Access regulation and infrastructure investment in the mobile telecommunications industry

Telecommunications Policy 35 (2011) 907–919

Contents lists available at SciVerse ScienceDirect

Telecommunications Policy URL: www.elsevier.com/locate/telpol

Access regulation and infrastructure investment in the mobile telecommunications industry Jihwan Kim a, Yunhee Kim a, Noel Gaston b, Romain Lestage c,d, Yeonbae Kim a,n, David Flacher c a

Technology Management, Economics and Policy Program (TEMEP), College of Engineering, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-747, Republic of Korea Globalisation and Development Centre and School of Business, Bond University, Gold Coast, Queensland 4229, Australia c Centre d’Economie de l’universite´ Paris Nord, Paris 13 University, 99 avenue Jean-Baptiste Cle´ment, 93430 Villetaneuse, France d France Telecom, Orange Labs, 38-40, rue du Ge´ne´ral Leclerc, 92794 Issy-les-Moulineaux, Cedex 9, France b

a r t i c l e i n f o

abstract

Available online 5 October 2011

While mobile virtual network operators (MVNOs) increase competition in the mobile telecommunications industry, granting market access to MVNOs may have unwanted consequences. In particular, infrastructure investment by incumbent mobile network operators (MNOs) may be smaller. This paper examines the effects of MVNO entry and access regulation on the investment behavior of MNOs. It uses firm-level data for 58 MNOs in 21 OECD countries during 2000–2008. The results suggest that mandated provision of access is related to lower investment intensity of MNOs, while voluntary access provision has no effect. Although reduced investment incentives do not necessarily correspond to under-investment, this underscores the need for those countries where MVNOs are provided access to address the issue of investment incentives. & 2011 Elsevier Ltd. All rights reserved.

Keywords: Mobile telecommunications MVNO MNO Access regulation Investment Competition

1. Introduction The degree of competition in mobile telecommunication markets continues to be an important policy issue. National policy-makers seek to improve consumer welfare by accelerating network investment and by fostering a more favorable environment for competition in these markets. Government policy in this regard is made difficult by limited radio spectrum and the large investment required for network deployment. The latter feature makes it difficult for new operators to enter and compete. In recent times, some national regulatory bodies have allowed mobile operators which do not possess their own frequency spectrum and infrastructure to lease the network facilities of mobile network operators (MNOs). These new mobile operators are referred to as mobile virtual network operators or MVNOs.1 Ergas, Waters and Dodd (2005) provide two justifications for providing mandatory MVNO access to the mobile telecommunications market. First, MVNOs may increase competition so that the prices of mobile services fall, mobile penetration accelerates, and the quantity of services supplied increases. Secondly, services-based entrants may eventually

n

Corresponding author. Tel.: þ82 2 880 9163; fax: þ 82 2 886 8220. E-mail address: [email protected] (Y. Kim). 1 The International Telecommunications Union (ITU, 2001) defines an MVNO as an operator that services mobile communications to subscribers without its own airtime and licenses granted by the government. For a summary of the existence of MVNOs and the regulations across countries, see Table 1. Note that the period for MVNOs and regulations may differ depending on the definitions and subsequent scope of MVNOs. 0308-5961/$ - see front matter & 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.telpol.2011.08.004

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invest in building their own infrastructure after gaining a sufficiently large customer base, as implied by the ladder of investment or stepping stone hypothesis (Cave and Vogelsang, 2003; Cave, 2006; Bourreau, Drouard, & Ferrali, 2008).2 In countries where service-based operators have long been established, mobile bills have become more affordable and new services have been offered (ERG, 2006). Serviced-base entry is generally regarded as a contributing factor to the reduction in mobile prices (Informa, 2005; Ovum, 2005). However, evidence to support this is scarce and inconclusive. For example, Kalmus and Wiethasu (2010) maintain that the introduction of MVNOs does not increase competitive pressure in the retail market per se. ERG (2006) argues that the competitive effects may not be due to MVNOs, but to other observed and unobserved factors. More importantly, there are also growing concerns regarding the impact of MVNOs and the related regulation on the investment incentives of MNOs. First, MVNO access can induce spillovers that affect MNO incentives to adopt new mobile technologies or to improve their existing networks (Foros, 2004; Woroch, 2004; Kotakorpi, 2006). Secondly, access regulation involves asymmetric risk sharing between the MNOs and MVNOs (Guthrie, 2006). The countries that have allowed MVNOs in the market are mostly in Europe. Notwithstanding, the experience of these countries provides lessons for those countries contemplating granting access to MVNOs.3 Unlike the unbundling of fixed lines, the literature on MVNOs appears to have paid relatively less attention to the investment incentives of MNOs even though their investments are crucial for mobile telecom services. The present paper tries to fill this void. As Table 1 shows, MVNO entry in many countries is granted in many non-mandatory ways, but is mostly via voluntary provision of access by MNOs. If granted market access, MVNOs can enjoy the benefits of entering while being free from the burden of infrastructure investment. This leads to the question of whether the entry of MVNOs is likely to affect the investment of MNOs. This paper considers the dynamic efficiency perspective by examining the impact of MVNOs and access regulation on MNO investment. The empirical results suggest that mandated access regulation reduces the incentive to invest for MNOs. The paper proceeds as follows. The next section provides the theoretical background. Section 3 describes the data and the econometric model. Section 4 reports and discusses the estimation results and the final section provides concluding observations and outlines some policy implications. 2. Theoretical background Few studies have dealt with how the presence of MVNOs affects MNO investment incentives.4 One exception is Foros, Hansen, and Sand (2002) which explores how a new non-facility based entrant affects the investment incentives of two facilities-based firms. In a game-theoretic setting, it is shown that a roaming quality improvement made by MVNOs reduces the investment of facilities-based firms. The present paper is the first empirical study that specifically focuses on the economic impact of MVNOs on MNO investment in the mobile telephony market. A related and recent literature has developed on the relation between regulation and innovation in the telecommunications ¨ sector. Roller and Waverman (2001) show that investment in the telecommunications industry is crucial for social welfare and long-run economic growth. Consequently, regulation in the telecommunications market may impose welfare costs by delaying deployment of innovative technologies or by reducing the amount of investment (Alesina, Ardagana, Nicoletti, & Schiantarelli, 2005). Conventional wisdom suggests a trade-off between the static efficiency associated with current competition and the dynamic efficiency related to current investment (Flacher and Jennequin, 2008). The promotion of dynamic efficiency that may involve risky innovations and investments may reduce static efficiency. For example, entry barriers that limit competition and market dominance that allow firms to charge prices over cost may facilitate dynamic efficiency (Bauer and Bohlin, 2008). 2.1. Access regulation The earlier experience of local loop unbundling in the United States shows the trade-off between the regulatory effects on the short-run market and long-run facilities-based investment (Bauer and Bohlin, 2008). Unbundling policies focused on the static side of efficiency by allowing service-based entry. However, policy-makers paid considerably less attention to investment incentives (Jorde, Sidak, and Teece, 2000; Hausman and Sidak, 2005). Jorde et al. (2000) argue that the unbundling of network elements diminishes incentives for both service-based entrants and facilities-based operators to invest in existing facilities and new technologies. Likewise, Waverman et al. (2007) argue that regulation on unbundling has a negative effect on investment. Although there is some dissent on the impact of unbundling regulation, most studies conclude that unbundling reduces investment incentives in advanced internet infrastructure.5 The same concerns for local loop unbundling of the fixed-line internet have emerged for MVNOs. When there is access granted to MVNOs in the mobile telephony market, there is a trade-off between facilitating competition in services and prices and providing incentives to invest in mobile network facilities (Dewenter and Haucap, 2007). Sections 2.1.1 and 2.1.2 discuss the literature on the fixed-line internet market and how it bears upon the issues of access regulation, MVNO entry and MNOs’ incentives to invest. Two economic characteristics of access regulation are addressed: investment spillovers and the asymmetric allocation of risk and returns on irreversible investments. 2 3 4 5

Some researchers dispute this hypothesis, for example, Hausman and Sidak (2005) and Waverman, Meschi, Reillier, and Dasgupta (2007). For example, in South Korea where MNOs denied access provision to MVNOs for many years, MVNOs will finally enter the market in 2011. For a comprehensive review of the theoretical and empirical studies on access regulation and investment in broadband, see Cambini and Jiang (2009). Wallsten (2006) is a representative study which shows that extensive unbundling mandates reduce broadband investment incentives.

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2.1.1. Investment spillovers An MVNO with access to the mobile network infrastructure can undermine the ability of an investing firm to appropriate the benefits from investments. The provision of access to an MVNO creates spillovers that arise from MNO investment in replacing old facilities, adopting new mobile technologies, or improving the current network infrastructure. When an MVNO is able to access an MNO’s network, improvements in quality or benefits from new technologies used in the network make MVNO service offerings more attractive. In this manner, the MVNO can share some of the positive outcomes from MNO network investment. Consequently, the MNO may face lower returns from their investment (see, e.g., Foros, 2004; Woroch, 2004; Kotakorpi, 2006). Griliches (1992) emphasizes that investment spillovers are different from knowledge spillovers. In fact, under certain conditions in the mobile access market, MNOs may be willing to give access to their networks voluntarily (Banerjee and Dippon, 2009). Some moderating factors may mitigate incentive problems stemming from spillovers. For example, a part of the spillover may be recovered if the MVNOs can afford a higher access fee charged by the MNO. Foros (2004) shows that without accessprice regulation and with a competitive downstream sector, a vertically integrated firm has an incentive to invest because its downstream rival is more efficient in offering services. With access price regulation, an incumbent may under- or over-invest depending on a downstream entrant’s ability to provide higher quality services. Similarly, Kotakorpi (2006) shows that without access-price regulation, investment spillovers may positively affect investment because an incumbent makes profit in the access market. However, these predictions are reversed in some situations. For example, if a service-based entrant is less efficient at offering services, then an MNO may lower the level of investment or deny access. Insufficient differentiation of MVNO services lowers profits for the MNO as the competition effect outweighs revenue from the access market. Therefore, MNOs may seek to deter MVNO access (Dewenter and Haucap, 2007). When MNOs refuse to make an access provision agreement with MVNOs, regulatory intervention can force them to allow market entry by MVNOs. Mandatory access provision to services-based downstream rivals may result in more intense competition in the retail market. Moreover, spillovers that benefit rivals shift some of the incumbent’s profit to the service-based competitor. This may reduce investment and deployment of the network (Woroch, 2004). Kotakorpi (2006) shows that when forced to provide access at a low price, an incumbent cannot secure a profit from access provision. In contrast, MVNOs enjoy benefits from MNO investment. Spillovers discourage investment and the level of investment is lower than in the absence of regulation. Therefore, access regulation will exacerbate any tendency to under-invest by MNOs. 2.1.2. Asymmetric allocation of risk and the return on irreversible investments The second characteristic of access regulation, which stems from the irreversible nature of the investment, is the asymmetric allocation of risk of consequent returns (Jorde et al., 2000; Guthrie, 2006).6 The degree to which capital is physically recoverable and is industry-specific affects the irreversibility of any capital expenditure. For example, investment in fixed landline networks, such as in copper or fiber-optic cables, requires significant cost recovery (Pindyck, 2004).7 For highly industry-specific capital, it is difficult to sell capital. In all likelihood, this situation applies to the mobile telecommunications industry where a number of the licensed owners of radio spectrum are subject to government regulation. The risk associated with irreversible investments is exacerbated when combined with long lead times, long physical life-times, and large economies of scale (Guthrie, 2006). These factors encompass the fundamental reasons that investing firms have difficulty in adapting their capital stocks to changes in the regulatory environment or to technological progress once investments have been made. Access regulation that allows MVNO investment flexibility also exposes MNOs to considerable risk. If investment in facilities is largely irreversible, MNOs may bear heavy sunk costs due to the risks associated with changed or volatile market conditions. Unlike MNOs, MVNOs leasing an MNO’s network do not need to make such irreversible investments. Moreover, downstream competitors and regulated provision of access to MVNOs may distort the allocation of risk between MNOs and MVNOs. If market conditions are unfavorable, an MVNO may not lease an MNO’s network. MVNOs will only seek access when market conditions are favorable. The MVNO shares the upside benefits with MNOs by acquiring access but can avoid the downside risks by abandoning access or deciding not to lease network facilities. Therefore, access regulation allocates more risk to network operators and less to service-based entrants, leading the operators to expect relatively lower returns on investments (Jorde et al., 2000; Guthrie, 2006). Overall, due to the nature of irreversible investments, access regulation creates an investment disincentive for MNOs by creating an asymmetric allocation of risks and payoffs. In some cases, the provision of access is mandated and in other cases, access may be voluntarily granted or negotiated by MNOs. Banerjee and Dippon (2009) show that it may be profit-maximizing for MNOs and MVNOs to have voluntary strategic partnerships based on resale, product differentiation, and re-branding. This suggests that MNOs that sell wholesale services to MVNOs may not necessarily lose sales in downstream retail markets. However, while it may be the case that voluntary relationships arise only if MVNOs add value by widening and/or deepening MNO-served markets, access might also be granted to MVNOs in order to avoid the costs associated with more heavy-handed policy mandates. 6

See also, Hausman (2000) and Pindyck (2004). According to Pindyck (2004), the resale possibility and value of industry-specific equipment are closely connected to economic conditions of the industry that a selling firm belongs to. Unfavorable conditions may force firms to divest by removing and reselling the equipment. This may drive others to resell their equipment. Consequently, no firm would want to buy the equipment, which makes the investment in such equipment effectively irreversible. 7

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The preceding discussion suggests the hypothesis. Hypothesis. Access provision leading to MVNOs entry induces lower investment by MNOs. Moreover, this effect is stronger for mandatory as compared to voluntary access provision. This paper focuses on the investment problem of network-operating incumbents and addresses the overall effect of MVNOs and access regulation regardless of market conditions, specific regulations, MVNO capabilities, or MNO strategies that may compensate for any loss due to spillovers. Therefore, it is expected that when MNOs are forced to allow MVNO access to their networks, their incentive to invest decreases relatively more than when they are not. 2.2. Competition among mobile network operators and investment incentives It is important to examine the relationship between market competition and investment by MNOs. The literature on competition-innovation provides an extensive treatment of the subject.8 Arrow (1962) shows that a monopolist has fewer incentives to invest in process innovations than a competitive firm does, because the greater profit a firm can earn from an old technology, the greater the disincentive to implement a new technology. On the other hand, Gilbert and Newbery (1982) suggest that an incumbent in a less competitive market may make greater investment than it would in a more competitive market. Gilbert (2006) addresses investment in product innovations that can be associated with investment in adopting advanced mobile technologies. According to Gilbert (2006), replacement of an old product with a new product leads to the same consequences outlined by Arrow (1962). However, this effect is attenuated if a monopolist can add a new product to its portfolio (and thus create higher returns) rather than simply replace an old one. In the mobile telephony market, entry is regulated through licensing. Since entry does not remain solely a potential entrant’s decision, incumbents’ investment may depend upon entry regulation. Following Arrow (1962), MNOs would thus have fewer incentives to invest in innovation if competition is less intense. It follows from this discussion that competition is more likely to provide greater incentive for investment in networks under the two conditions suggested by Gilbert (2006). First, competition lowers the pre-investment profit, and hence, it induces an increased incentive to invest for incumbents. Secondly, the advanced mobile services rendering the old ones obsolete reinforce Arrow’s (1962) view, particularly if competition is weak. For example, as 3G replaces 2G, MNOs in less competitive markets have a lower incentive to invest. Overall, however, the theoretical literature is inconclusive about whether market competition increases or decreases investment. One strand of the literature identifies the positive role of greater competition that leads firms to reduce slack (Hart, 1983; Schmidt, 1997) or to enhance their market position (i.e., an escape-competition effect) (Gilbert and Newbery, 1982; Aghion, Harris, Howitt, & Vickers, 2001; Aghion, Bloom, Blundell, Griffith, & Howitt, 2005). Another strand stresses that intensified competition may reduce post-investment profits and thereby create disincentives for investment (i.e., a Schumpeterian effect) (Grossman and Helpman, 1991; Aghion and Howitt, 1992). Therefore, competition may exert conflicting effects on investment. Recently, Aghion and Howitt (1998) and (Aghion et al., 1999, 2001, 2005, 2009) have developed models incorporating the two effects. For a step-by-step innovation, the escape-competition effect prevails in neck-to-neck industries, while the Schumpeterian effect prevails in unleveled industries. Empirical studies have found an inverted-U relationship between competition and investment (Aghion et al., 2005; Lee, 2005; Tingvall and Poldahl, 2006). However, this may not be the end of a story. For example, Sacco and Schmutzler (2011) show that competition has an U-shaped effect for more efficient firms and negative effects for laggard firms. 3. The econometric approach 3.1. Data The data are mainly drawn from the Wireless Intelligence database, which provides the financial and operational performance of network operators in mobile markets.9 The sample consists of the selected 58 MNOs operating in 21 countries for the 35 quarters from 1/2000 to 3/2008. Each MNO reports capital expenditures (Capex)10, average revenue per user (ARPU), and revenue in US dollars (USD), market share, and the number of connections by type of mobile technology standard. ARPU is total revenue divided by the weighted average number of customers. 8 Theoretically, R&D investment shares some common features with capital investment with respect to financing and adjustment costs of capital. Also, from the perspectives of static efficiency and dynamic efficiency, both current R&D and capital investment may come at the expense of static efficiency, but contribute to dynamic efficiency. Furthermore, some types of investment are sources of new services and cost-savings, for example, investment in physical capital may constitute an investment in innovation. 9 Retrieved from https://www.wirelessintelligence.com. In the sample, the operators with subsidiaries in several countries report financial information and performance by the country in which their subsidiaries operate. 10 According to Wireless Intelligence, the database captures Capex reported by operators where it is specifically for wireless cellular networks. When it is unclear whether the data are merged with other Capex data (e.g., for fixed lines), the data are excluded from the data set. Capital expenditure refers to tangible and intangible assets; it is not reported by wholesale- or retail-related purposes.

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Table 1 Mobile virtual network operators and regulation. Country

Period of MVNO¼ 1 in the sample (quarter/year)

Australia Austria Belgium Canada Czech Republic Denmark Finland France Germany Greece Italy Japan Korea Norway Poland Portugal Slovakia Spain Sweden United Kingdom United States

4/2000–3/2008 – 3/2006–3/2008 4/2005–3/2008 – 4/2002–3/2008 1/2002–3/2008 3/2004–3/2008 4/2001–3/2008 – 2/2007–3/2008 – – 1/2000–3/2008 4/2006–3/2008 3/2005–3/2008 – 4/2006–3/2008 1/2003–3/2008 4/2002–3/2008 2/2002–3/2008

REG¼ 2a

REG ¼1b

J( 1/2001)

J(2/2001  )

– – – –

–

–

J J

J( 1/2006)

J(2/2006  )

– – – – – – –

J

–

J J

J

– –

J(1/2006  )

J(  4/2005)

– – –

J

–

J(1/2006  )

J(4/2000  4/2005)

J(2/2000  3/2005)

J(  1/2000)(4/2005  )

– –

J

J

J

a REG¼ 1 includes non-mandatory ways of providing access, such as voluntary provisions and government threats of regulatory intervention. b REG ¼2 denotes mandatory access provisions.

World Cellular Information Services (WCIS) provides data on mobile technologies, access networks, and the subscriptions of MVNOs.11 These data identify 80 MVNOs in 16 out of 21 countries from 1/2000 to 2/2009. Due to the different definitions and scope of MVNOs across countries, the figure of 80 suggests that WCIS use a very narrow definition of MVNOs. Information on the regulatory environment pertaining to MVNO access in each country from several sources is collected. Since the nature of access provision differs across countries and varies across time, comparable time-series data on regulation for each country are difficult to compile. For this reason, the regulatory policies relevant only to MVNO access are addressed. Finally, for the overall degree of regulation in the telecom industry, an OECD indicator for regulatory reform is used.12 3.2. Mobile virtual network operators and the regulation variables The dummy variable MVNO measures the presence of an MVNO (i.e., irrespective of the number of MVNOs). The regulation variable is a dummy intended to capture the effect of access regulation. The regulation of MVNO access and the trajectories of reform are very complex and difficult to identify because the market environment and MVNO business models differ in time and across countries. In addition, access provision is regulated in many ways such that, once again, comparable data across countries are difficult to compile. Pursuant to the discussion in the previous section, access regulation is divided into mandatory access and nonmandatory access. The latter includes no policy, any type of voluntary provision, threats of regulatory intervention, and other types that cannot be precisely identified.13 In many countries with MVNOs active in the mobile telecommunications markets, access regulation has been replaced with voluntary negotiation-based provisions.14 Alternatively, access regulation did not exist in some countries for the sample period.15 Voluntary provision constitutes the majority of the observations in our sample. As shown in Table 1, to evaluate the regulation effect compared to the absence of MVNOs (i.e., MVNO¼0), when the mandatory regulation is set or is finalized, REG ¼2 is defined for the quarter/year where such an action is taken. The preceding or next quarter has REG¼ 1, for which the access provision is non-mandatory. An interaction variable of MVNO and the regulation variable, that is, MVNOnREG, is also created. The interaction variable measures the additional effect of mandatory access regulation (REG¼2) as compared to the average effect of other cases, such as voluntary provision and threats of regulatory intervention (i.e., REG ¼1). 11

Retrieved from http://www.wcisplus.com. The data are retrieved from http://www.oecd.org/eco/pmr. Conway and Nicoletti (2006) describe the indicators in more detail. 13 In some countries (e.g., France and the United Kingdom), the regulatory authorities have announced that they monitor the joint dominant market position or market competition of incumbent MNOs over time to decide on access regulation. These actions may restrict MNO investment, possibly leading to higher market shares, or they will intervene in the case of failure to reach a voluntary agreement between MNOs and MVNOs. 14 For example, Australia, Denmark, the United States, and Sweden. 15 For example, France, Germany, and the United Kingdom. 12

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Table 1 shows that in some periods some countries had no active MVNOs. In these countries, MNOs are treated as if they did not face access regulation. Obviously, when MVNO¼0, it does not affect the estimation if REG takes values of 1 or 2. Therefore, in countries when there are no MVNOs in the market, the effect of access policies can be ignored. In addition to MVNOnREG, The alternative dummy variables, MVNOnREG_V and MVNOnREG_M are constructed to examine the robustness of the results. MVNOnREG_V equals 1 if MVNOnREG¼1 while MVNOnREG_M equals 1 if MVNOnREG¼2. Lastly, it should be noted that there are some limitations inherent in using dummy variables regarding market entry and regulation. The variables related to MVNOs and regulation are somewhat coarse so that they do not carry sufficient information on MVNO competitive pressure and effectiveness of regulation conditional on market-specific factors like the number of active MVNOs, regulatory details, and so on. Also, MVNOs and access regulation are likely to have differential effects whether MNOs provide access or not. Unfortunately, this paper cannot examine this since the data do not include information on the specific relationships between MNOs and MVNOs.

3.3. Dependent variable, market concentration and other variables The dependent variable for investment intensity is the natural logarithm of capital expenditures divided by revenue. Competition among MNOs is also an important force affecting the level of any MNO’s investment. The Herfindahl–Hirschman Index (HHI) is a traditional measure of market structure. Our data on the market shares of MNOs do not include the market shares of any MVNOs. The 58 MNOs are the complete set, or constitute most, of the major mobile operators for the 21 countries in this study.16 This characteristic of the data allows the examination of MNO investment independently of the influence of MVNOs. The relevant literature identifies a number of variables that may affect the infrastructure investment of a firm. For ¨ example, in Friederiszick, Grejek, and Roller (2008) regulation-related variables are introduced along with population density and other variables to capture ‘cost shifters’, GDP per capita is a ‘demand shifter’ and proxies for competitive pressure. Greenstein, McMaster, and Spiller (1995) use demographic and economic information, such as population in urban and rural service areas, income by industrial sector, construction wages, and the number of competitors. Table 2 summarizes the regulatory, competitive, economic, demand, and market environments as well as the firm characteristics that this paper considers. The correlation coefficients are reported in Table 3. There may be some policy factors that are likely to affect both MNO investment and MVNO entry or regulation. Gradual changes in the government’s attitude to regulation over time affect MNO investment and access regulation. The variable, overall regulation, employs the indicator of regulation in energy, and transport and communications (ETCR). It ranges from 0 (most liberalized) to 6 (most regulated). The indicator for the telecom sector reflects the legal conditions of entry, public ownership (the government’s share in the largest firm), and market structure (the market share of new entrants).17 MVNO entry could occur at a time after MNOs’ investment is sunk (e.g., selling extra capacity) or the market becomes mature (e.g., lower rate of market growth). Consequently, a decline in investment following MVNO entry may include the effects of other factors. These effects have to be controlled for. As for market conditions, total penetration of mobile telephony services (Total penetration) and its growth (growth rate of total penetration) are important because higher market penetration or slow market growth may lower opportunities for investment and entry of MVNOs may be associated with the sufficient deployment of mobile networks. Real GDP growth rate, the natural logarithm of GDP per capita, and the natural logarithm of population density are intended to control for economic and demand conditions. Economic growth will affect investment and entry, GDP per capita is a proxy for income (it is measured in US dollars at purchasing power parity). The costs of deploying mobile networks are affected by population density. Firm characteristics affect investment decisions as well as the propensity to grant access to MVNOs. Advantages arising from firm size and business experience are captured by the natural logarithm of the number of connections and firm age (i.e., the number of years since a firm was founded), respectively. The growth rate of connections controls for the possibility that MNOs may reduce investment and be willing to use MVNOs if they suffer from slow growth of connections and excessive capacity due to past over-investment. Mobile services that use advanced technologies or different technological standards require a considerable amount of prior and subsequent investment. If this is the situation when MVNOs enter, sudden increases in capital expenditure are likely to lead to biased results. More important, such changes may influence the presence of MVNOs, as well as regulation, leading to an endogeneity problem. It is expected that there should be substantial investment prior to, subsequent to, and in the year when the data on 2G, 2.5G, and 3G services appear. Three dummy variables (intro) relating to the introduction of new mobile technologies are introduced with yearly lags ranging from  1 to þ1. 16 In the Wireless Intelligence data, the remaining portions of the reported MNO market shares are aggregated under the title of ‘other’ (e.g., Denmark, Norway, and the United States) and usually their sizes are not significant. However, there may be small upward biases in the HHI measures. Given the small size of the market share of ‘other’, these biases are unlikely to be significant. 17 It includes entry regulation (legal conditions of entry), market structure (market share of new entrant), public ownership (percentage of shares in the Public telecommunications operator (PTO) owned by government, percentage of shares owned by government in the largest firm in the mobile sector), in the trunk telephony market, international market, and mobile market. It focuses on the regulations that need to be reformed to encourage market competition and thus affect investment. However, as the OECD indicator focuses on market reform, it excludes some influential forms of regulation, such as regulation of the mobile termination rate.

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Table 2 Descriptive statistics. Variables Dependent variables (for MNOs) ln(CAPEX intensity)

Description

Mean

Std. dev.

Min

0.63

 3.30

0.53 0.59

0.50 0.60

0 0

1 2

0.48

0.50

0

1

Capital expenditure in tangible and intangible assets, and divided by  1.81 revenue.

Max

1.11

Regulatory and competition variables MVNO Dummy variable¼ 1 if an MVNO exists and 0 otherwise. Dummy variable¼ 0 if an MVNO does not exist, 1 if a MVNO exists MVNOnREG and REG¼ 1 (voluntary provisions, threats of regulatory intervention, etc.), and 2 if an MVNO exists and REG¼ 2, mandatory provision of access. MVNOnREG_V Dummy variable¼ 1 if an MVNO exists and REG ¼1 (voluntary provisions, threats of regulatory intervention, etc.), and 0 otherwise. Dummy variable¼ 1 if an MVNO exists and REG ¼2, mandatory MVNOnREG_M provision of access, and 0 otherwise HHI Herfindahl–Hirschman Index. Overall regulation Degree of regulation in the telecom market and by country.

0.06

0.23

0

1

0.31 1.14

0.10 0.69

0.13 0.10

0.51 2.80

Market characteristics Total penetration Sum of MNOs’ market penetration and by country Growth rate of total penetration Rate of growth in total penetration by country.

0.79 0.13

0.24 0.12

0.21  0.002

Demand and economic environments Real GDP growth rate Rate of GDP growth (2000 constant prices). ln(population density) Total population/total land area.

2.71 4.24

1.59 1.39

 0.93 0.94

10.58 6.20

15.57 0.18

1.13 0.36

13.02  0.77

18.00 4.89

2.59

0.92

0

5.02

MNO Firm characteristics ln(no. of connections) Growth rate of connections ln(age)

The number of connections. Connection growth in current year divided by connections in previous year as a percentage Firm age in years.

1.65 0.935

Notes: All nominal variables are deflated using 2000 USD. Table 3 Correlation coefficients.

(1) MVNO (2) MVNOnREG (3) MVNOnREG_V (4) MVNOnREG_M (5) HHI (6) Overall regulation (7) Total penetration (8) Growth rate of total penetration (9) Real GDP growth rate (10) ln(population density) (11) ln(age) (12) ln(no. of connections) (13) Growth rate of connections

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

1 0.92 0.89 0.23  0.32  0.27 0.20  0.23  0.21  0.18 0.21 0.11  0.11

1 0.65 0.58  0.21  0.22 0.25  0.20  0.21  0.16 0.20 0.02  0.10

1  0.23  0.38  0.28 0.10  0.21  0.18  0.17 0.19 0.20  0.10

1 0.12 0.01 0.21  0.02  0.07  0.01 0.05  0.19  0.02

1 0.82 0.35  0.00 0.14 0.39  0.08  0.09  0.09

1 0.22  0.03  0.00 0.16  0.08  0.15  0.10

1  0.35 0.11 0.40 0.05 0.02  0.21

1 0.12  0.05  0.04  0.12 0.36

1 0.00 0.09  0.02  0.01

(10)

1  0.24 0.25  0.03

(11)

1 0.16  0.15

(12)

1  0.09

(13)

1

As explained in the next section, system-GMM estimation requires the data to be annual. Quarterly capital expenditure and revenue are therefore aggregated. The data on total penetration and the number of connections in the fourth quarter are used. Growth rates of total penetration and the number of connections are year-on-year rates. Dummy variables for the introduction of services based on new mobile technologies take annual lags ranging from  1 to þ1. Table 3 provides the correlations of the variables.

3.4. The econometric model Our baseline specification for investment intensity is given below. lnðCAPEX intensityÞijt ¼ a0 þ a1 lnðCAPEX intensityÞij,t1 þ a2 MVNOjt ðorMVNOnREGjt Þ þ a3 HHIjt þ a4 lnðNo: of connectionsÞijt þ controls þ eijt

ð1Þ The variable subscripts denote firm (i), country (j), and time (t).

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It is hypothesized that MVNO and regulation exert a negative influence on MNO investment intensity. HHI captures the effect of competition among MNOs. The controls include the variables listed in Table 2 that reflect the development of the mobile market, economic conditions, demand and the national regulatory regime in the telecom market as well as firm characteristics. The dummy variables for the introduction of new mobile technologies control for any surge in investment to adopt new mobile technologies. A time trend is included. The investment equation is estimated with two-step system GMM. Since investment in infrastructure is likely to display persistence, a lagged dependent variable is included as an explanatory variable. Estimating such an equation requires caution about the correlation between the lagged dependent variable and the error term (Wooldridge, 2002). The GMM estimator introduced by Arellano and Bond (1991), and developed by Arellano and Bover (1995) and Blundell and Bond (1998), addresses this issue. To use this estimator, observations in time-series should be kept relatively smaller in number than the number of MNOs, as outnumbered instruments invalidate the estimates and test statistics. Therefore, quarterly data is transformed into annual data despite the implied loss of information. To check the sensitivity of the results, the investment equation is estimated with a fixed-effects model to control for any unobserved time-invariant effects specific to countries and firms. The fixed-effects estimation uses quarterly data and includes quarter dummies. The Intro variables relating to the introduction of new mobile technologies have quarterly lags ranging from –4 to þ 4. The investment equation is also estimated with a two stage least squares (2SLS) fixed-effects model. The number of connections may be endogenous if it affects investment and the possibility of allowing access. The instruments for ln(no. of connections) are its one period lag, HHI, and ln(GDP per capita), Overall regulation with a one year lag, ln(ARPU) and ln(revenue), as well as the explanatory variables used in the investment equation.

4. The findings 4.1. MVNOs and the investment intensity of MNOs The main interest of this section is the effect of MVNOs and access regulation on the investment intensity of MNOs. After discussing their effects, the estimation results of the control variables are briefly discussed at the end of the section. In Table 4, the once-lagged dependent variable is included on the right-side of the investment intensity equation, and Eq. (1) is estimated using the two-step system GMM estimator with standard errors robust to heteroskedasticity and intra-firm correlation, and the finite-sample correction of Windmeijer (2005). Table 4 displays the Arellano–Bond tests for AR(1) and AR(2) in first differences and the over-identification test based on Hansen’s J-statistic. The system GMM estimator estimates the firstdifferenced equation and the level equation simultaneously. First, under no serial correlation in error terms, second or higher lags of the level variables are suitable instruments for the differences of the endogenous variable. Second, under no correlation with the firm-fixed effects, valid instruments for the level equation include the most recent differences of the variables. The first condition can be tested by AR(1) and AR(2), and Hansen’s J-statistic tests the second condition. The statistics for AR(1) and AR(2) indicate that there is first-order but not second-order serial correlation, which suggests that the error term in the level equation is serially uncorrelated. Hansen’s J-statistic does not reject the overall validity of the instruments. An obvious finding is the strong statistical significance of the lagged dependent variable. Investment is highly persistent. Just as importantly, is that the negative effect of MVNOs in Model 1 is insignificant, that is, it cannot be concluded that MVNO entry affects MNO investment intensity. The MVNO dummy variable is somewhat coarse and its coefficients reflect the average effect of MVNOs on MNO investment, illustrating the diverse and complex regulatory and business surroundings such as the number of MVNOs, business models of MVNOs, strategies of MNOs providing access with MVNOs, and so on. Moreover, the type of regulation should be taken into account. Therefore, it is necessary to capture the effect that a government mandate to provide access to MVNOs has on MNO investment intensity. In Model 2, MVNOnREG reports a statistically significant negative impact on investment intensity of  0.092 at the 10% significance level while controlling for the economic, regulatory, and market environments. The effects of the separate dummies for non-mandatory provision (MVNOnREG_V) and mandatory provision (MVNOnREG_M) are also estimated. MVNOnREG_V is insignificant and MVNOnREG_M is significantly negative (0.171) at the 10% level as shown in Model 3. The results suggest that mandatory provision is related to the decreased investment incentives of MNOs. The coefficients of the short- and long-run effect of mandated access provision (MVNOnREG_M) are 0.171 and  0.326, respectively. The effect of mandated MVNO entry has a significant negative impact on investment intensity of MNOs. Nonmandatory provision, such as voluntary agreements, the anticipation, or threat, of government intervention, is not significantly related to the investment intensity of MNOs. Non-mandatory access provision constitutes the majority of the observations in the sample. This suggests that those countries where access is being provided on a voluntary basis are highly unlikely to experience a decline of investment intensity. Although mandated access provision is not as widespread as voluntary access provision in the sample, there are sufficient observations that give confidence in the statistical results. The estimates are statistically significant and indicate the presence of a negative effect on investment. Notwithstanding, it is an important finding that non-mandatory provision does not affect investment incentives. In fact, this points to the fact that, under certain conditions, MNOs may not be worse off by granting access to their networks voluntarily, as suggested by Banerjee and Dippon (2009). In this regard, non-mandatory provision may be an important strategy for policy-makers if it fulfills other regulatory goals.

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Table 4 Two-step system GMM estimation. 1 ln(CAPEX intensity)t-1 MVNO MVNOnREG MVNOnREG_V MVNOnREG_M HHI (MNOs) HHI2 Overall regulation Total penetration Growth rate of total penetration Real GDP growth rate ln(population density) ln(age) ln(no. of connections) Growth rate of connections Intro dummies No. of observations Wald Chi-sq, p-value Arellano–Bond test for AR(1) in first differences (p-value) Arellano–Bond test for AR(2) in first differences (p-value) Over-identification test (Hansen J statistic, p-value)

2 nnn

0.551 (0.122)  0.107 (0.071)

0.524

3 nnn

(0.129)

4 nnn

0.475

(0.133)

5 nnn

0.489 (0.152)  0.107 (0.066)

0.468nnn (0.160)  0.115n (0.064)

 0.551n (0.329)

 3.653n (2.006) 5.479n (3.307)

 0.092n (0.054)

 0.456 (0.779)

 0.274 (0.775)

 0.075 (0.072)  0.171n (0.103)  0.319 (0.855)

 0.051 (0.102)  0.279 (0.218)  0.027 (0.256) 0.012 (0.018) 0.005 (0.032)  0.091nn (0.043)  0.027nn (0.013) 0.083 (0.118) Included 257 0.00 0.016

 0.071 (0.101)  0.306 (0.217) 0.036 (0.251) 0.010 (0.018) 0.007 (0.033)  0.093nn (0.043)  0.031nnn (0.012) 0.092 (0.122) Included 257 0.00 0.024

 0.068 (0.103)  0.337n (0.219) 0.057 (0.230) 0.009 (0.016) 0.013 (0.035)  0.098nn (0.043)  0.036nn (0.014) 0.102 (0.130) Included 257 0.00 0.020

 0.466n (0.274) 0.023 (0.177) 0.011 (0.017) 0.020 (0.036)  0.102nn (0.046)  0.033nnn (0.013) 0.132 (0.106) Included 259 0.00 0.055

 0.336 (0.265) 0.043 (0.169) 0.003 (0.018) 0.011 (0.036)  0.117nn (0.048)  0.011 (0.109) 0.122 (0.109) Included 259 0.00 0.081

0.198

0.181

0.206

0.153

0.114

0.204

0.232

0.629

0.299

0.317

Notes: The standard errors in parentheses are robust to heteroskedasticity and intra-firm correlation using the finite-sample correction of Windmeijer (2005). Dummy variables on introductions of mobile technologies are not reported. n Significance p¼ 0.1. nn Significance p ¼ 0.05. nnn Significance p ¼0.01.

Theories describe conditions, under which voluntary agreements can benefit both host MNOs and MVNOs. The MNOs’ incentives for voluntary agreements on access provision depend on the mode of competition and the degree of product differentiation. Voluntary relationships exist when revenue effect outweighs competition effect (Dewenter and Haucap, 2007). Provided that investment incentives crucially rely on revenue changes both before and after access provision, the presence of voluntary provision indicates that it could even increase investment by MNOs. As Banerjee and Dippon (2009) show, host MNOs can increase their profitability by granting access MVNOs with high brand reputation under certain demand and sales conditions. Also, without access price regulation and with a competitive downstream sector, a vertically integrated firm has an incentive to invest if MVNOs are more efficient in offering services (Foros, 2004; Kotakorpi, 2006). Thus, such a voluntary provision cannot emerge in markets where these conditions are not developed, met, or found. This may be consistent with the observation that in countries where no MVNO exists, an open access obligation on MNOs have been considered or imposed. On the other hand, the estimation results show that non-mandatory provision neither decreases nor increases investment intensity. This may be attributable to the data that does not include specific information on the precise nature of MNO–MVNO agreements, and thus, may include both MNOs providing and not providing access, whereas theoretical models presume that MNOs granting MVNOs unlimited network access. A caveat to this conclusion is that the information contained in the category of non-voluntary provision does not provide detail on the effective competitive pressure of MVNOs. Moreover, it needs to be kept in mind that MVNOs generally have small market shares.18 MVNO entry and regulation may encourage MNOs to adjust their investment level. As competition among MNOs places pressure on infrastructure capacity, services-based competition triggered by MVNOs may promote a more efficient use of network resources. Therefore, a lower investment intensity should not be interpreted as evidence that access agreements lead to under-investment, independently of any market and technological contexts. HHI is highly correlated with overall regulation. Therefore, Models 4 and 5 in Table 4 drops the overall regulation variable.19 As can be seen, the effect of HHI on investment intensity is significant. Competition of MNOs is strongly related to lower investment intensity. Furthermore, an U-relationship between HHI and investment intensity is significant in Model 5. The total effect of MNO market concentration on investment intensity, however, remains positive over the range of the HHI values (ranging from 0.13 to 0.51 in the sample).

18 Market shares of the key MVNOs increased during the last decade. According to Analysys (2006), Telmore takes 7–8% of the total (2003–2005) in Denmark, Tele 2 7% (2006) in Norway, Debitel 8% (2006) in Holland, Saunalahti 7–8% (2004–2005) in Finland, Virgin 6–7% (2003–2005) in the U.K., Tracfone 3% (2005) in the U.S. In Western Europe and North America, MVNOs’ market share reached 10% in recent years. 19 In Models 1–3 of Table 4, the overall regulation variable is not dropped as HHI is a control variable.

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The effect that overall regulation has on investment intensity is insignificant in Table 4. Although not reported, its effect without the HHI variable (due to its high correlation with HHI) is estimated, which resulted in a negative coefficient at the 10% significance level. That is sector-specific market liberalization does reduce investment by MNOs. Total penetration affects the investment intensity of MNOs in Models 3 and 4. Firm age is also negatively related to investment intensity and the effect of the number of connections is negative. Population density, total penetration growth, GDP growth, and a higher growth rate of connections do not alter investment intensity. 4.2. Sensitivity analysis To test the sensitivity analysis of the GMM results, fixed-effects and 2SLS with fixed-effects estimation are performed.20 The estimated coefficients are reported in Tables A3 and A4 in the Appendix. The results are strongly supportive. Table A3 reports the estimated coefficients using the fixed-effects model with standard errors robust to heteroskedasticity and intra-firm correlation. The impact of MVNOs on the investment intensity of MNOs is negative but insignificant (Model 1a). In Model 2a, MVNOnREG has an insignificant coefficient. The effects of the separate dummies for non-mandatory provision (MVNOnREG_V) and mandatory provision (MVNOnREG_M) are also estimated. MVNOnREG_V is insignificant and MVNOnREG_M is significantly negative ( 0.260) at the 10% level as shown in Model 3a of Table A3. Table A4 reports the estimates of a 2SLS fixed-effects model with standard errors robust to heteroskedasticity and intra-firm correlation. Endogeneity tests reject the null hypothesis that the number of connections is exogenous. Under-, weak and overidentification tests validate the instruments. In Models 1b and 2b, the signs of MVNO and MVNOnREG are negative but insignificant. The result of Model 3b is similar to those in Table 4 as well as Table A3, indicating that mandatory access provision significantly reduces investment intensity. The coefficient of MVNOnREG_M is –0.257 at the 10% level, which is nearly the same as –0.260 from Model 3a, whereas MVNOnREG_V is not associated with a decline in investment intensity. From Table 4 and Tables A3 and A4, the effect of MVNOs entry is insignificant for all the estimation methodologies used. MVNOnREG has significantly negative coefficient of –0.092 in Table 4 when it is estimated using two-step system GMM. For non-mandatory provision of access (MVNOnREG_V), the estimated effect is insignificant in all estimations. Mandatory provision (MVNOnREG_M) reveals a strong negative relationship with investment. 5. Conclusions MVNOs are often thought to be an effective tool for promoting competition in the mobile telecommunications market across the world. However, there have been concerns that MVNOs and the related regulation might undermine investment incentives for MNOs. MVNOs and the associated regulation made it viable to empirically examine whether a regulatory policy promoting competition undermines the dynamic efficiency of the sector in terms of investment. The findings of this paper give some credence to these concerns. The role of MVNOs and related regulatory changes were investigated. Granting MVNOs access to MNOs’ networks may have significant consequences. MVNOs and regulation in the mobile access markets have a negative effect on the investment intensity of MNOs. However, according to the results, non-mandated provision, mostly voluntary provision, of access does not affect MNO investment incentives. Voluntary access provision is preferable than mandatory provision as measured by the impact on MNOs’ investment. From a policy perspective, it is highly significant that voluntary access provision prevails in more and more countries. MVNOs are hoped to accelerate service-based competition in the short-term and encourage investment in mobile telecommunications infrastructure in the long-term. The accumulated effect on investment by MNOs may lead to undesirable results in the long-term, such as delayed deployment of advanced networks, poor service quality, and slow technological advances. However, the mobile telecommunications sector does not appear to suffer from insufficient investment and MVNOs generally have small market shares. The possible explanation for a decline of investment intensity associated with mandatory access provisions is that entry by MVNOs and regulation may force MNOs to adjust their investment levels. Services-based competition driven by MVNOs may further promote the efficient use of network resources. The optimal level of investment will depend on the extent to which the current deployment of mobile networks or mobile technologies coincide with and support the development of other relevant technologies and market needs. Therefore, a lower investment intensity should not necessarily be interpreted as evidence against granting market access to MVNOs. For example, lower investment is not necessarily undesirable where duplication of, or over-investment, in existing networks matter. Notwithstanding, the results still suggest that regulators need to deal with investment disincentives of providing access to MVNOs.

Acknowledgements We are grateful for the financial support from the Science and Technology Amicable Relationship (STAR) project funded by the National Research Foundation of the Korean Ministry of Education, Science and Technology, the French Ministry of Foreign Affairs 20

In Table 4 and Tables A3 and A4, the estimates using the different econometric models are comparable, for example, see the models numbered 1.

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and the French Ministry of Higher Education and Research. The authors are also grateful to Gulasekaran Rajaguru, three referees and the editor, Erik Bohlin, for their valuable comments. The views expressed in this paper are those of the authors alone.

Appendix A For the sensitivity analysis, the fixed-effects and 2SLS with fixed-effects estimation are performed, respectively. Tables A1 and A2 provide the descriptive statistics and correlation coefficients of the sample used in these estimations (Table A3 and A4). Table A1 Descriptive statistics of quarterly data. Variables

Description

Mean Std. dev. Min

Dependent variables (for MNOs) ln(CAPEX intensity)

Capital expenditure in tangible and intangible assets and divided by revenue

18.53 1.38

Regulatory and competition variables MVNO Dummy variable ¼ 1 if an MVNO exists and 0 otherwise (quarterly) MVNOnREG Dummy variable ¼ 0 if an MVNO does not exist, 1 if a MVNO exists, and REG ¼ 1 (voluntary provisions, threats of regulatory intervention, etc.), and 2 if an MVNO exists and REG¼ 2, mandatory provision of access (quarterly) MVNOnREG_V Dummy variable ¼ 1 if an MVNO exists and REG¼ 1 (voluntary provisions, threats of regulatory intervention, etc.), and 0 otherwise. Dummy variable ¼ 1 if an MVNO exists and REG¼ 2, mandatory provision MVNOnREG_M of access, and 0 otherwise. HHI Herfindahl–Hirschman Index (quarterly) Overall regulation Degree of regulation in the telecom market, by country. (annual) Market characteristics Total penetration Sum of MNOs’ market penetration, by country (quarterly) Growth rate of total penetration Rate of growth in total penetration by country (quarterly)

Max

14.64 22.15

0.50 0.50 0.55 0.58

0 0

1 2

0.46 0.50

0

1

0.05 0.22

0

1

0.30 0.09 1.12 0.69

0.13 0.13

0.51 3.13

0.78 0.24 0.03 0.03

0.16  0.09

1.69 0.35

Demand and economic environments Real GDP growth rate Rate of GDP growth (2000 constant prices) (annual) ln(GDP per capita) GDP per capita in USD and PPP (annual) ln(population density) Total population/total land area (annual)

2.59 1.62 10.22 0.29 4.24 1.39

 1.20 10.58 9.24 10.64 0.94 6.20

MNO firm characteristics ln(no. of connections) ln(ARPU) Growth rate of connections

15.59 1.12 3.65 0.27 0.03 0.03

12.80 18.08 2.83 4.36  0.09 0.03

20.44 1.19 2.60 0.89

17.21 23.25 0 5.03

ln(revenue) ln(age)

The number of connections Average revenue per user Connection growth in current quarter divided by connections in previous quarter as a percentage (quarterly) revenue in USD (quarterly) firm age in years (annual)

Notes: All nominal variables are deflated at 2000 USD.

Table A2 Correlation coefficients. (1) (1) MVNO (2) MVNOnREG (3) MVNOnREG_V (4) MVNOnREG_M (5) HHI (6) Overall regulation (7) Total penetration (8) Growth rate of total penetration (9) Real GDP growth rate (10) ln(population density) (11) ln(age) (12) ln(no. of connections) (13) Growth rate of connections (14) Time trend (year) (15) ln(revenue)

(2)

(3)

(4)

(5)

1 0.93 1 0.90 0.69 1 0.22 0.56  0.21 1  0.34  0.24  0.40 0.12  0.29  0.24  0.30 0.02 0.22 0.26 0.13 0.20  0.16  0.17  0.11  0.09

1 0.83 0.33 0.04

 0.21  0.19  0.19  0.04  0.21  0.19  0.20  0.02 0.21 0.20 0.18 0.06 0.08 0.00 0.16  0.18  0.07  0.06  0.06  0.00 0.39 0.36 0.36 0.07 0.10 0.01 0.18  0.18

0.13 0.40  0.12  0.08  0.07 0.08  0.15

(6)

(7)

1 0.22 1 0.09  0.31

(8)

(9)

(10)

(11)

(12)

(13)

(14) (15)

1

 0.01 0.05 0.04 1 0.17 0.38  0.01 0.00 1  0.10 0.04  0.12 0.09  0.27 1  0.15 0.02  0.04  0.07 0.26 0.14 1  0.08  0.17 0.33 0.03  0.04  0.09  0.07 1  0.04 0.62  0.34 0.06 0.05 0.22 0.18 0.10 1  0.20  0.07  0.02  0.12 0.18 0.18 0.96  0.07 0.12 1

Notes: MVNO, MVNOnREG, HHI, total penetration, growth rate of total penetration, ln(no. of connections), growth rate of connections, and ln(revenue) are quarterly variables. The rest of the variables use annual data.

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Table A3 Fixed-effects models. 1a MVNO MVNOnREG MVNOnREG_V MVNOnREG_M HHI Overall regulation Total penetration Growth rate of total penetration Real GDP growth rate ln(population density) ln(age) ln(no. of connections) Growth rate of connections Time trend (year) Quarter dummies Intro dummies No. of observations F (p-value) Centered R2

2a

3a

 0.122 (0.099)  0.121 (0.077)

2.397** (1.195)  0.062 (0.100)  0.233 (0.585) 0.651 (0.912) 0.018 (0.023)  3.822 (4.366)  0.064 (0.105)  0.511** (0.219) 1.154* (0.611) 0.017 (0.048) Included Included 1243 0.000 0.236

2.311* (1.180)  0.077 (0.100)  0.228 (0.589) 0.652 (0.907) 0.018 (0.023)  3.212 (4.424)  0.066 (0.105)  0.522** (0.221) 1.165* (0.614) 0.015 (0.048) Included Included 1243 0.000 0.237

 0.112 (0.097)  0.260* (0.154) 2.305* (1.185)  0.083 (0.102)  0.225 (0.589) 0.660 (0.909) 0.017 (0.023)  3.144 (4.432)  0.067 (0.105)  0.525** (0.222) 1.169* (0.611) 0.013 (0.049) Included Included 1243 0.000 0.237

Notes: n Significance p ¼ 0.1; nn Significance p ¼0.05; and nnn Significance p ¼ 0.01. The standard errors in parentheses are robust to heteroskedasticity and intra-firm correlation. Dummy variables for quarters and the introduction of mobile technologies are not reported.

Table A4 SLS fixed effects estimation. 1b MVNO MVNOnREG MVNOnREG_V MVNOnREG_M HHI (MNOs) Overall regulation Total penetration Growth rate of total penetration Real GDP growth rate ln(population density) ln(age) ln(no. of connections) Growth rate of connections Time trend (year) Quarter dummies Intro dummies Obs. Joint F statistic (p-value) Centered R2 Under-identification test (Kleibergen–Paap rk LM statistic, p-value) Weak identification test (Kleibergen–Paap rk Wald F statistic 4critical value in Stock and Yogo [2005]) Over-identification test (Hansen J statistic, p-value) Endogeneity test (p-value)

2b

3b

 0.113(0.099)  0.117(0.077)

2.000(1.260)  0.122(0.108)  0.227(0.593) 0.947(1.174) 0.018(0.024)  2.992(4.550)  0.067(0.106)  0.465nn(0.213) 1.092n(0.633) 0.011(0.046) Included Included 1180 0.00 0.21

1.895(1.240)  0.137(0.108)  0.225(0.596) 0.934(1.170) 0.018(0.024)  2.280(4.618)  0.068(0.105)  0.474nn(0.215) 1.101n(0.635) 0.009(0.047) Included Included 1180 0.00 0.21

 0.103(0.097)  0.257n(0.154) 1.886(1.247)  0.147(0.111)  0.221(0.596) 0.945(1.170) 0.017(0.024)  2.180(4.642)  0.068(0.105)  0.477nn(0.216) 1.107n(0.633) 0.007(0.048) Included Included 1180 0.00 0.21

0.01

0.01

0.01

Yes

Yes

Yes

0.62 0.04

0.60 0.06

0.58 0.06

Notes: n Significance p¼ 0.1, nn Significance p ¼0.05, and nnn Significance p¼ 0.01. The standard errors in parentheses are robust to heteroskedasticity and intra-firm correlation. Dummy variables for quarters and introduction of mobile technologies are not reported.

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