Discussion Paper No. 804

PREVENTION OF COMPETITION
BY COMPETITION LAW: EVIDENCE
FROM UNBUNDLING REGULATION
ON FIBER-OPTIC NETWORKS IN JAPANNaoaki Minamihashi
The 13th ISER-Moriguchi Prize (2010)
Awarded Paper

March 2011

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

Prevention of Competition by Competition Law: Evidence
from Unbundling Regulation on Fiber-Optic Networks in Japan
Naoaki Minamihashiy
Boston University
This Draft: Feb, 2011
First Draft: July, 2010

Abstract
This paper …nds that a regulation that promotes competition in one market
may decrease competition in other related markets. Policy makers in the telecommunication industry currently are facing an important decision about whether tocontinue unbundling regulations on new optical-…ber lines. I …nd that unbundlingregulation prevents new providers from building optical-…ber networks, by estimating a dynamic entry game with a dataset of …ber-optic network constructions inJapan from 2005 to 2009. In particular, when a new technology is introduced,
unbundling regulation has an oligopolization e¤ect on the regulated …rms. This…nding in the Japanese telecommunications industry suggests that unbundling regulation during periods of new technology di¤usion may reduce the price of service
but also decrease competition in the infrastructure market. (JEL K21, L43, L96
Keywords: Unbundling, FTTH, Entry and Exit, Dynamic Game, Fiber-optic Networks)

This paper has bene…tted from the continuous advice, encouragement, and overall guidance of Marc
Rysman. I am indebted to Takanori Ida, Jordi Jaumandreu, Joshua Lustig, Masatsugu Tsuji, and Ingo
Vogelsang for discussions that generated great improvements. I also thank to Charles Ho, Chun-Yu Ho,
Toshifumi Kuroda, Mitsuru Sunada, Elif Nilay Yilmaz and participants in International Telecommunications Society, Japan Economic Association, Japan Fair Trade Committee and Osaka university. I
acknowledge Hiroshi Ohashi, Ministry of International A¤airs and Communication and NTT East fordata usage. This paper was awarded the 13th Moriguchi Prize by the ISER at Osaka University, and I
acknowledge suggestions from annoymous referees. The author takes full responsibility for any remaining
errors.
y
Boston University, 270 Baystate Road, Boston, MA, 02215, US Mail: naoaki@bu.edu Web:http://people.bu.edu/naoaki/

1Should we protect competition with competition law? Historically, government authorities have engaged in fostering competition in industries with antitrust laws. They
have banned abusive conduct, such as tying or predatory pricing, and have prevented large
mergers and acquisitions. However, in recent developments of globalization, technologicalprogress, and the de facto standard economy, we can observe oligopolistic structures insome markets.1 The authorities are deregulating or reinterpreting competition law andregulations to keep up with the current society’s needs.
Telecommunications is one of the industries where competition is highly protectedby regulations. Governments around the world adopt a regulation called a Local-Loop
Unbundling (LLU) to accelerate competition. The law requires that telephone companies
that have monopolistic local premises (called "local loops") should share their lines withother companies at a low price. This is because the telecommunications industry is
characterized by a “natural monopoly” due to its huge, sunk, up-front and …xed costs,
and there is no competition in the market without the regulation. If governments regulate
carriers with facilities to allow other …rms to use their premises, then …rms with nofacilities can easily enter the market, and consumers can obtain a wide variety of highquality services at a low cost as a result of the competition. Industries that have natural
monopoly characteristics, such as electric, gas, and railroad industries, also have similar
unbundling regulations.
Policy makers in telecommunications, however, are confronted with a new problem inthe di¤usion process of building …ber-optic networks, called FTTH (…ber to the home).
The unbundling regulation decreases the incentive for …rms to invest in the latest technology; few …rms build home …ber-optic networks. This is because they cannot getmonopolistic pro…ts if they have to lend the …ber lines at a regulated low cost. Compared to the traditional metal line, this …ber-optic line can transfer large amounts ofdata with faster transfer rates, enabling services such as high speed internet, high qual1

For example: airlines, OS software, digital music downloads, credit cards, search engines, etc.

2ity digital voice, HDTV programs and cloud computing. Therefore, the regulation of…ber-optic networks is one of the most important concerns of policymakers in the world
today. A change in unbundling regulation would have immense e¤ects on investments,
penetration of …ber-optic networks, consumer welfare, and, ultimately, a country’s productivity. For example, in 2003, the United States’Federal Communication Commission(FCC) amended the law and removed unbundling regulations on …ber-optic premises inorder to accelerate building competition among carriers and promote investments in …ber
networks, even though many companies without facilities objected.2
However, in relation to unbundling regulation’s importance, the literature that studies
it is limited. This is because the municipal level data set is rarely available and buildingof the new networks, such as …ber-optic networks, is uncommon. For example, in thetelecommunication industry, metal networks were built more than 50 years ago; the new
networks that are going to be formed will be the …rst since the 1960s. Furthermore,home …ber-optic networks have not yet been installed in most countries. Japan, however,in 2005-2009 experienced a rapid increase of …ber-optic networks (FTTH) under the
unbundling regulation on …ber premises. There, authorities and regulated …rms alsoo¤ered micro-level data. Tables 1 and 2 show the international comparisons for thedi¤usion and regulation of …ber networks. We can observe that Japan is one of the rare
countries that experienced penetration and continued unbundling regulation.
Previous literature mainly studies the e¤ects of unbundling on service markets. Greenstein and Mazzeo (2006) found that unbundling widened the variety of services, andEconomides, Seim and Viard (2008) found that competition in service markets induced
2

This deregulation has been continually criticized by …rms that use the regulated lines, and createda controversy between regulated …rms and the users of their facilities. For example, in December 2009,
Cbeyond.Inc, supported by the Small Business Administration (SBA), …led a petition with the FCC toreverse the deregulation. In response to this, the Telecommunications Industry Association (TIA) andthe Fiber-to-the-Home (FTTH) Council in January 2010 jointly …led with the FCC not to reverse thederegulation. Similar disputes exists in Asia and Europe. For example, the Japanese government is
considering joint managment of …ber-optic networks within all related …rms. In Australia, the largest
telecom company, Tlesta, declared that they will not build …ber networks if the regulation is enforced.

3

by unbundling increased social welfare. However, the e¤ects of unbundling on infrastructure construction markets is not considered well. To reveal the e¤ects on infrastructure
construction of unbundling, the Japanese experience was an important episode. In 20052009, Japanese government continued the unbundling regulation on new …ber-optic lines
in the di¤usion periods of …ber-optic network construction. In the process, cable television and electric companies have reduced or stopped building their …ber lines. They
claimed to regulators that the unbundling decreased their incentives to build their own
lines. This is due to their lost of potential customers to the unbundling user …rms, andalso to intense price competition with unbundled …rms. As a result, in Japan, regulated…rms have dominated the infrastructure markets with the increase of unbundling usage,
and regulators failed to accelerate competition in building …ber-optic networks.
Using this phenomenon and the data sets, this paper analyzes unbundling regulatione¤ects on the entry decision of new …rms in building networks, and gauges the regulation’se¤ects on competition in the building of infrastructure. In this paper, we show the e¤ectsof unbundling usage on cable television’s entry decision on the …ber network construction
using linear regression and probit estimation. Second, this paper models the dynamic
game of infrastructure construction and estimates the e¤ect of unbundling on the pro…tsof new entrants. To evaluate how unbundling a¤ects the infrastructure construction, we
need a dynamic model of entry. New …rms enter the market considering future pro…ts
because it takes a huge initial investment to build the …ber lines. In both cases, we …nd
the negative e¤ects of unbundling on entry decisions due to pro…t decrease. This …nding
suggests that unbundling regulation during periods of new technology di¤usion decreases
competition in the infrastructure market.
This paper proceeds as follows. Section 1 overviews related literature. Section 2
discusses unbundling regulation and what happened in the infrastructure competition in
the …ber penetration in Japan. The data sets to be used in this study, their management

4and their characteristics are presented in Section 3. In Section 4, the evidence fromlinear and probit estimation is provided. The model of dynamic game of infrastructurecompetition and the estimation identi…cation is discussed in Section 5, and Section 6
concludes.

1

Previous Related Literature

Theoretical papers about local loop unbundling regulation analyzed its price and usagee¤ects on the installment of infrastructure. Jorde, Sidak and Teece (2003) found that theusage of unbundling will decrease investments, and Bourreau and Dogan (2005) and Horiand Mizuno (2006) considered regulation-price e¤ects on the infrastructure competition.
These theoretical papers suggest that unbundling regulation reduces investments andcompetition in infrastructures. On the other hand, Cave (2006) claims that unbundlingincreases the investment of carriers.
In empirical papers, the literature considered the pros and cons of unbundling regulation on society. As positives, Greenstein and Mazzeo (2006) found that unbundlingwidened the variety of services in the telecommunications industry. Economides, Seimand Viard (2008) found that competition induced by unbundling increased social welfare.
Conversely, Crandall, Ingraham and Singer (2004) showed that existing telecommunication carriers decrease their own investments by unbundling policies.
This paper is di¤erent from the literature above because of the following reasons:First, we identify that unbundling regulations prevent new entry in the facility market.
Previous literature mainly focuses on the service markets. This paper gauges the e¤ectsof how unbundling regulation to foster competition in service markets changed the competition in di¤erent markets. We …nd that regulation increases the regulated …rms’shareparadoxically, even though it aims to weaken those …rms. Secondly, we use the events of5

installing new technology to identify the e¤ects. The installment of …ber-optic lines tothe home is a good case to check the regulation e¤ects: entrants constructing new …berlines needs a signi…cant amount of money, and we can observe those behaviors clearly.
Furthermore, policy makers are currently debating whether to keep the regulation on…ber premises or not. In Japan’s case, "free and fair" competition in service markets,
induced by unbundling, destructs facility competition. Third, because entry decision intelecommunications is based heavily on dynamic behaviors, this pape r estimates thee¤ects using structural dynamic models.

2

Local Loop Unbundling and the Di¤usion of FiberOptic Networks in Japan

2.1

Telecommunications Act of 1996 and Export of US Unbundling Regulation

In 1996, the FCC (Federal Communications Commission), under the Clinton Administration started the Telecommunications Act of 1996. This law aims to promote new
entries and competition in the communication industry, mainly by the unbundling regulation. Unbundling requires speci…c existing carriers with local premises to lend theirfacilities to any competitors at a regulated low price. This law enables the …rms without
facilities to enter the industry easily, and solves the problem of natural monopoly. Literature shows that, as a result of fair competition, unbundling decreases prices, increases
a variety of services, raises consumer welfare, and provides high quality services, all ofwhich are positive contributions to society. Vogelsang and Mitchell (1997) summarizes
the regulation.
In 1998, unbundling regulation was exported outside the United States. Under the6

WTO telecommunications law, unbundling is approved as accelerating free and fair competition in telecommunications. Similar regulations are imposed in more than 80 countries over the world.
In the U.S., however, regulated …rms brought many suits on the regulations. They
claimed that it decreased the investments of regulated …rms, weakened facility-based
competition, and infringed upon their property rights. In response to these claims andjudicial decisions, the FCC amended some of the regulations. Particularly, the FCC
confronted the delay of prevalence of …ber to the home (FTTH) and aimed to speed up
the di¤usion. In contrast, regulated carriers insisted that unbundling regulation deterred
their investments on building …ber-optic networks. To encourage the di¤usion of …beroptic networks, the FCC in 2003 decided to remove unbundling regulation on …ber lines.
Whether this decision by the FCC was good for social bene…ts is still under discussion. In the contrast to era of Telecommunication Act of 1996, when regulated …rms
complained, at present the user …rms of unbundling regulation are petitioning to the
FCC to reverse the deregulation on unbundling on …ber lines.

2.2

Di¤usion of Fiber-Optic Networks and Battles over Unbundling in Japan

Unlike the United States, Japan is among the countries that faithfully adheres to theunbundling regulation of the WTO agreement on both …ber and metal lines. In Japan,
Nippon Telegraph and Telephone Corporation (NTT) is de…ned as a unique regulated
carrier. NTT was a government-owned telephone company, until privatization in 1985,
and remains the world’s largest group in the telecommunication industry. NTT inherited
numerous metal telephone lines from the government. Unbundling regulations started
in 1997, and the Telecommunications Business Act in Japan strictly enforced a NTT

7

to lend their local and relay lines, both …ber and metal, to all other …rms at a low
government-decided rental price.
The di¤usion process of …ber networks (…ber to the home (FTTH)) in Japan can beroughly divided into three stages. First, in the early 2000s, NTT’s FTTH’s share waslow. In March 2002, its share was 25.6%, but cable televisions (CATVs) and electriccompanies provided strong competition. NTT had metal telephone lines, CATVs had
metal CATV lines, and electric companies had their own electric lines. Therefore, forNTT, CATVs and Electric companies, it was easy to install …ber-optic lines next to theirpre-exiting lines. CATVs and electric companies entered the …ber market to earn pro…ts
from services such as high quality IP-phone, high de…nition TV programs, and high speed
internet. During this period, NTT’s competition thought that unbundling regulation waspreferable because it decreased NTT’s investment on …ber networks, which in turn would
allow their competitors’shares in the …ber market to increase.
However, in the middle of the decade, CATVs and electric …rms decreased theirinvestments or resigned to build in …ber networks (FTTH), because non-facility …rms
entered into the market using NTT’s premise. These new …rms took CATVs’and electriccompanies’potential customers. Also, even if CATVs build their own …ber lines, they willbe among harsh price competition with NTT

that has to share lines at regulated

low cost. Furthermore, the user …rms strongly demanded the government reduce therental price and ‡exible usage of the facility: user …rms estimated and claimed the rental
cost at 690 Yen (7.6 USD) per …ber line a month, but it was signi…cantly di¤erent fromthe government-decided / NTT’s claimed rental cost of 5094 Yen (56.6 USD). Con‡icts
on the conditions and prices of …ber lines between the NTT and user …rms, involved
Ministry of Internal A¤airs and Communications (MIC), Japan Fair Trade Committee(JFTC), courts, politicians, consultants, lawyers, and economists. In the battles between
NTT and user …rms, CATVs and electric companies always …led petition and claimed to8

MIC that the unbundling regulation decreased their incentive to enter the …ber-optic line
market and increase investment. They claimed that unbundling only favors the service
market in allowing "fair" competition, but negatively a¤ects competitors in facility-basemarkets.
Finally, by the end of the 2000s, NTT’s share of …ber lines was around 75%, and they
dominated the …ber facility market, eliminating other …rms under unbundling regulation.
Also, a few CATV started to borrow the …ber lines from NTT, rather than build lines
themselves.3 This market structure was heavily criticized by both user …rms and facility
competitors faced with a monopolistic situation. The MIC is currently discussing to
deprive the operation of …ber lines from NTT. However, NTT and their stockholders areheavily opposed to the idea because they have already used 2.7 trillion yen to install …berlines, and the infrastructure is one of the important sources of pro…ts for NTT.
This paper assesses numerically whether unbundling regulation prevents new entries
in the facility market and whether it induces monopolization.

3

Data Description and Variables Construction

3.1

Data Sources

This paper uses four data sets and matches them in a municipal level for analysis. The…rst data is unbundling regulation usage data. NTT East, a unique, regulated carrierin eastern Japan, provides data of the number of companies that used NTT’s …ber-optic
facility in station level between 2005 to 2009. The number of stations that NTT modi…ed
3

In general, CATVs do not share their lines to other …rms. This is because there is little scale economy
in CATV’s industry and their size is small. So, if user …rms want to borrow lines from CATVs, they
have to negotiate for each user …rms’customer. This cost signi…cantly large transaction cost. Electrics
companies o¤er a little bit wider area and they lend their lines to other …rms. However, compared to
NTT and government regulation system, their shared line is little.

9

to the …ber lines is also taken from this data.
The second source is the entry and exit data of …ber-optic network (FTTH) building markets. The Ministry of Internal A¤airs and Communications (MIC), a Japanese
regulation authority, provides an information and communications statistics database.
Using these …gures, we can detect which company built the …ber-optic premises between
a station and a home in an prefecture of monthly interval. Therefore, we can identify
when, where, and which …rms built the …ber-optic networks (FTTH).
The third data are …gures that examine CATVs and their coverage area. The Regional
Broadcasting Division in the MIC provides facility data of CATVs in a municipal level.
Using this data set, we can identify which CATVs enter which market. Combined with thesecond FTTH data set, we can deduce which CATVs built …ber-optic networks (FTTH)
in which markets. Most …rms that build …ber-optic networks provide HDTV programs
via …ber line, so the data includes …rms such as TEPCO (operated by The Tokyo ElectricPower Company) and JCN (operated by KDDI), which do not specialize in CATV.
The fourth source is market characteristics data. We use population, population
density, and income at a market level. The population and density data is taken fromthe 2005 Census, and income data is taken from a tax division of the MIC.

3.2

Construction of Variables

3.2.1

De…nition of Market

This paper combines the aforementioned four data sets in a municipal level. The municipal is the smallest de…nition of a market that we can construct using public data. The
data follows the de…nition of municipal in April 2009.4 962 municipals exist in east Japanin April 2009, and the average number of household is 25,924. (maximum is 40,910 and
4

There are many mergers of municipals in Japan from 2005-200910

minimum is 131)5 The reason we use the municipal level data is twofold: First, in ourmodel of dynamic entry game, we assume symmetric …rms. If we use a larger de…nition
than a municipal level, it is possible that the assumption of a symmetric …rm size is false.
For example, if we use a larger de…nition of a market, it is possible that 10-20 CATVs
enter in one market, but their actual sizes might be very di¤erent. If we divide large…rms with small areas, we can assume similar symmetric size in the area. Most markets
contain zero to two CATVs. Second, this paper considers competing networks between
CATV …rms. In other words, we assume consumers can choose …ber-optic lines froma few options, such as one NTT and one or two CATVs. If we use a larger data size,
the consumers’ choice set is di¤erent from an actual one. Using the municipal market
de…nition, in more than 95% of market, the consumer has to choose between two CATVs
or less, and this is plausible, considering the actual consumers’choice set.

3.2.2

Usage of Unbundling Regulation

One of the key variables in this paper is the usage of unbundling regulation. NTT East
advertises the number of …rms that used their …ber facilities. Because we cannot get thedirect quantity data in each market, we used this number as a measure of unbundlingregulation usage. We take two variables from this data set: usage of "station to home"and usage of "station to station" …ber-optic network. The "station to home" usage is
our most concern, which is the usage of …ber optic networks (FTTH) between the core
network to the home/o¢ ce. In each market there are several stations (average is 3.67).
The maximum number of usage …rms for the station in the market are taken as themarket’s usage measure, assuming several …rms enters in all markets. We guess there isa positive correlation between the usage and the number of families: in a large market,
the number of …rms which uses the NTT’s facility will increase. To account for this,5
We excluded Niigata and Kamiku Isshiki because they do not …t the de…nition of a municipal market
in April 2009.

11

we divide the number of …rms by the number of families. Therefore, in this paper,
the number of usage …rms per household is the measure of the market’s usage level ofunbundling regulation in the market.
The regulation system of unbundling itself is the same all over eastern Japan: NTT
has to lend all their facilities to every applicant at the same rental price determined by
the regulation authority. However, the usage level is di¤erent in each market. There areseveral sources that contribute to this variety. First, the regulation price is …xed in all
markets; however, the actual rental price could be di¤erent in each market. In general, theprice in a urban area is higher than a rural area, so the real rental price is relatively lower
in the urban area. Furthermore, the cost to build a …ber-optic network is also di¤erent ineach market. It costs a lot to build a …ber-optic network in some rural areas that have low
population densities or are isolated by mountains or seas. Even in some urban locales, if
the telephone/CATV lines are underground, the cost of building a …ber-network is higher
compared to installation via telephone poles. Therefore, in low real rental price markets,…rms easily use NTT’s premises and the number of usage …rms will increase. So, theusage level is di¤erent due to actual price. Second, the usage demand of consumers aredi¤erent in each areas. In general, NTT’s facilities are provided to all companies, whereas
non-NTT facilities are self-used. If a city has popular community-based TV programs or
ISPs, then those …rms may increase NTT’s usage. Third, the procedures and connection
condition is also di¤erent in each market. In a discussion between NTT and user …rms,
an argument ensued about problems such as how promptly NTT should react to user
…rms’applications. These factors may also a¤ect the usage-level variety.

3.2.3

Building Fiber-Optic Networks

In this paper, the main interest is to analyze if CATVs built their own …ber networks
between station to home (FTTH). The …ber network backbone had been installed all12over Japan more than ten years ago. However, with metal lines, the data transfer rate
decreases exponentially with the from the core network. Comparably, with …ber-optic
lines from core network to the home/o¢ ce, the transfer rate reduction disappears anda high data transfer rate is maintained. The line between a station to a home is called
the "last one mile," (the distance a station can cover is approximately one mile.) In theprocess of building …ber-optic networks, installing this "last one mile" makes up a largepart of cost. Therefore, this installment is of much interest to policy makers.
Which and where CATVs build …ber-networks is recorded by MIC. Information andCommunications Statistics Database in the MIC maintain records for which companies
build networks in which prefecture. Also, the MIC’s Regional Broadcasting DivisionDatabase can identify in which municipal the CATVs operate. By connecting these two,
we can observe when and in which market CATVs built a …ber-optic network. Because
we only have …rm/prefecture level …ber-optic entry and municipal level CATV activity,
we assume that CATVs decide to enter the prefecture level on their own networks. Since
most CATVs cover a few markets, we think this a plausible assumption.
NTT, the dominant carrier, also built a …ber-optic network which covered most ofJapan: NTT did not o¤er coverage to only 2 out of 962 markets in eastern Japan. NTT’sdata set show how many stations they installed with …ber optics. This number of stations
correlates to the number of …ber-optic lines. However, the number of stations depends
on both the number of lines and the population density. More stations are needed in a
low density area than a high density area, even if the number of lines o¤ered are equal.
Considering this aspect, we divided the number of stations by population density, anduse the number of stations per density as a quantity measurement of NTT’s optical …berlines.
The …ber-optic network technology is di¤erent between CATVs and NTT. CATV’s
main technology utilizes both Hybrid Fiber Coaxial (HFC) and Fiber To The Home

13

(FTTH). The Hybrid Fiber Coax is similar to FTTH. The di¤erence lies in that the
HFC uses …ber lines to connect the core network to a building area, and then uses themetallic lines after this point, while the FTTH uses …ber lines entirely. The HFC has
a slightly lower data transfer rate than the FTTH, but both o¤er similar speed. For
example, in June 2010, the NTT’s FTTH o¤ered 200 Mbps at 6720 yen and J:COM(CATV) o¤ered 160 Mbps at 6300 yen in Tokyo.

3.2.4

Market Characteristics

Because the decision of building the …ber-optic network also depends on market factors,
we used several market characteristics variables. We took two categories: demand andcost. As demand factors, number of households, number of people per household, andaverage income are taken. We also used population density as cost factors of the market.
Year dummies are added because the regulated price and building technology changes
with time, and also spurious relationship exits in variables. The number of households
is to measure the potential lines in the market. Ordinarily, the …ber lines are installed
one line per household. The number of people per household is de…ned by population divided by number of households. This variable represents the characteristics of households:
large households may want to install …ber lines more than small households. The average
income, de…ned as aggregate income divided by population in each market, shows therichness of the market; richer markets may have more demand on …ber-network premises.
The density is population divided by area in each market. It costs more to install lowerdensity markets. All market variables are …xed in one year, because it is di¢ cult to get
the data with time and also do not change much from year to year. In the estimationof dynamic game, we can reduce the state space by …xing unchangeable variables. We
took from the 2005 Japanese census the number of households, number of people perhousehold, density, and average income of the market. The income is taken from the tax

14division in the MIC of 2008. To adjust the unit problem, we divide all market characteristics by the mean of the variable. Assuming the e¤ects of these market characteristics
are concave, we take a log of all variables, after adding 1 to avoid an in…nity problem.

4

Evidences and Identi…cation

4.1

Linear Regression Models

First, this paper considers whether the usage of unbundling a¤ects the entry share of
CATVs into the …ber optic networks market, using linear regression models. We assume
the following estimation equation

ymt =

0+

1

usagemt +2stationmt + Xmt 3 + dm + dt + "mt(1)

where ymt is the percentage of CATV …rms that build the …ber-optic lines (the number
of CATVs, that build …ber-optic networks divided by the number of all CATVs), usagemt
is the number of …rms per household that used the NTT’s regulated facility between
station to home, which is our interest.6 stationmt is the number of the stations which
NTT adopted the …ber-optic lines. We use this variable as the measurement of quantityof NTT’s line. This variable is for distinguishing the usage e¤ect from NTT’s competitore¤ects. Xmt is market characteristic variables: number of households, number of people
per household, average income and density. dm and dt are the market and year dummy.
Considering the endogeneity of usagemt , we used the number of …rms which used
the regulated facility between station to station as the instrument. When …rms with no6

We divided by number of households, because oftenly when number of households increase, numberof user …rms increase. However, there are possibility the divsion of family caused the negative e¤etct,
because the number of user …rms increase concavely. We consider the e¤ects and checked robustness
using original …rms number and exponental conversion. We con…rmed the signi…cant negative e¤ects.

15

facility typically enter into the market, they use both station to home facility and station
to station facility. Some …rms use just station to home lines; these are called bottleneck
facility, because some of them have station to station facility. Therefore, the usage ofstation to station facility is related to the usage of station to home facility. However,the decision of CATV …rms as to whether they build the line between station and homeshould be unrelated to the usage of the facility between station and station, because thestation to station usage will not substitute the lines between home and station. We use
this as instrument variable and estimated the estimation equation.7
Table 8 depicts the results of linear regression model. This table reports whether the
unbundling usage of NTT facility decreases the entry share of CATVs in building …beroptic networks. The …rst column is ordinary random-e¤ects GLS regression. The usage
has no signi…cant results. CATVs will enter in the earlier stage considering the future
pro…ts, rather than later stage. The second column estimates allowing the endogeneityof usage, using 2SLS random-e¤ects IV regression. NTT’s competitor e¤ects become
signi…cant, but we cannot observe signi…cant usage e¤ect. The third column shows theresults of random-e¤ects tobit regression. In this regression, we consider the censored datae¤ects. The entry share (…ber CATVs divided by all CATVs) should takes between 0 and
1 from its de…nition. Considering these e¤ects, we used a tobit model. This estimation
does not consider the endogeneity because of limitation of tobit regression. The tobit
regression’s result shows the usage is signi…cantly negative. Therefore, we observed theusage of NTT facility decreases the CATV’s entry share in building …ber-networks.
7

The vailidity of instruments may arise. There is possibility of the inverse causality that NTT’s
construction of …ber decrease the usage of station to station. Considering about the instrument vailidity,
we are planning to add past usage of station to home as instruments in the future.

16

4.2

Probit Models

Next, using the discrete choice model, we consider how much the usage of unbundlinga¤ects the number of entry of CATVs to …ber-optic networks. We consider entry decisions
using probit and bivariate order probit models. First, we assume following estimation
equations with an IV probit model and consider the causality of usage on building …beroptic networks.

ymt = 1(ymt =0+ 1

usagemt + 2 Incumbentmt + 3 stationmt +Xmt 4 +dt +"mt > 0)(2)where ymt takes 1 if there is entry in the …ber-optic building market, otherwise 0.
Other variables are almost all the same and I used the same instruments with the linear regression model. Also, I added the number of current incumbents of the market
that built the …ber-optic lines (Incumbentmt ), and could not enter the market dummycompared to linear regression model because we used the instrument in the probit model.
Next, we con…rm the e¤ect of usage using a bivariate ordered probit model. The
bivariate ordered probit model also can solve the endogeneity problem. We assumed thefollowing estimation equations:ymt = 1(ymt = Xmt 0 +1u\sagemt = 1(\
usagemt = Xmt 0 +stationmt +1

2

stationmt +u\sagemt + dt + "mt > 0)
3

Instrument mt + dt +(3)
mt > 0)(4)

where ymt is the entry of CATV …rms that build their own optical …ber network.
u\sagemt is the number of …rms that used NTT’s facility. This is similar to previous
17usagemt but we discretise it in 7 bins to estimate by ordered probit model. Instrument mt
is the same with a linear regression model. Other variables are the same de…nition.
Our previous concern was the endogeneity between ymt and u\
sagemt , and the correlation
between "mt andmt causes the bias.

In this model, we simultaneously estimated thetwo probit/ordered probit models using a bivariate ordered probit model, allowing thecorrelation between "mt and

mt , and solving the problem.

Table 9 denotes the results of probit models. We could not add the market e¤ects for
IV or ordered probit model’s estimation limitation. The …rst column estimates the e¤ectsof the usage on whether CATVs enter in …ber-networks or not, using IV probit model. We
observed that the usage decreased the entry signi…cantly. The second and third columns
are the results of bivariate ordered probit model. By simultaneously estimating theordered probit model, we get the true e¤ect of removing the bias caused by endogeneity.
The results also suggest that the regulation usage decreased the number of CATVs thatbuild …ber-optic networks.

5

Unbundling E¤ects on the Dynamic Behaviors of
New Entrants

5.1

Structural Dynamic Entry Game ModelIn comparison to the above, in this section we consider a structural dynamic entry game.
By modeling the competition in building …ber-optic networks using dynamic game, we
get several good features. First, in the model of dynamic game, we can estimate dynamic
behavior of …rms. The telecommunication industry has natural monopolistic characteristics for its huge, sunk, up-front and …xed costs. The entrants consider future pro…ts andmake the decision to build the …ber-network facility over the long term. In the dynamic

18

model, we can model this aspect, compared to static models. Second, by this dynamic
structural estimation, we can estimate unknown parameters that ordinary estimation
methods cannot get. We have only entry and exit data of …ber-optic network, usageof unbundling regulation, and market characteristics in market level. Using that data,
we con…rmed the e¤ects of regulation on the entry share and the number of entries inprevious models. However, by adding a bit of economic assumptions, we can estimate
the pro…t function and sunk cost of entry. These estimates have important values fordesigning regulation and considering the social impact of the regulation on …ber-optic diffusion and competition. Furthermore, we can value the policy change by counter-factual
simulation using the getting parameters.8

5.2

Framework

There are m 2 f1; 2; 3; :::; M g independent geographic markets and t 2 f1; 2; 3; :::; 1g
discrete in…nite time periods. The unit of m is municipal and the one of t is one year.
There are two type of players

2 fCAT V; N T T g: one dominant carrier, called NTT,

and Nm CATV …rms compete to build "station to home" …ber-optic network in themarket m. (This game is a Mazzeo (2002) type (2 type competition) dynamic game.)
CATVs decide whether to build …ber-optic station to home lines to their clients or not,while NTT decides whether build station to home …ber-optic lines in its stations or not.
Because the exit from o¤ering …ber-optic network is very rare, we limit the …rms’option
as whether they enter or not. (We deleted the markets where a …rm quit o¤ering a…ber-optic network.)
The timing of the game is as follows. First, at the beginning of each time periodt, NTT and CATVs observe: 1.) the number of CATVs that have already constructed…ber-optic networks; 2.) the number of stations for which NTT has already adopted a
8

In the future revision, we are planning to conduct this.

19optical …ber network; 3.) usage of NTT’s facility by user …rms; 4.) market characteristics;
5.) market …xed e¤ect and 6.) current year. Second, CATVs decide whether they build
the …ber-optic network in the market and NTT decides whether they build its …ber-optic
network in additional stations, simultaneously. Third, entrant CATVs pay costs, andNTT also pays a cost if they decide to increase lines (stations) for …ber-networks. At theend of each period, incumbent CATVs get pro…ts and NTT also gets proportional to its
station. After the realization, market states evolve to next period. We should keep inmind that this model assumes a one year "time-to-build": the entrants pay the building
cost at time t, but they will earn pro…ts after t + 1.

5.3

State and Action Variables

Considering the competition of building …ber-optic networks and applying it to the model,
we de…ne here …ve state variables. Observing these state variables, CATVs and NTT
decide to build …ber-optic networks. The …ve state variables are the number of …ber-built
CATVs, the number of …ber-built NTT stations, usage of NTT facility, market dummy
and year dummy. We …xed the other market characteristic variables such as number ofhouseholds, density and income, because they will not change much over time and we
can decrease the state space. In this paper, we assumed the number of …ber-built CATVs
and the number of …ber-built NTT stations as endogenous state variables for which themodel determines the state. We also assumed usage of NTT facility, market dummy andyear dummy as exogenous state variables, for these states variables evolve outside themodel. We discretise the variables to reduce the state space: number of NTT’s …ber-built
stations for 4 bins, usage for 7 bins. The state of number of …ber-built CATVs are 3.
(0, 1 and 2) I also constructed 4 market dummy and 4 year dummy. Therefore the total
state space is 3

4

7

4

4 = 1344.

We assume action variables are binary. For CATVs, it is whether they build station to20

home …ber-optic networks for their clients. For NTT, it is whether they increase station tohome …ber-optic stations. In the most markets, CATVs did not exit …ber-optic network
service and NTT did not decrease the …ber-station. We can assume CATVs do notexit and NTT does not disinvest. We deleted markets in which CATV exited or NTT
disinvested.

5.4

Unobservable Heterogeneity

One of the important concerns of the relationship between CATV’s entry and usageof NTT’s facility is unobservable heterogeneity. If there are some unobserved market
characteristics, the estimated results are biased. For example, if for some reason markets
have di¢ culty installing …ber-network facilities, this causes an increase of installed lines’
usage and a decrease of entry of CATVs. To avoid this unobserved market heterogeneity,
we inserted the market …xed e¤ect variables. To address this, we used a two-stage …xed
approach. This is similar approach with Aguirregabria and Ho (2009), Collard-Wexler(2006) and Lin (2009). First we take the average entry number of …ber CATVs andNTT’s …ber station for each market. By regressing them of market characteristics, we get
residuals of each market. We discretised the residual for four bins, and get three dummies
to adjust the level of unobserved pro…tability. In the second stage, we added the three
dummies to the per period payo¤ function to remove the unobserved heterogeneous bias.

5.5

Spurious RelationshipIn the di¤usion process, key variables such as usage of unbundling, NTT’s …ber stationand entry of CATVs increased simultaneously. We may have another concerns on the
spurious relationship. To remove this e¤ects, I added year e¤ects in pro…t function as
endogenous variables. It increases with year and stops in 2009. We can evaluate the21usage e¤ects avoiding year e¤ects by this.

5.6

Per Period Payo¤ Function

We assumed linear and reduced-form payo¤ function. Linear forms require less computing
time and these assumptions are also common in other papers.
imt =

Xmt X
| {z }

Revenues of FTTH service

Zmt Z| {z }

Costs of FTTH serviceg(N imt ; N imt )|{z}Competitors’e¤ect

Gmt G| {z }

Regulated usage e¤ect

where Xmt is demand factors of the market (number of …rms, number of people perhousehold and average income), Zmt is cost factors of the market (density), g(N imt ; N imt )is the competitors’e¤ect of similar services (number of other CATVs that provide …beroptic services and number of …ber stations of NTT), and Gmt is the unbundling regulatione¤ects. We took facility usage of NTT …rms. We used number of …rms which used NTT’s
facility as measurement. In this paper, we assume CATVs are symmetric and the sizeof NTT’s stations are also identical. These …rms conduct Cournot type competition,and the regulation access rates’ e¤ects has already re‡ected the usage of unbundlingregulation. We assumed …rms pay sunk cost to enter, and get zero pro…t if they do notenter.
On the competitor e¤ect g(N imt ; N imt ); we didn’t assume the proportional e¤ects
because the …rst competitor’s e¤ect is larger than the second competitor’s in CATVs
competition. We also assume the CATV’s entry a¤ects NTT’s decision, and NTT’s
construction a¤ects CATV’s decision. Re‡ecting these, the function of g(N imt ; N imt )becomes the following:

22

5.7

g (N imt ; N imt ) =

CAT V
1

presence of …rst CATV that constructed FTTH

+

CAT V
2

presence of second CATV that constructed FTTH

+

NT T
3

# of NTT’s …ber stations

Firms Behaviors and Markov Perfect Equilibrium

Under the above assumptions, CATVs and NTT simultaneously chooses their actions tomaximize the present values of the sums of future pro…ts. We can de…ne value function
as follows,

V (Sit ) = max E[ it (ait ; Sit ) +ait 2AZ

V (Sit+1 )dF (Sit+1 jSit; ait )]where ait is an action variable of …rm i, type

and time t. Sit is the state variable

for …rm i and time t. Following previous literature, we take the discount factor
because the data is annual. A Markov strategy is a mappingi (Sit ) 7

as 0.95! f0; 1g 2 Ait ,where Ai is the …rm’s action set. If CATV …rms enter in or NTT increased the …berstation, it is 1; otherwise, 0.
We can rewrite the above value function, conditional on the strategy,

V (Sit j ) = max E[ it ( ; Sit ) +ait 2AZ

V (Sit+1 j )dF (Sit+1 jSit; )]Then a set of Markov strategy ( ) is a Markov Perfect Equilibrium if and only if,
for all i, Sit , and alternative strategy

V (Sit j it ;

0

it ;

satis…esit )V (Sit j it0 ;
23

it )

5.8

Exogenous Transition Probability

Endogenous state variables, number of …ber-built CATVs, and number of …ber-built
NTT stations, evolve within the model and their transition probabilities are determinedby rational pro…t maximizing behavior of CATVs and NTT. Compared with these, usageof NTT facility’s transition probabilities, market dummy and year e¤ect are determined
exogenously.
First, we construct the transition probability matrix of usage of NTT …ber lines from
actual movement. Each element of transition probability is calculated from the following
equations using actual observations. These calculations are similar to Dunne, Klimek,
Roberts and Xu (2009) or Elejalde (2009).

0[
Prob(usage
jusage) =P(m;t) 1(usagem;t+1 = usage

P0

and usagem;t = usage)(m;t) 1(usagem;t = usage)

In this dynamic game settings, we assume that CATVs and NTT perfectly predict
the future usage of NTT facility and decides their entry decisions.
Second, we assumed market dummy is …xed over the year, and it does not change.
Also, year e¤ects increase with time, but stop in 4 years after. These transition is common
knowledge for players.

5.9

Estimation Methodology

In this paper, we used Aguirregabria and Mira (AM) (2007)’s Nested Psuedo Likelihood
estimation (NPL). The estimation methodology is the re…nement of Hotz and Miller(1993)’s 2-step type Psuedo Maximum Likelihood Estimation (PML) by Aguirregabria
and Mira (2002). AM(2007) has robust characteristics with small sample bias and it canestimate under the multiple equilibrium.
24

The value function is de…ned as

V (xt ) =Z

Z

maxf (xt ) + t (at ) +V (xt+1 )dF (xt+1 jxt; at )gg(d t )From action observable, we can construct CCP(conditional choice probabilities),pit (ait jxt ; t ) = Pr( it (xt ; it ) = ait jx) =it

I(.) is the indicator function, and we assumetZ

I( it (xt ; it ) = ait )dF ( t )N (0; ):

Nested Pseudo Likelihood estimator is calculated using the following procedures.
Step 1: Set initial probability. We took nonparametrically the initial CCP from thedata set, following AM(2007), as

c0 (ait jx) =P

P P= ait ; x = x)t Pi I(aPti I(x = x)

Step 2: Given a CPP(P k ), construct the pseudo maximum likelihood function andget thek+1

by maximization

k+1= arg max
2

where

P PP
m

t

i ln

(aimt jximt : P k ; )is the choice probability function.

Step 3: Based on P k and thek+1

in the step 2, update the probability function

according to[
k+1 (a jx) =Pj(aj jximt : P k ; k+1 )for all aj 2 A and x 2 X:
25

Step 4: Continuously updates Step 2 and Step 3 till ’s distance converges. We took
the criterion to 1e-3.
These are direct application of AM(2007).

5.10

Implication

Table 10 shows the estimation results of the dynamic structural model. The usage-e¤ectcoe¢ cients on CATVs’ pro…t were signi…cantly negative, and on NTTs’ pro…ts weresigni…cantly positive. The results …nd that the regulation usage decreased the CATV’s
pro…ts on building of …ber-optic networks, therefore it decreases their incentives of CATVs
to enter the markets via pro…ts as reduced form results suggest. Compared to this, NTT’s
pro…ts will increase if the unbundling usage increase, and they have incentives to increase
their …ber by unbundling regulations. (This suggests that NTT can make more pro…ts
in infrastructure markets if it lends to unbundling regulation users. However, this does
not necessarily imply the increase of total pro…ts of infrastructure and service markets.)
For further analysis, we can improve or expand the results. We divided the market
dummies by four, due to the state space problem, but more smooth adjustment will
improve the estimates like sunk cost of NTT and market characteristics, which are thedi¤erent sign with our prediction. Also, using this values, we can evaluate counter-factual
analysis on policy issues:how many CATVs build their own …ber lines if regulators quit
unbundling like FCC in the US.

6

Conclusion

This paper studies the e¤ects of competition law on other related markets that are
not targeted by the law. One of important analyses on unbundling regulation is the26

e¤ects on compentition structure in infrastructure markets, which previous literature
have not studied well. This paper identi…ed the e¤ects using unique events of …ber-lines
infrastructure formation, and estimated how the unbundling regulation usage changed
the CATVs’entry behaviors. Japanese data set is utilized because it has experienced …berlines penetration and continued unbundling regulation, in contrast with other countries.
This study …nds that the unbundling regulational usage block new entry and hasmonopolization e¤ects for regulated carriers on building …ber-optic networks. Using theentry data of CATV …rms in building …ber-optic networks and the usage data of regulated…ber-optic facilities, this paper structurally estimates the pro…t function and the entry
sunk cost, assuming dynamic entry game. Estimation results suggest that the regulation
reduces the pro…t of new entrants, and prevents to build their own …ber-optic networks.
Quitting to build their own lines is fatal decision for CATVs because they may go extinct
in the near future if they cannot o¤er high speed internet or HD TV programs via …berlines.9
As a policy implication, this paper suggests that there is a possibility that competition
law distorts market discipline and reduce the competition in related markets. New …rms
enter markets seeking monopolistic pro…ts. If regulations remove the monopolistic gains,…rms will not enter the markets. As an example, unbundling regulation is the doubleedged sword. It may lower the price in service markets. However, in the di¤usion
stage of new technology, unbundling regulation strengthens the shares of regulated …rms
and may destruct competition in facility market. Japan was one of the ironic examples
where the regulated carrier monopolized the …ber-optic facility market, whereas normallyunbundling regulation removes "natural monopoly" of the lines.
This prevention of competition has a huge risk. For the next several decades, Japanesecitizens may have to pay high maintenance fees to NTT, use the unwanted technology
9

There is also possibility that those CATV …rms borrow …ber lines from NTT and survive markets.
But nobody knows the future.

27

provided by NTT, and endure the narrow variety of connection services o¤ered by thecompany. The Japanese government should work with NTT to decide the maintenancefees considering NTT’s claims, user …rms claims, and consumer bene…ts for the next
few decades. Whether the bene…ts of the low unbundling price in the di¤usion period
outweighs the risks is still under question.
For the …rst time in half a century, countries all over the world are changing their
metallic telephone lines to …ber-optic lines. Policy makers are required to make a big
decision as to whether they will continue unbundling regulation on the new lines or not.
The U.S. chose to abandon unbundling. Japan continued the regulation. Findings fromJapanese experiences suggest that unbundling in technological change reduced competition in telecommunication facilities in order to gain ‡eeting bene…ts.

28

References[1] Aguirregabiria, Victor and Chun-Yu Ho 2009, "A Dynamic Oligopoly Game of the
US Airline Industry: Estimation and Policy Experiments" Forthcoming, Journal of
Econometrics[2] Aguirregabiria, Victor and Pedro Mira 2002, "Swapping the nested …xed point algorithm: A class of estimators for discrete Markov decision models." Econometrica
70, 1519-1543.
[3] Aguirregabiria, Victor and Pedro Mira 2007, "Sequential estimation of dynamic
discrete games." Econometrica 75, 1-53.
[4] Bourreau, Marc and Pinar Dogan 2003. "Unbundling the Local Loop," European
Economic Review, vol. 49, pp. 173-199.
[5] Collard-Wexler, Allan. 2010, "Demand Fluctuations in the Ready-Mix Concrete
Industry," Forthcoming, Econometrica[6] Crandall, Robert W., Ingraham, Allan T. and Singer, Hal J. 2004 "Do Unbundling
Policies Discourage CLEC Facilities-Based Investment?" The B.E. Journal of Economic Analysis & Policy, Vol. 4, pp. 1-23.
[7] Dunne, Timothy, Klimek, Shawn D., Roberts, Mark J. and Xu, Daniel Yi. 2009
"Entry, Exit, and the Determinants of Market Structure," NBER Working Paper
No. 15313.
[8] Economides, Nicholas, Katja Seim, and V. Brian Viard. 2008 “Quantifying the Bene…ts of Entry into Local Telephone Service.”NET Institute Working Paper #08-01,
forthcoming, RAND Journal of Economics.
[9] Elejalde, Ramiro de, 2009. "Local Entry Decisions in the US Banking Industry" ,mimemo[10] Greenstein, Shane and Mazzeo, Michael. 2006 "The Role of Di¤erentiation Strategy
in Local Telecommunication Entry and Market Evolution: 1999-2002," Journal ofIndustrial Economics, v. 54, iss. 3, pp. 323-50[11] Hori, Keiichi & Mizuno, Keizo, 2006. "Access pricing and investment with stochastically growing demand," International Journal of Industrial Organization, Elsevier,vol. 24(4), pages 795-808, July.
[12] Jorde T.M., Sidak J.G. & D.J. Teece 2000 "Innovation, Investment, and Unbundling", in Yale Journal on Regulation, vol. 17, pp. 1-37.
[13] Lin, H., 2008, Quality Choice and Market Structure: A Dynamic Analysis of Nursing
Home Oligopolies. Manuscript. Indiana University. Business School.

29[14] Toivanen, O., and M. Waterson. 2005 "Market Structure and Entry: Where’s the
Beef?," RAND Journal of Economics, 36(3), 680-699.
[15] Ingo Vogelsang and Bridger Mitchell. 1997 "Telecommunications Competition : The
Last Ten Miles," AEI Press

30

Figure 1: Share of Dominant Carrier in Building FTTH Line

Table 1: Regulation on the Telecommunication Industry
US Japan Germany France
UK
Metallic Line
R
R
R
R
R
1
Fiber-optic Line UR"R" means Regulated, "U" means Unregulated.
*1 The US abolished the regulation to induce investment in 2003

Table 2 :Share of FTTH in June 2009 (Top 5 Countries)
US Japan Germany France UK# of Broadband Subscriber 81.2 30.9
24.1
18.6
17.7
Fiber-optic Share
6%
51%
0%
0%
0%
Broadband subscriber is in millions. Source: OECD31

Figure 2: Industry Structure

Table 3: Number of CATV …rms that operates FTTH (Firm Level)2005 2006 2007 2008 2009
Total Number 12
28
29
40
42
Enter
16
1
12
4
Exit
0
0
1
2

Table 4:Number of CATV Firms (Market Level)
2005
2006
2007
# Firms CATV FTTH CATV FTTH CATV FTTH
0
542
912
591
858
578
852
1
300
50
272
94
276
99
2
94
0
75
10
85
11
3
21
0
18
0
17
0
4
4
0
5
0
4
0
5
1
0
1
0
2
0
>5
0
0
0
0
0
0
Max
5
1
5
2
5
2

32

2008
CATV FTTH
572
792
283
147
84
21
17
2
5
0
1
0
0
0
5
3

2009
CATV FTTH
542
772
299
164
95
24
19
2
6
0
1
0
0
0
5
3

Figure 3: Market De…nition: Eastern Japan

Table 5: Number of Stations of NTT
2005 2006 2007 2008 2009
Number 3261 3414 3527 3691 3762

33

Table 6: Summary Statistics (962 markets, 5 years)
Mean# of families
25924# of …rms that uses NTT’s facilities (home to station)
5.05# of …rms that uses NTT’s facilities (station to station) 6.41
# of station
3.67
usage per household of home to station.0005
usage per household of station to station.0007# of CATV …rms
.56
# of FTTH entry of CATV …rms
.15
Entry rate in FTTH by CATV …rms
.26

Table 7: Market Characteristics# of …ber# of households station to home
CATV
0
19402
3.9
1
62164
10.9
2
12665021.3
3170145
23.8

34

Std
44280
6.09
6.70
3.66
.0008
.0010
.79
.39
.40

Min
131
0
0
0
0
0
0
0
0

Max
40910
69
74
22
.140
.140
5
3
1

station to station # of CATVs # of stations
5.3
12.3
24.2
24.8

0.4
1.4
2.6
3.25

3.3
5.5
7.9
7.5

Table 8: Results of Linear Regression Model
Usage per household
Number of NTT’s…ber station per densityTra¢ c Demand
Number of People
per household
Number of household
Density
Average Income
Const(1) GLS
0.00(0.01)-0.01(0.02)-3.77***(1.32)
1.50***(0.49)
3.79***(1.33)
0.02(0.04)
0.04(0.15)-5.50***(1.89)

p(2) 2SLS
0.00(0.01)-0.08**(0.02)-3.79***(1.32)
1.51***(0.49)
3.81***(1.33)
0.02(0.04)
0.04(0.16)-5.52***(1.89)

p(3) Tobit-0.07***(0.02)-0.11***(0.05)-17.3***(1.92)
6.51***(0.70)
17.2***(1.93)-0.18***(0.07)-0.32*(0.18)-24.8(2.77)pYear DummypppMarket Dummyp
Endogeneity 2p
Censored 3
Adjusted R2
0.06
F testWald test
35.6
34.9
356.4
Log likelihood-1620.0
Note: Dependend variable is the share of CATV …rms that build …ber-optic networks*1: usage is the number of …rms per household that use the regulated facility
between home and station*2: In the IV estimation, this paper uses the number of …rms that use
the regulated facility between station and station as the instrument of usage*3: In the Tobit estimation, the upper and lower bounds are 0 and 1, each.
* is signi…cant at 10% , ** is at 5% and *** is at 1%. Parenthis is standard deviation.

35

36

p

p

(2) Simultaneous Bivariate Ordered Probit
Usage per household
CATV’s Entry in FTTHof NTT’s Facility-0.34***(0.17)
0.61***(0.04)-0.77***
0.02(0.22)(0.07)
0.15
0.40***(0.12)(0.04)-1.80-0.08(3.80)(1.60)
1.40-1.08(1.36)(1.61)
1.77
0.43(3.82)(0.55)
0.43***
0.66***(0.18)(0.05)
1.86***
0.36*(0.41)(0.20)
0.10(0.19)

Year Dummyppp
Endogeneity 2
Wald chi2
136.7
Log likelihood
-4939
-2980
rho
0.10
Ch2
0.26
Note: * In the IV estimation, this paper uses the number of …rms that use the regulated facility
between station and station as the instrument of usage* is signi…cant at 10% , ** is at 5% and *** is at 1%. Parenthis is standard deviation.

Const

Average Income

Number of people
per household
Density

Number of households

Incumbent CATV
which build FTTH
Number of NTT’s
Fiber Station per DensityTra¢ c Demandp-0.47***(0.15)-0.77***(0.23)
0.27**(0.13)-5.39(3.58)
2.56*(1.36)
5.21(3.59)
0.50***(0.18)
2.59***(0.51)-9.26(5.03)

Usage per household
Instruments

CATV’s Entry in FTTH

Dependent Variable(1) IV Probit

Table 9: Results of Probit Models

37

Table 10: Estimation of Dynamic Game of Infrastructure Construction(1) CATV’s Pro…t Function to Build Fiber Network (2) NTT’s Pro…t Function to Build Fiber Station
Estimate
Standard Errors
Estimate
Standard Errors
First Fiber-CATV-0.06929**
0.002929
0.001791**
0.0007457
Second Fiber-CATV-0.3786**
0.03561-0.0003890
0.001009
Sunk cost to enter of CATV
-0.2760 **0.02178
Sunk cost to bulid …ber station
0.04368**
0.007629
NTT’s number of …ber station
0.00001
0.00001
0.01661**0.0003175
Usage E¤ect-0.06984**
0.006866
0.003442**
0.0009264
Market Dummy 10.1450**0.01713-0.03028**
0.001618
Market Dummy 2
0.2006**0.01512-0.02853**
0.0005787
Market Dummy 3
0.1550**0.012450.008039**
0.0004306
Year E¤ects
0.04930**
0.006490-0.03035**
0.0008791
Household-0.01727**
0.002707
0.0009409**
0.0001923
Income-0.17470**
0.01088-0.05392**
0.002544
Density
0.01547**
0.003036
0.0009769**
0.0001607