
HHI indicates that the gradual increase in market concentration has not hindered the
adoption of a very important technology. Moreover, a study of the duopoly ISPs’
investment patterns – their CAPEX/Revenue – indicates that this spending has not
translated into mobile broadband adoption either. The combination of these two
insights makes a significant implication – the duopoly needs to go through some reform
although not necessarily a drastic change. The resilience of mobile broadband adoption
in the face of increasing HHI suggests that a duopoly can be a sufficient, albeit flawed,
structure for the Philippine market. It may be more productive from a policy standpoint
to influence ISP investment to more productive channels rather than lobbying for the
breaking up of the duopoly (Tnadeo 2015, p.3). Globe and PLDT may be more amenable
to adjusting their investments than agreeing to the prospect of being broken into
separate companies.
The second empirical study reveals the importance of foreign innovations in
driving mobile adoption. Social media and the increased presence of foreign technology
firms appear to have a marked effect on Filipinos’ willingness to use mobile broadband
devices. This is not the case for domestic innovations as they are still dictated by the
two ISP firms, which are incentivized to pursue sub-optimal actions. This finding
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suggests that the Philippines should craft more policies that facilitate the increased
activity of foreign firms in the mobile space. One action that appears to be particularly
effective in driving mobile broadband adoption is the creation of a direct distribution
point, such as a retail store, where foreign firms can sell their products to Filipino
consumers.
The largest limitation to this analysis is the lack of data. First, many of the drivers
of Philippine internet adoption are new events or industries. This means that there is
too little existing data to make accurate claims. Mobile broadband is also not a very
established phenomenon, suggesting that it may be difficult to establish definitive
trends. A potential remedy and interesting point of future study would be to utilize the
case of the Philippines in cross-country comparisons such as the one conducted by
Yates, Gulati, and Marabelli (2015). However, a challenge in conducting comparisons
between different nations is the fact that they will have different histories and
socioeconomic circumstances. Thus, one variable may be crucial to understanding one
country but insignificant for another. Control variables may be very difficult to identify.
A potential solution would be to have a continuous study of mobile broadband so that
the evolution of adoption drivers is accurately recorded.
The study underscores other potential research question that warrant further
study. It would be interesting to see whether the ISP duopoly, through government
actions like taxation, subsidies, or private-public partnerships, could be compelled to
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better invest in mobile innovation. Another fascinating question is whether the duopoly
ISPs and foreign technology firms can create mutually beneficial partnerships that
expand mobile broadband capabilities. Lastly, a study on the impacts of mobile
broadband adoption in specific Philippine industries – from tourism to retail to
agriculture – would help shed light on the most beneficial methods that mobile
broadband can be used.
There is clearly a significant inclination to utilize mobile broadband technology
in the Philippines. The paper’s conclusion that foreign innovation can help overcome a
sub-optimal market structure shows that it is worth investigating what stimulus can
best encourage Filipinos to continue adopting these devices.
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8 – Bibliography
Agonoy, Jay. "Slow Yet Expensive PH Internet 'not Our Fault'." Rappler. September 16, 2015.
Accessed December 31, 2016. http://www.rappler.com/move-ph/106062-slow-expensive-
ph-internet-not-our-fault. Almqvist, Erik, Janette Stewart, Alex Reichl, and Gergana Rangelova. The Impact of Mobile
Broadband in the Asia-Pacific Region, and Future Spectrum Needs. Report no. 2002099-
483. London: Analysys Mason, 2015.
BMI. Philippines Telecommunications Report Q3 2016. Report no. 1748-4731. London:
Business Monitor International, 2016.
Budde. Philippines - Telecoms, Mobile, Broadband, and Digital Media Statistics and Analysis.
Report. 22nd ed. Bucketty: Budde, 2016.
Cincera, Michele, Lauriane Dewulf, and Antonio Estache. "How Much Does Speed Matter in the
Fixed to Mobile Broadband Substitution in Europe?" International Center for Innovation
Technology and Education, 2014, 1-30.
EIS. Mobile Phones in the Philippines. Report. PASSPORT. Euromonitor International, 2016.
Gilbert, Richard J., and David M. Newberry. "Preemptive Patenting and the Persistence of
Monopoly." The American Economic Review 74, no. 1 (March 01, 1984): 251-53.
Accessed January 5, 2017. http://www.jstor.org/stable/10.2307/1803330?ref=search-
gateway:3d03d2071dbfdd3fcbdf83952faab3b6.
GSMA. The Mobile Economy - Asia Pacific 2016. Report. GSMA Intelligence. London: GSMA,
2016.
Hollinger, Peggy. "Poor Broadband Threatens UK Growth." Financial Times. February 8, 2016.
Accessed June 13, 2016. https://www.ft.com/content/1f26c3fe-cd98-11e5-92a1-
c5e23ef99c77. ITU. The Economic Impact of Broadband in the Philippines. Report. Vol. 1. Broadband Series -
Millennium Development Goals. Geneva: ITU, 2015.
Kongaut, Chatchai, and Erik Bohlin. "Investigating Mobile Broadband Adoption and Usage: A
Case of Smartphones in Sweden." Telematics and Informatics 33, no. 3 (2016): 742-52.
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Ono, Hiroshi. "Digital Inequality in East Asia: Evidence from Japan, South Korea, and
Singapore." Asian Economic Papers 4, no. 3 (2005): 116-39.
doi:10.1162/asep.2005.4.3.116.
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Romero, Joshua J. "FCC Redefines Broadband: Lack of Competition Now Obvious." IEEE
Spectrum: Technology, Engineering, and Science News. January 30, 2015. Accessed
November 13, 2016. http://spectrum.ieee.org/tech-talk/telecom/standards/when-are-fast-
internet-connections-fast-enough.
Tandeo, Hazel. Philippine Telecoms - Almost Ripe for Digital. Report. Manila: CLSA, 2015.
Tsuji, Masatsugu, Sobee Shinohara, and Hiroyuki Morikawa. "Empirical Analysis of Mobile
Broadband Adoption in Major Six Countries." SSRN Electronic Journal, 2014, 1-22.
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Yates, David J., Girish J. Gulati, and Marco Marabelli. "Determinants of Mobile Broadband
Diffusion: A Focus on Developing Countries." Association for Information Systems, May
29, 2015, 1-15.
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9 – Appendix Figure 1
This chart shows the number of internet subscribers in the Philippines from 2011-2016 and the
projected number of subscribers from 2017-2019. The chart also breaks down these subscribers into
mobile broadband and fixed (wired) broadband users. This establishes that mobile broadband has
consistently been utilized at a higher rate than fixed broadband.
Figure 1 uses data collected in the 2016 Budde Telecommunications Report on the Philippines
and another telecommunications dataset (Tandeo 2015). Internet subscribers, rather than internet users,
are measured. This is because of the varied definitions used to describe an ‘internet user’ – some
publications define an internet user as the owner of an internet-capable device while others define a user
as one who regularly goes online.
Figure 2
This graph shows the number of hours the average internet user in different Asia Pacific
countries spent online in 2015. The chart shows that Filipinos generally spend a high amount of time
online compared to citizens of neighboring countries. This highlights how the Philippines is somewhat of
an anomaly – it features high internet usage within a duopoly market.
Figure 2 uses data collected in a 2015 survey focused on Asia Pacific consumers in the
telecommunications industry (Tandeo 2015). The survey interviewed a sample of individuals meant to be
representative of a country’s entire population. One of the questions asked was ‘how much time do you
spend on the internet?’. The hour figures displayed on the graph is the average amount of time spent on
the internet by each country’s sample.
0
20
40
60
80
100
2011 2012 2013 2014 2015 2016 2017 2018 2019
Sub
scri
ber
s (m
illio
ns)
Philippine Internet Subscriptions
Fixed Broadband Mobile Broadband Total Internet
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Figure 3
The figure shows a comparison between the annual growth rates of smartphone data usage in the
Philippines, High Adoption Nations, and East Asia. This is measured by the average annual growth rate
in amount of mobile data consumed (measured in gigabytes) from the years 2008-2015. ‘High Adoption
Nations’ refer to a select group of countries with populations that widely use mobile phones (over a 75%
adoption rate). These include the US, UK, Germany, and Japan. The chart shows that the Philippines has
adopted smartphones at a markedly rapid rate, highlighting how high mobile internet usage has
translated to the adoption of the latest innovations in mobile broadband.
Figure 3 uses data collected in the 2016 Budde Telecommunications Report. Smartphones are
defined in this chart as any mobile phone with a distinct operating system to avoid any classification
issues when comparing between different countries. Data usage is measured in gigabytes. The average
annual growth rate is calculated by getting the arithmetic mean of data usage growth in each year from
2008-2015. ‘High Adoption Nations’ refer to a select group of countries with populations that widely use
mobile phones (over a 75% adoption rate). These include the US, UK, Germany, and Japan. ‘East Asian’
countries includes China, Hong Kong, Macau, Taiwan, Mongolia, South Korea, and Japan.
0
10
20
30
40
50
60
70
80
Philippines High Adoption Nations East AsiaSmar
tph
on
e D
ata
Ave
rage
A
nn
ual
Gro
wth
Rat
e (
20
08
-1
5)
Philippine and Asia Smartphone Data Usage
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Figure 4
This chart shows the average monthly internet cost, measured in $/mbps, and the average
internet speed, measured in mbps (megabytes per second), of the Philippines, Vietnam, Malaysia, and
Cambodia in 2015. Also included is a global average of the two above-mentioned values. This includes
the monthly internet cost and speed of all UN member countries. Figure 5 shows how the Philippines
suffers from internet that is not only slow but expensive.
Figure 4 uses data collected by the International Telecommunications Union (ITU), a specialized
agency of the UN. Average monthly internet cost is calculated by the price of a country’s average internet
subscription – mobile or wired – divided by the average speed of said subscription. Average internet
speed was calculated by getting the arithmetic mean of the speeds of a country’s wired and mobile
internet connections. Vietnam, Malaysia, and Cambodia were used as comparison countries because they
have similar socioeconomic, population, and technological traits as the Philippines.
0
5
10
15
20
25
30
0
2
4
6
8
10
12
14
16
18
20
Philippines Vietnam Malaysia Cambodia Global average
Ave
rage
inte
rnet
sp
eed
(m
bp
s)
Mo
nth
ly In
tern
et C
ost
($
/mp
bs)
Average monthly internet cost ($/mpbs) and speed (mbps)
Price Speed
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Figures 5 and 6
Figures 5 and 6 show the gradual consolidation of the Philippine broadband market into a
duopoly from 2005-2015. Both graphs measure the market shares of the two duopoly companies in the
broadband industry. Market share is calculated by dividing a company’s ISP and broadband service sales
by the entire amount of sales in the Philippine broadband market. Figure 5 shows Globe and PLDT’s
market shares separately while Figure 6 shows the two company’s combined market shares. Figure 6 also
notes 2011, the date when Globe purchased the last remaining non-duopoly ISP. One can observe that the
combined market share increases to 100% in 2012 and stays at that level, highlighting the creation of the
current ISP duopoly.
The data used to calculate market shares is collected from company filings and
telecommunications industry reports (Tandeo 2015). Globe and PLDT are both publicly listed on the
Philippine Stock Exchange. Therefore, their sales in the ISP space are annually reported. Both companies
define ISP sales as any income derived from broadband – wired and mobile – services. The total
broadband sales figure is an independently calculated statistic measured annually (Tandeo 2015). Before
2012, it combined all ISP sales of each Philippine ISP firm, all public companies. From 2012 onwards, the
total Philippine ISP sales value was equivalent to the combined market share of Globe and PLDT.
0%
25%
50%
75%
100%
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Globe and PLDT Market Share of Philippine Broadband Market (%)
Globe Market Share PLDT Market Share
0%
50%
100%
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Globe and PLDT Market Share of Philippine Broadband Market (%)
Globe + PLDT Market Share
Globe purchases the last
non-duopoly ISP provider
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Figure 10
Figure 10 shows the number of ISP subscribers – mobile and wired – Globe and PLDT
maintained from 2010-2014 and the average Philippine Internet speed in that same period. Average
internet speed was calculated by getting the arithmetic mean of the speeds of the Philippines’ wired and
mobile internet connections in each year. ISP subscribers are annually reported by Globe and PLDT
although there is typically a 18-24 month lag, which is why subscriber numbers for 2015 and 2016 are not
available. The graph shows that ISP subscribers have increased despite stagnant internet speeds.
Globe and PLDT count any individual who uses a subscription regularly as a ‘subscriber’. ISP
subscribers are more difficult to track than ISP sales because it is harder to determine how many people
use a single subscription. Average internet speed is used to illustrate the typical experience of a user and
to show that poor quality has not dulled the growth of internet users.
0
0.5
1
1.5
2
0
5
10
15
2010 2011 2012 2013 2014
Inte
rne
t Sp
ee
d (
Mb
ps)
ISP
Su
bsc
rib
ers
(M
illio
ns)
Globe and PLDT Subscribers and Average Philippine Internet Speed
Globe Subscribers (Millions) PLDT Subscribers (Millions)
Average PH Internet Speed
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Figures 11 and 12
Figures 11 again shows the number of hours the average internet user in different Asia Pacific
countries spent online in 2015 (first displayed in Figure 3). This is compared with Figure 12, which shows
the average amount of time individuals in different countries spend on social media in 2015. ‘Time spent
on social media’ is defined as an individual actively using a website or application associated with a
social network. Subsidiaries of social media groups, such as WhatsApp, count as ‘time spent on social
media’. Passive use, such as leaving a social media application open, is not counted. The two charts
highlight how social media is a major driver of a typical Filipino’s broadband usage habits.
The data used to measure ‘time spent on social media’ was derived from an annual consumer
survey conducted in 2015 that focused on Asia Pacific consumers in the telecommunications industry
(Tandeo 2015). The survey interviewed a sample of individuals meant to be representative of a country’s
entire population. One of the questions asked was ‘how many hours per day do you spend on the listed
social media platforms?’ (a list was provided). The definition of ‘using a platform’ was also clarified to all
respondents as active usage.
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Figure 13
Figure 13 shows the number of Philippine Facebook and Internet (mobile and wired) users. The
number of internet users is a projection derived from annual results published by the two ISP duopoly
companies. The amount of Facebook users is based on public company data and projections made
through an annual consumer telecommunications survey conducted in 2015. Facebook’s two largest
operational actions in the Philippines – the deployment of full-time staff and the completion of new
offices – are noted to show how the company is courting more Philippine users. There appears to be a
strong relationship between Facebook users and overall Internet users.
The projections for future internet user numbers are made by CLSA research by using a
proprietary model that considers historical internet usage and projections made by Globe and Smart.
Similarly, the projections for future Facebook user numbers are made by CLSA using historical usage
patterns and Facebook growth in similar Southeast Asian countries. 2009 is the first year considered in
this chart as it is the first full year where Facebook reached over 1 million Filipino users.
0
10
20
30
40
50
60
70
80
90
100
0
10
20
30
40
50
60
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Ph
ilip
pin
e I
nte
rne
t U
sers
(M
illio
ns)
Face
bo
ok
Use
rs (
mill
ion
s)
Philippine Facebook Users vs. Philippine Internet Users
Facebook Users Philippine Internet Users
Facebook
sends full-
time staff
Completion
of Facebook
offices and
PH expansion
