FDI in the Telecommunication Sector of Transition and Developing Countries Silvio Contessi Johns Hopkins University∗

First Draft: October 2003 This Draft: November 2004

Abstract

I model FDI in the telecommunication sectors of transition and developing economies using a demand function for connections characterized by network externalities and introducing capacity constraints. In the three-stage game the government decides how to liberalize, either through sale of national monopolists or allowing direct entry of new operators, while the Multinational Corporation (MNC) decides on capacity expansion and on technology transfer. I provide econometric evidence using a panel of 46 transition and emerging economies for the period 1989-2000. Using a set of different indicators for the telecommunication sector, I show that privatization processes are significantly correlated with increases in teledensity and that the foreign participation in the incumbent generates positive benefits through an underlying non-linear relationship that also characterizes the theoretical model.

JEL CLASSIFICATION: F23, L23, L96 KEYWORDS: FDI, Telecommunications, Developing countries, Technology transfer

∗ This

project started at Bocconi University, Milan, and was completed at Johns Hopkins University, Baltimore.

Financial support from both institutions is gratefully acknowledged. I have benefited from the comments of many individuals, among them Marco Alderighi, Carlo Altomonte, Johanna Francis, Cesar Mattos, Gianmarco I.P. Ottaviano, Matt Shum, and participants at the 30th Conference of the European Association for Research in Industrial Economics (Helsinki, 2003) and at the 8th Conference of the Latin American and Caribbean Economic Association (Puebla, 2003). All errors are mine. Mailing address: Dept. of. Economics, JHU, Mergenthaler Hall, 3400 N. Charles St., Baltimore 21218-MD, USA. E-mail address: [email protected]

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1

Introduction

In many countries, market-based approaches to deal with telecommunications issues are increasingly popular and independent regulatory authorities are more frequent and active to assist and discipline the challenging transformation of their national sectors, traditionally dominated by state-owned monopolies, into competitive arenas. In this paper, I focus on the economic issues surrounding the liberalization of telecom in Transition and Less Developed Countries (TLDC) from both a theoretical and an empirical point of view. In particular, I evaluate the potential impact of the WTO liberalization measures in the telecom sector using a model of Foreign Direct Investment (FDI) and technology transfer in an oligopoly setting. I then provide and empirical estimation of the model using a panel of 46 TLDC for 1989-2000. The analysis takes into account three empirical regularities that characterize the telecom sectors of TLDC: (1) The existence of public monopolies, and an ongoing process of demonopolization and privatization; (2) Extended waiting lists for land-telephone access (up to 4 years), and consumers willing to put down deposits for the privilege of waiting for a telephone line1 ; (3) The intensified activity of multinational corporations (MNC) as actors in the telecommunications sectors. Given these stylized facts, I infer that some TLDC experience capacity constraints due to under-investment in telecom infrastructure, frequent in the past because of the continuous contingent need of securing financial resources to guarantee macro-stability. The simple model helps understand the process of liberalization that TLDC will experience once the liberalization process initiated at the World Trade Organization level takes off. In the system of agreements emerged after the conclusion of the Uruguay Round in 1994, the telecom sector is regulated by the GATS of 1994, the Annex on Telecommunications of 1994 and the Basic Telecommunications Agreement of 19972 . I focus on countries where telecom networks, wireline and/or wireless, are small and inefficient as compared to developed countries, where telecom have been or still are publicly owned, more likely to experience capacity constraints and/or reduced efficiency, so that consumers might be rationed and/or prices might be high with respect to international Ravamurti (2000) reports that in many Latin American countries, deposits are frequently set even beyond USD 1000. 1

The GATS regulate four main modes of supply of services. However, if consumption abroad, movement of natural persons, and cross-border supply are of a limited importance in the telecommunication sector, commercial presence is certainly not. ’Commercial presence’ is defined as "any type of business or professional establishment, including through (i) the constitution, acquisition or maintenance of a juridical person, or (ii) the creation or maintenance of a branch or a representative office, within the territory of a Member for the purpose of supplying a service." From a substantial point of view, it is equivalent to Foreign Direct Investment 2

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standards. Using a set of different indicators for the telecom sector, I look for the effect of privatization processes and foreign participation in the incumbent itself on such indicators in Central and Eastern European Countries (CEECs), Middle East and North African (MED), South American (SA) and Central American (CA) countries. I find that privatization processes are significantly correlated with increases in teledensity and that the share of foreign-ownership in the incumbent has a positive, concave impact on sectorial indicators. As for regulatory reforms, I find that the establishment of a separate regulator has a positive significant effect on teledensity. As for competition, the variable “foreign penetration in the cellular market”, which captures the competitive effect coming from foreign presence in the wireless market, apparently increases teledensity, teledensity growth and the ratio between fixed lines and staff, possibly as a response to such a form of competition.

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The international telecommunication sector

Telecom sectors have long been dominated by strong interventionism (Noll [2000]). The monopolistic telecom provider was typically incorporated into the Government and run as a division of the ministry of Posts, Telegraph and Telecommunications, far from being considered as a stand-alone business enterprise. Long-term capital investment should constitute a large part of the costs of a telecommunication operator. In some jurisdictions, telephone revenues of state-owned operators have historically been treated as part of general government revenues, whereas expenditures and investment of the state-owned operators have been included in the general government budget. This has led cash-strapped governments to extract revenues from state-owned operators to finance their government priorities, without extensive consideration of the economic or social impact of price increases. And in many transition and developing countries, such organization of the telecom sectors has deprived operators of the capital required to upgrade network, and frequently annihilated the incentive to innovate and reduce costs, leading them to both poor performance and overstaffing. The liberalization process that is taking place at the international level is related to this situation. Indeed, developing countries have begun to see the liberalization of their telecom sectors as an opportunity to attract private capital possibly to expand and upgrade networks, introduce new services, and improve the quality of the existing ones. In most transition and developing countries, however, policy makers have to deal with underdeveloped infrastructure networks3 . The evidence shows that many countries are still endowed with tiny networks, while at the same time network developments might take place at a rapid pace. In this paper I assume that the monopolist operating in TLDC is capacity constrained. According to the seminal literature on “soft budget constraint” (Kornai [1979]), public firms 3

Figure 1 plots the correlation between teledensity and GDP per capita over 178 countries.

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might happen to expects other institutions to pay for its expenditure, because they fail to internalize compltely their own costs and benefits. Auriol and Picard [2002] model the impact of the government’s budget constraint on the optimal industrial policy in industries with increasing returns to scale of development countries and single out telecommunications as a benchmark case. They point out that, as a matter of fact, privatization processes have been launched in situations of growing public debts and large trade deficits. This has been the case both in developed and in developing countries and would suggest that governments have privatized public assets not because of long run efficiency concerns, but because of critical contingent budgetary conditions. In TLDC, privatizations have also been a dominant element of structural adjustment programs and the World Bank and the International Monetary Fund often include privatization programs as a condition for assistance during debt crisis. Indeed, emergency or unsustainable macroeconomic situations affect the way and the timing privatizations are decided and implemented and, in turn, affect the competitive structure and the sectoral efficiency of a number of economic sectors that have traditionally been public and characterized by soft-budget constraints. If soft budget constraints harden, then companies do not receive additional money to carry out investment plans from the Governments, so that they can actually have installed capacity below the level that would be optimal if the constraint did not hold. Thus, entry of foreign investors through FDI might be a good policy instrument for governments who want to remove the under-investment constraints and improve the supply of telecom services. Different modes of entry might naturally have different impacts on domestic telecom development, ranging from differences in the extent of technology transfer and/or capacity expansion and/or competition implications. To study the expansion of telecommunications through FDI from a theoretical point of view, I modify Mattoo, Olarreaga and Saggi [2004] by introducing introduce explicitly the network externalities in consumption that characterize the demand function for telecom connections originally modelled by Rohlfs [1974], and the possible existence of capacity constraints in the supply of connections. The theoretical prior upon which the model is developed is that investment in infrastructure is market-enhancing in the sense of Aghion and Schankerman [2000], i.e. infrastructure investment fosters market interaction and competition through three channels - direct market selection, restructuring and entry 4 . From an economy-wide perspective, empirical support for this argument comes from Röller and Waverman [2001] who find evidence for the claim that investment in telecom fosters growth, estimating a structural model that endogenizes telecom investment, on data from 21 OECD countries over a 20-year period. The show that there exist a significant positive causal link, In contrast, earlier theoretical work on infrastructure and development has emphasized the indivisibility and public good aspects of infrastructure and the coordination failures involved in building infrastructure ahead of demand [Lars Röller and Leonard Waverman, 2001)]. 4

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especially when a critical mass of telecom infrastructure is present at a level of telecom infrastructure, near universal service. The paper is structured as follows. Section 2 provides some background and explains the importance of infrastructure investment to economic growth as emphasized by a few recent theoretical and empirical papers.Section 3 is a literature review of recent work on FDI and modes of entry, and considers a few papers that investigate the incentives and the effects of international investment decisions, when the alternative between different modes of entry is considered explicitly by the investor. In section 4, I construct a demand curve for telecom connection and set up the model. In section 5, 6 and 7, I develop a partial equilibrium model of FDI. Finally, in section 8, I estimate the empirical implications of the theoretical model. Section 9 concludes.

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Theoretical Models on international modes of entry

Despite the fact that FDI in the telecom sector has gained importance in the last ten years and the transactions related to operations of telecom MNC typical register huge amounts of financial resources being transferred internationally, surprisingly little research has been carried out at both theoretical and empirical level. The only theoretical piece of research that deals specifically with telecom FDI is Graham (2001). The paper originates from the concerns about potential unfair competition exerted on US telcos by the acquisition of Voice Stream by Deutsche Telekom, in the context of the Hollings Bill. In a Kreps and Scheinkman (1983) type of game, two separate markets for identical goods are considered; markets are separate in the sense that, initially, firms in one market may not sell in the other market because there exist barriers to entry that deter them from doing so. Firms operate with a cost structure typical of telecom, where much of the cost of providing the relevant service is fixed in nature. Graham (2001) investigates the effects of opening up one market asymmetrically and letting into this market the firm that was previously selling only in the non-liberalized market under two alternative scenarios. In the symmetrical scenario, both countries de-monopolize and allow entry, while in the second, a-symmetrical, one firm can use subsidies provided by her domestic government costly because the subsidy augments domestic capacity - to finance aggressive entry into the liberalized market and ease the burden of building new capacity there. In the first case, a punishment strategy “if you enter my market, I enter yours” is sub-game perfect and Pareto-dominates other alternatives. The best option for a government wishing to achieve more competition is to unilaterally open her own market, without insistence for reciprocity, whereas reciprocal opening would retard entry. Under the second scenario, the advantage of recurring to the rents gardened in the home market to subsidize foreign operations depends on the net gain from using the subsidy, which is not necessarily positive due to high cost of

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expanding capacity. The simple model is extremely useful to understand interaction between ex-monopolists of developed, say OECD, countries but might fail to capture the asymmetry of FDI investment in TLDC so that a more elaborated framework of analysis needs to be created. Besides this rare contribution, only a recent literature in international trade charazterized by a a marked industrial organization flavor has tried to explain international modes entry modelling entry in partial equilibrium with a game theoretic structure5 . From the international business perspective, Buckley and Casson (1998) study the case of a firm localized in a home country that decides to sell for the first time in a foreign market where a vertically integrated monopolist operates. The production process of the MNC is broken down in vertically disintegrated phases including production, distribution, research and development and, marketing. After defining a set of twelve possible market entry strategies6 with a number of variants, they measure the associated profit and rank them accordingly, via elimination of dominated strategies. The elimination of dominated strategies reduces the set to three options: Greenfield production combined with acquired distribution, Greenfield production combined with franchised distribution, and licensing. The choice among them depends on six variables, namely the adaptation costs of production plants, the cost of building trusts to access marketing expertise through newly acquired distribution facilities, the value of profit-sharing collusion, transaction costs incurred when licensing technology, transaction costs incurred in using an external market for the wholesale product and the rate of interest. Thanks to the simpler analytical structure and the fine coverage modes of entry, the results encompass a number of conclusions of other articles. Higher tariffs, transport costs or a loss of economies of scale in domestic production encourages production abroad, as in Brainard (1993); stronger technological advantages encourages Greenfield production, as in Markusen (1995), and discourages acquisition or licensing, while higher costs of building trust tend to favor Greenfield investment. Higher transaction costs for intermediate output trigger vertical integration of production and distribution, as in all Dunning (1977), Brainard (1993) and Markusen (1995). In general, subcontracting is not a first best mode of entry into the foreign market, especially because it does not give access to the domestic rival’s marketing expertise. Finally, the model predicts that high costs of competition associated to the existence of domestic monopolies favor strategies giving long term control over production or distribution facilities and favor acquisition over Greenfield FDI in either production or distribution. Görg (2000) formalizes the approach of Buckley and Casson (1998) with a static Cournot game, by modeling the choice of a firm that has decided to enter a new market via FDI 5 Contessi, 6 These

Guagliano and Haller (2004) for a survey. strategies include FDI in production or distribution, subcontracting, franchising/exporting, licensing, Joint

Ventures integrated in production, in distribution, in export, and various combinations of FDI/Joint Venture in the home/host country.

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and faces the simpler alternative between setting up a new plant or acquiring an existing company in the market. As in Buckley and Casson (1998), goods are non-traded so that the price is determined endogenously in every market, but there exist two firms established in the host economy, that are possibly endowed with different levels of technology. Here, moreover, the take-over of a domestic firm is costly for the MNC. The result indicates that under most conditions on the structure of the costs, take-over of existing low-cost (high-tech) firms could be the preferred form of entry. Greenfield investment is preferred only when marketing costs are very low relative to the costs of adaptation. More elaborated papers include Norbäck and Persson (2004) dealing with privatization, Norbäck and Persson (2002) with acquisitions vs. greenfield entry, and Mattoo, Olarreaga and Saggi (2004) with technology transfer and FDI policy. Norbäck and Persson (2004) introduce explicitly the possibility of entry through privatization as an alternative to Greenfield FDI, that is particularly relevant for the understanding FDI in TLDC. They study the interaction between privatization procedures and incentives for FDI and exports in a two-country partial equilibrium model where three companies producing a homogeneous tradable product. An existing domestic monopolist, a foreign (private) firm and a third firm (that can possibly be domestic or foreign) face a liberalization program made by a package of three distinct measures: privatization of the state enterprise (as a simultaneous bid auction between the two private firms), FDI liberalization (removal or ease of FDI restrictions), and trade liberalization. If a foreign firm has not invested in the domestic market, it can be an exporter and accept to bear a trade cost in addition to the normal production costs. In the equilibrium market structure, it is shown that low Greenfield costs and low trade costs induce foreign acquisition, which is certainly a counter-intuitive result from the point of view of the mainstream theory of international economics, where FDI are treated only as new start-ups/Greenfield, and the tariff jumping argument is seen as one of the determinants of MNC activity7 . The topic is expanded in Norbäck and Persson (2002), that shows that the acquisition price might be higher than the seller’s reservation price when there are many possible MNC/acquirers. This happens becasue there might be both an asset complementarity effect and a preemption effect; the former arises when domestic assets might more efficiently used if transferred from domestic to foreign owners because the MNC might exploit superior technology, the latter has been described by Horn and Persson (2001) as the possibility of preventing other MNCs from acquiring the asset. This article also shows how such a mechanism might lead to the counter-intuitive result of low trade costs being 7 The

reason why low Greenfield costs induce acquisitions of state assets is that the domestic firms cannot prevent

foreign firms from becoming locally strong competitors and, thus, their willingness to pay for the state assets are low. Even if domestic firms buy the state assets, they might have to face foreign firms local competition, so they simply have no incentive to buy. If Greenfield costs are high, instead, the likelihood of foreign entry decreases and the domestic firms tend to buy the state company to reduce competition on the domestic market and increase their monopoly (or oligopoly) profits.

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conducive to foreign ownership of assets, once again contrary to the traditonal tariff jumping argument. Norbäck and Persson (2002) study explicitly the effect of discriminatory governmental policy forbidding IM&A and a non-discriminatory policy, showing that countries that liberalizare FDI might forego the possibility of welfare enhancing IM&A. Naturally the three models just described do not apply easily to the telecom market where services are not tradable. Mattoo, Olarreaga and Saggi (2004) instead, is more suitable. In the first stage of the three stage game, a Government and a MNC bargain to determine the mode of entry of the foreign company into the market; in the second stage, the MNC decides how much technology to transfer and, in the third stage, companies Cournot-compete facing an inverse demand function q = 1 − p for a homogeneous non-tradable good. Mattoo et al. (2004) show that when a foreign firm faces high costs of technology transfer, it generally prefers direct entry through Greenfield to Acquisition, because such high costs are associated to smaller cost advantage over domestic firms and a high acquisition price. Governments, on the other hand, prefer acquisitions because they lead to a larger extent of technology transfer by the foreign firm and a relatively high acquisition price for the domestic firm. Higher technology transfer under acquisition partly offsets its anti-competitive effect which, when combined with the larger producer surplus under acquisition makes it more attractive relative to direct entry. Thus, when the amount of technology transferred is high, it makes sense for government to restrict direct entry in order to induce acquisition, even in highly concentrated markets, improving welfare in the host country. If the cost of technology transfer is low, instead, governments tend to prefer Greenfields to Acquisitions. Under this scenario, direct entry is not only associated to a more competitive domestic market, but also brings more technology transfer. Acquisitions, instead, lead to higher concentration and low acquisition prices so that Governments might restrict Acquisitions (equity participation) to induce direct entry, even if markets are relatively competitive. The model I develop in the following pages, adapt Mattoo, Olarreaga and Saggi (2004) to the telecom sector by introducing two fundamental modifications. First of all, it considers explicitly a bell-shaped demand function for telecom connections that captures the network externalities originally modelled in Rohlfs (1974). By doing this, I remove the simplifying assumption of a linear inverse demand function, introducing non-linearities, whose importance has been emphasized by Röller and Waverman (2001). Secondly, I introduce capacity constraints in the supply of telecom connection, which have been shown to characterize TLDC, bringing the model close to the Kreps and Scheinkman capacity-quantity game. I maintain, however, the possibility for the MNC to transfer technology and I study the interaction of these three elements, network externalities, capacity constraints and technology transfer, to determine the equilibrium market outcome of liberalization process of telecom sector. Consistently, I begin to construct the network-enriched demand function for telecom connections in the next paragraph.

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4

Previous empirical literature

Before 1998, there has been basically no econometric study on the effect of telecom reforms, neither for developed countries, nor for transition, emerging, and developing countries. The methodologies used in the few esiting studies tend to vary and can be loosely grouped in two main categories: Case studies and econometric studies with a cross section or a panel data structure. Geographic coverage is also quite variable, and fluctuates between single country studies and wide panels including more than 100 countries. The study with the broadest scope, so far, is certainly Wallsten (2002), which covers 197 countries. The feeling one might have when reading these studies is that deregulation and liberalization of telecom services are associated with significant growth in teledensity and operating efficiency, and with significant improvements in the quality and price of telecom services. The impact of privatization is less clear-cut, but most studies agree that the combination of privatization and deregulation/liberalization is associated with significant telecommunications improvements. This is certainly the result predicted by Noll (2000) in his survey article examining the political economy of telecom reform in developing countries. Ros (1999) and Wallsten (2001) provide the empirical work that the econometric exercise taken here resembles the most, albeit different in the time coverage and the research question under investigation. Ros (1999) uses employs ITU data on 110 countries over 1986-1995 to examine the effect of privatization and competition on network expansion and efficiency. Although he does not focuses on foreign presence, he deals with private entryand finds that (1) countries with at least 50% private ownership of main telecom firm have significantly higher teledensity levels and growth rates; (2) both privatization and competition increase efficiency, (3) but only privatization is positively associated with network expansion. On a smaller sample of 30 African and Latin American countries from 1984-1997, Wallsten (2001) explores the effects of privatization, competition and regulation on telecom performance. He finds that (1) competition is significantly associated with increases in per-capita access and decreases in cost; (2) privatization is helpful only if coupled with effective, independent regulation; (3) increasing competition in combination with privatization is best. As a final point, he suggests that privatizing a monopoly without regulatory reforms should be avoided. In a similar study, Fink, Mattoo and Rathindran (2001) analyze the liberalization of basic telecom in 12 developing Asian economies over 1985-1999. They find that despite the demonopolization, most government strictly control entry, keep limits on private and foreign ownership, and maintain weak regulators. In countries where comprehensive reform has been implemented, there are significant higher levels of main line availability, service quality and labor productivity. Finally, Bortolotti, D’Souza, Fantini, and Siniscalco (2002), examine the financial and operating performance of 31 national telecom companies in 25 countries privatized in 19811998 using panel data at firm level. They find that privatization is significantly related to 9

higher profitability, output and efficiency, and to significant declines in leverages. Competition reduces profitability, employment and, surprisingly, efficiency after privatization, while the creation of an independent regulator significantly increases output.

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The model

Liberalizations, broadly defined, may concretely take different directions, departing from situations of public monopoly. The primary motivations for telecom reforms are assumed to be raising revenues to finance public budget deficits and collecting foreign exchange reserves, that is more macroeconomic motives rather than efficiency reasons related to the performance of the domestic telecom sector. Ramamurti (2000) proposes an informal model concerning privatization and deregulation as options for telecom reform. He defines an initial and a final stage, state-owned monopoly and full competition, respectively, and two intermediate stages through which a country may pass, private monopoly and early competitive structures. His classification actually finds an empirical counterpart in the real world where all these situations have been experienced to various degrees. In fact, many TLDC - especially LA nations - have privatized their telecom sectors without deregulating sectors, that is allowing entry, thanks to the legal formula of exclusivity rights. Exclusivity rights guarantee investors who buy public telcos that competitors will not be allowed to enter the market for a given time window, typically 6 to 10 years. As a matter of principle, countries could have privatized the telcos and contemporaneously deregulated the sector, but for a number of reasons that are not investigated here, they just opted for a change of ownership first, and thought to reach competitive structures at a later time. Other TLDC, including China, India and South Korea, instead, deregulated first and then (partially) privatized state-owned companies. Ravamurti (1999) focuses of LA and points out that “a final element in the privatization strategy of all countries in LA was permitting foreign ownership in the telephone sector. In all countries but Mexico, foreign investors were also allowed to own a controlling interest in the telephone service firms. Foreign investors were welcomed into this sector, even though they had been shooed away only a few decades earlier, because the countries needed hard currency badly and felt that the telephone sector could not be improved without the technical assistance of Western telephone companies. However, even countries that permitted foreign control required that local partners participate in the consortia that purchased these companies”. The objective of my model is to explain the different market outcomes deriving from the options Ramamurti explores in order to define a set of evaluation criteria for governmental choices. The model compares different market structures resulting from a move from a public monopoly to a market situation where a private entity can operate, for an abstract telecom sector. This is possibly the market for wireline connections or the market for wireless con-

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nections. In alternative, it is possible to think about fixed and mobile services as substitutes rather than complements, and imagine that the firms described in the model can offer both wireless and wireline connections so that a firm’s supply is the sum of the number of both types of connections. This interpretation of the model is intuitively appealing for developing countries where fixed and mobile services are actually perceived as substitutes, not least by policy-makers, as recently confirmed for African countries by Hamilton (2003). 5.1

The demand for telecom connections

Companies providing telecom connections face a demand function characterize by consumption network externalities. The non-tradable good studied hereby is “one connection to a telecom service” and is discrete in nature. The focus is not on modeling the good “use of the telecom connection”. In the above mentioned study, Mattoo, Orellaga and Saggi (2004), assume a linear inverse demand function of the form q = 1 − p and claim that the model of international entry they develop is suitable for the study of FDI entry in service sectors such as telecom. Their statement is completely correct if the telecom of developed countries are under consideration, but has to be better specified for less developed countries. In effect, the demand for telecom connections does not need to be downward sloped over its range of definition as Jeffrey Rohlfs (1974) initially pointed out in his seminal paper. In fact, telecom access as a good is said to exhibit network externalities because the utility that a consumer derives from a communication service increases as others increase the utilization of the service. This section will put up the demand curve for telecom used in the following pages, as in Shy (2000). Consider a set of potential telecom customers uniformly indexed by the variable q on the unit interval [0, 1] with density η > 0. Individuals 1, 2, 3, , n are assigned an index number q1 , q2 , ..., qη with q1 = 0, qη = 1. A low (high) value of q reflects a high (low) willingness to pay for the connection, meaning that customers with low (high) q place a high (low) evaluation on the good “being able to communicate . The density function captures the size of the population, namely there exist η consumers. The cumulative distribution function says, for each type q, how many customers exist having index types between 0 and q8 . If Q ∈ [0, 1] is the total number of customers that actually subscribe to the service, p the connection fee (price) of subscribing to the service, and Qe ∈ [0, 1] the expected number of customers subscribing to the network, individual q’s utility function is defined as ⎧ ⎨ (1 − q)Qe − p if the individual subscribes Uq = ⎩ 0 if he does not

(1)

To give an example, there are η2 customers, half of the total population, that are indexed on [0, 1/2]. The assumption of uniform distribution is convenient to keep calculations simple. 8

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The utility function exhibits network externalities because utility increases with the expected total number of customers. Utility depends on the identity of the individual and how he evaluates the service (q), on the expected number of subscribers (Qe ), and on the price of the connection. It captures network externalities in consumption because the utility of each individual depends positively on the expected number of subscribers connected to the (.) network. Moreover, the magnitude of ∂U ∂Qe depends positively on the individual evaluation of the service where high evaluation corresponds to low q. To define the consumers aggregate demand for phone services, consider a peculiar consumer indexed by qb. This individual is indifferent between subscribing and not subscribing to the service, at a given connection fee p. Thus, for the marginal consumer (1 − q) Qe − p = 0

(2)

or qb=

Qe − p Qe

(3)

For a given p, any consumer indexed by q > qb will not subscribe to the service whereas all consumers indexed q ≤ qb will do so. It is assumed that individual have perfect foresight, so that Qe = Q =ηq, and p = (1 − qb)ηb q

(4)

that is a quadratic function of qb. As Economides (1996) points out, this inverse demand function has rather to be considered a fulfilled expectations inverse demand function, because it is based on the realization of rational expectations. The intuition behind the curve is the following. At small demand level customers’ willingness to pay rises with the total demand, since the network effect dominates the price effect. Once the network size reaches half of the population the negative price effect dominates so that the inverse demand function becomes conventionally downward sloped. In the paper I omit the hat above q. 5.2

Description of the game

FDI in the telecommunications sector is modeled as a three-stage game. In the first stage, the government liberalizes the domestic sector. Typical liberalization processes in TLDC pass through three groups of measures that could be differently combined: Privatization (selling the state assets), trade liberalization, and FDI liberalization (allowing for new plants to be opened by foreigners, by allowing Greenfield investment and

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abolishing investment restrictions). Since telecom connections are non-tradable goods, only privatization and direct entry through Greenfield FDI matter concretely. Moreover, the resources required to entry a telecom market are elevated, so that it reasonable to assume that only foreign companies can afford entry. Foreign firms could be already MNC, having established in other countries, or become MNC by investing abroad for the first time. Thus, the choice faced by the MNC is to enter the domestic telecom market through: 1.

Acquisition or partial privatization of the public monopolist [call it Private monopoly or PM]: The foreign firm MNC can acquire a share σ of the monopolist with the payment of a privatization fee υP M ; in this case the privatized firm plays as a (possibly partially) private monopolist.

2.

Greenfield FDI [Direct Entry or DE]: The foreign firm MNC enters directly the market by paying υDE and setting up her own facilities for the supply of telecom connections; in this case the incumbent and the entrant compete à la Cournot.

This choice is the result of a bargaining between the MNC and the Government. The two agents consider the following variables: the privatization share σ, the privatization fee υP M , the price of the license awarded to the incumbent M , the price of the license awarded to the entrant DE , the monopoly profit supported by the market under PM (when the MNC the monopoly profit earned by the entry removes the capacity constraint) πP M , and πDE M publicly owned operator under DE (when the public monopolist cannot remove his capacity constraint) In case of partial privatization that leads to the Private Monopoly (PM) sub-game, the Government accepts any offer (σ, υP M , P M ) such that: (1 − σ)π P M +υP M +

PM

≥π DE M +

DE

(5)

This inequality will be fundamental in the bargaining process detailed below. In the second stage, the MNC decides the magnitude of the capacity expansion and the technology transfer. The effect of the MNC choice, resulting from the second stage, is represented graphically in graphs 1 and 2. Technology transfer reduces marginal costs, whereas capacity expansion removes the constraint and allows the market to reach the unbound optimal solution. [Figure 2 about here] In the third stage, depending on the mode of entry as defined in the first stage, either there exist two firms who compete à la Cournot, with possibly asymmetric marginal costs, or the private monopolist alone, reaping monopoly profits.

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is the set of existing firms, M is a initially state-owned national monopolist in the telecommunications sector. MNC is a multinational company interested in entering the national market. These firms supply telecom connections that customers evaluate as perfect substitutes, and that are not tradable at international level. Consumers’ decisions are represented and aggregated by the inverse demand function, p = (1 − qb)ηbq characterized by consumption network externalities9 . The cost function of the ith firm is I = [M, M N C]

⎧ ⎨ F + rηK + c ηq i i i i Ci (qi ; K i ) = ⎩ ∞

if

0 ≤ qi ≤ Ki

i = M, M N C

if

qi > Ki

ci = c + r, c + r − t

(6)

where Fi is the fixed cost, Ki = sup(qi ) is the installed capacity that can be thought as being fixed in the short run, r is the cost of capital per unit of installed capacity and is exogenously determined, ci is the constant marginal cost. ci is composed by a marginal production cost c and the financial cost of installing capacity (per unity of capacity) r , and can be reduced by t, the marginal-cost-reducing technology transferred by the MNC. 5.3

The unconstrained case

Domestic Public Monopoly. The total cost function of the monopolist M assumes the form: ⎧ ⎨ F + rηK + cηq M M CM (q; K M ) = ⎩ ∞

if

0 ≤ q ≤ KM

if

q > KM

(7)

According to this specification the quantity of connections demanded might actually be higher than the capacity installed by the monopolist. In this case part of the demand will be unsatisfied and some form of rationing will take place. Efficient rationing is assumed. Once capacity is installed KM = K M is given and the fixed component of the cost function can be redefined as ΦM = F M +rηK M

(8)

The monopolist has to take two decisions, that are formally a single stage maximization problem but are considered here as a two-stage problem, to get an intuitive grasp of what is going on. First, it has to install capacity and determine the optimal K M that will allow production and supply of the connections; secondly, given the installed capacity, it has to decide how many connections to provide based on demand. Let’s suppose, initially, that there are no capacity constraints, i.e. the monopolist can provide any number of connections. Consistently with the cost and the demand function described in the previous paragraph, the profit function is 9

See appendix 1.

14

π M (q) = p(q)ηq−C M (q)

(9)

In this case, the monopolist problem solves max {[(1 − q)ηq − (c + r)] ηq − FM }

that has solution

(10)

qe

1 qbM = + 3

µ

1 c+r − 9 3η

¶ 12

(11)

The latter is going to be the benchmark case of constrained public monopoly from which the liberalization process will depart. Now, consider the case where the MNC enters by acquiring the public monopoly. The government faces two options regarding the liberalization of telecom supply. It might either privatize the monopoly or let a second competitor enter. It is assumed that the small dimensions of many developing and transition countries might sustain at most two competitors. Privatization. The government privatizes a share σ ∈ [0, 1] of the monopolist by selling it to a foreign investor. It is assumed that no domestic investor in a developing country is able to take up the financial burden to buy the privatized share of the telecom operator. If a telecom MNC buys a share σ of the public telecom monopolist, she collects a share σπM of the monopoly profits but she can increase profits by transferring proprietary marginal-costreducing technology. The whole theory of MNC has developed on the idea that MNC have technological advantages due to the ownership of knowledge capital (technologies, brands, patents, and so on), that has the nature of a quasi-public good, being non-rival in consumption in the sense that the cost of replicating it is negligible compared the cost of producing it, but excludable, being it a property of MNC. Here, it is assumed that the MNC owns a technology that allows the participated firm to reduce marginal costs by an amount of t. In the second stage, t is determined by maximizing the profit function modified to take into account the technology transfer. Thus, if the MNC actually transfers technology the new total cost function for the privatized monopolist is ⎧ ⎨ F q if P M + rηKP M + (c − t)ηb CP M (b q; K P M ) = ⎩ ∞ if

0 ≤ qb ≤ KP M

(12)

qb > KP M

Where PM stands for Private Monopoly. As in Mattoo et al (2004), the cost of transferring technology is assumed to be a quadratic function T (t) of t. 2

T (t) = τ2t

15

t≥0

(13)

The convexity of the technology transfer cost function depends on the parameter τ ,so that τ ≥ 0.

∂ 2 T (t) ∂t2 =

In the case of partial privatization the problem for the MNC is to maximize the profit function modified taking into account technology transfer and the ownership structure of the acquisition: M M πP [b q (t); t] = σπP q (t); t] −T (t) = σ {p [b q (t)] ηb q (t) − CM [b q (t)]} −T (t) f M [b

(14)

If there are no capacity constraints, given the optimal level of technology t chosen at stage 2, the problem of the domestic (partially privatized) monopolist has a solution similar to the one found for the public monopolist with a difference in the structure of the marginal cost that depends explicitly on t: 1 qbP M (t) = + 3

µ

1 c−t+r − 9 3η

¶ 12

(15)

In the second stage, the problem of the MNC is then to choose the quantity of technology to transfer to maximize her profits on that market: max {σ ([(1 − qb(t))ηb q (t) − (c + r − t)ηb q (t)] − ΦM ) − T (t)} t

(16)

whose FOC defines the optimal level of technology tP M as an implicit function of the ownership share σ. ⎡

⎢2 ⎣ + 3



³

t 1 9



c−t 3η

´ 12 −

µ

1 c−t − 9 3η

¶ 12

The second order condition for tP M being argmax is ⎡ ⎢ ⎣



³

1 1 9



c−t 3η

´ 12 −

t 4η [η − 3(c − t)]

³

1 9



⎥ 2 3tτ =0 ⎦η − 2σ ⎤



3 ⎥ 2 ´ 12 ⎦ η − 2σ t < 0 c−t

(17)

(18)



that always holds for η big enough. Moreover, for a large η, the first order condition is approximately ση −τ t = 0 3

(19)

1 ση 3 τ

(20)

and tP M =

Simulation results using consistent parameter values show that such a relation is positive as in Mattoo et al. (2004). 16

Thus, the technology transferred by the MNC increases wits her share of ownership PM > 0),increases with size of the population of consumers ( ∂t∂η > 0) and decreases with PM the increase of the marginal cost of technology transfer ( ∂t∂τ > 0) Direct Entry. The second option that the Government could explore to liberalize entry is letting a second operator into the market. In the telecom sector a whole set of regulatory problems arise, concerning interconnection and access to existing networks. The approach taken here is to assume away all regulatory problem and focus on a simplest framework of entry. Direct entry is modeled as a Greenfield FDI, wherein the foreign firm establishes a new wholly-owned company that begins to compete with the domestic firm. The domestic firm is still publicly owned, is capacity constrained and cannot afford the marginal-cost-reducing technology, whilst the MNC can transfer technology and has free access to financing at rate r, to set up the supply of new connections and expand the capacity of the market. It is assumed that companies compete à la Cournot on the quantities, after the duopoly is set up with the establishment of the new company. In the third stage, capacity and technology are given and firms compete à a Cournot. Each duopolist i = M, M N C maximizes a profit function that takes into account the effect of the quantity produced by the competitor on her own marginal revenue. As a matter of fact, ΦM and ΦM N C can be different. The problems of the two firms PM ( ∂t∂σ

max {[(1 − qbM − qbM N C ) η (b qM + qbM N C ) − (c + r)] ηb qM − ΦM }

(21)

qM + qbM N C ) − (c + r − t)] ηb qMNC − ΦM N C } max {[(1 − qbM − qbM N C ) η (b

(22)

qeM

qeMN C

Have first order conditions10 :

¢ DE h DE ¡ DE ¢2 ¡ ¡ DE ¢2 i 2 DE DE η −cηb bM + qbM N C − qbMNC −3 qbM +2 1 − 2b qM qM =0 NC q

h ¡ DE ¢2 ¡ ¡ DE ¢2 i 2 ¢ DE DE DE DE −3 qbM + 2 1 − 2b q + q b − qbM qM η − cηb q b NC M MNC M NC = 0

(23)

(24)

with associated reaction functions: ¡ DE ¢ ¡ DE ¢ DE DE 1 0 And SOCs −3 q bM + 2 − 4b ≤ 0 and −3 qbMN ≤ 0,requiring the qnMNC qM C + 2 − 4b

following conditions hold jointly:

DE ≥ 1 qeM NC 5 DE ≥ 1 qeM 5

.

17

h i1 ¡ DE ¢2 3(c+r) 2 DE − qbM 1 + qbM NC NC − η h i1 ¡ DE ¢ 1 ¡ ¡ DE ¢2 ¢ DE ± 1 1 + q DE − 3(c+r−t) 2 = R qbM − qbM bM = 3 1 − 2b qM 3 η

¡ DE ¢ DE qbM = R qbM NC = DE qbM NC

1 3

¡

¢ DE 1 − 2b qMNC ±

1 3

(25)

Because of the non-linearity of the demand function, each optimization actually implies two reaction functions. Letting η grow, the two possible reaction functions of the firm diverge. For both the ex-monopolist and the MNC only the “+” solution is assumed. It is fairly tough to find an explicit solution for the quantities produced by the duopolists in equilibrium. However, it is reasonable to assume η big once again, so that the solution DE DE DE bM + > qbM ' 0.439. converges rapidly to qbM NC = q 5.4

Capacity Constraints

Capacity constraints are assumed to be completely exogenous, Depending on the relationship between qbM and K M two situations may arise. If qbM ≤ K M , then the monopolist supplies exactly qbM and there exist excess capacity equal to K M − qbM . Note that such a situation is not profit maximizing being strictly dominated by installing K M = qbM and saving on the cost of capacity r. On the contrary, if qbM ≤ K M ,then the monopolist cannot meet all the demand and has to set the supply at K M , leaving unsatisfied qbM − K M potential customers. Monopoly. Formally, the monopolist solves a constrained maximization problem in the form max {[(1 − qb)ηb q − (c + r)] ηb q − ΦM } qe

(26)

s.t. qb ≤ K M

Where, by assumption 1 KM < + 3

µ

1 c+r − 9 3η

The problem can be restated in terms of K ,



=b qM

max {[(1 − K)ηK − (c + r)] ηK − ΦM } K

(27)

(28)

s.t. K ≤K M

that has (corner) solution K =K M =b qM

(29)

The graphical representation of the price-quantity-profit equilibria for the unconstrained and the constrained case are represented in Figure 4. [Figure 4 about here]

18

It might happen that, if the dimension of the network is small because the installed (constrained) capacity is limited, the monopolist might even incur in losses due to the fact that marginal costs are higher than the price, at low qb. Profits can be derived by substituting the optimal value in the profit function (9) to get, with and without capacity constraints: η πM (b qM ) = [η − 4(c + r)] +[η − 2(c + r)] 9 2

µ

1 c+r − 9 3η

3

¶ 12

η −ΦM 3

2

πM (b q M ) = η K M +{η[η − (c + r)}K M −ΦM

(30)

(31)

Profits are non-negative only if

η [η − 4(c + r)] +[η − 2(c + r)] 9 3

µ

1 c+r − 9 3η

¶ 12

η ≥ ΦM 3

2

η2 K M +{η[η − (c + r)}K M ≥ ΦM

(32)

(33)

And necessarily, πM (bqM ) ≥ πM (bqM ) because ∂π(.) b ≤ qbM . ∂ qe > 0 for q With capacity constraints, maximization problem solved by the MNC11 is ª © max σπ P M [K(t); t] − T (t) t

(34)

s.t

K ≤K

whose solution is defined implicitly by ⎡

⎢2 ⎣ + 3

PM



³

t 1 9



c+r−tP M 3η

´ 12 −

µ

PM

1 c+r−t − 9 3η

¶ 12



⎥ 2 3tP M τ =0 ⎦η − 2σ

(35)

This equilibrium is depicted in Figure 4b where the darker shaded area represents the gross profit before technology transfer and capacity expansion, while the lighter shaded area is the profit after the implementation of the decisions taken by the MNC in the second stage. The technology transfer has the effect of lowering the marginal cost as in figure 2a and increasing the number of connection supplied in equilibrium. Besides transferring technology and lowering marginal costs however, the foreign company has the financial resource to invest and expand capacity to the optimal level, removing the constraint the public monopolist was facing before privatization. [Figure 4b about here] What happens if the ex-monopolist is capacity constrained, and the constraint cannot be removed as it has been assumed for TLDC? ³ ´1 1 c+r−t 2 1 1 Under the assumption K < 1 + − 3η . 3 9 19

Then the quantity of connections supplied by the monopolist might be lower or higher DE . than qbM The optimal quantity supplied by the monopolist would be then: ⎧ ⎨ qbDE M ⎩ K

DE K ≥ qbM

if

(36)

DE K ≤ qbM

if

In the first case, the situation boils down to the equilibrium market outcome just discussed. In the second case, instead, the ex-monopolist has a fixed capacity with no financial resources to expand, let alone block or prevent the competitor from entering. Thus, the competitor actually faces a residual demand function and could behave like a monopolist on the residual demand, capture all the potential users who are not connected to the network. As a matter of principle, the MNC has now the option of maximizing the residual demand (the one not served by the ex de-jure monopolist, as a de facto monopolist) or capturing the oligopoly profits of her competitor on the number of connections not provided due to the capacity constraint. If there were no capacity constraint, the ambiguity could be solved by adding an additional hypothesis about the existence of switching costs. DE and the In the case studied here, however, the ex-monopolist is constrained at K = qbM entrant solves for the residual demand as an actual monopolist (with a superior technology), setting 1 DE qbM q M −K M = + N C =b 3

DE

qbMNC =

µ

1 c−t+r − 9 3η

¶ 12

−K M

(37)

∙ ¸1 ¢ 1 ¢2 ¡ 1¡ 3 (c + r − t) 2 1 − 2K M ± 1 + K M − K M − 3 3 η

while the ex-monopolist sets

DE qbM =K M

(38)

and the total number of connection offered on the market is DE

DE PM qbMNC +b q M ≥b qM

(39)

which is higher than the quantity offered by a private monopolist willing to improve the technology and reduce the marginal cost. This equilibrium is depicted in Figure 5.

6

Government-MNC Bargaining

Let’s now go back to first stage and see how the Government who decides to liberalize can behave. This choice is the result of a bargaining between the MNC and the Government. The two agents consider the following variables: the privatization share σ, the privatization 20

fee υP M ,the price of the license awarded to the incumbent M ,the price of the license awarded to the entrant DE , the monopoly profit supported by the market under PM (when MNC entry removes the capacity constraint) πP M , and πO M the monopoly profit earned by the publicly owned operator under DE (when the public monopolist cannot remove his capacity constraint) In case of partial privatization that leads to the Private Monopoly (PM) sub-game, the Government accepts any offer (σ, υP M , P M ) such that: (1 − σ)π P M + υP M +

PM

≥ π DE M +

DE

(40)

It is reasonable to assume that the price of the license award to every operator is similar, so that

PM

'

DE

(41)

and (40) boils down to (1 − σ)π

PM

¡ ¡ P M ¢¢ qM ) qb t (σ) +υ P M ≥π DE M (b

(42)

If the MNC has all the bargaining power, then the inequality is binding in equilibrium: ¢¢ ¡ ¡ υP M =π DE qM ) −(1 − σ)π P M qb tP M (σ) M (b

(43)

The MNC makes an offer (σ, υP M ), based on the following optimization problem: ¢¢ £ ¤ © ¡ ¡ ª max σπ P M qb tP M (σ) − T tP M (σ) − υ P M σ,υ

s.t. υP M =π DE qM ) −(1 − σ)π M (b

or,

PM

¡ ¡ P M ¢¢ qb t (σ)

¤ª £ ¤ £ ¢¢¤ª © © £ ¡ ¡ max σπ M qb tP M (σ) − T tP M (σ) − π DE qM ) − (1 − σ)π P M qb tP M (σ) M (b σ

(44)

(45)

(46)

or, equivalently,

¤¢ £ ¤ª © ¡ £ max π M qb tP M (σ) − πDE qM ) − T tP M (σ) M (b σ

that has FOC

or

q ∂tP M ∂T ∂tP M ∂πP M ∂b · PM · − PM · =0 ∂ qb ∂t ∂σ ∂t ∂σ

21

(47)

(48)



∂T ∂πP M ∂b q − PM P M ∂b q ∂t ∂t

¸

∂tP M =0 ∂σ

(49)

where the term in brackets is null because of the envelope theorem . PM Since ∂t∂σ > 0, the problem has a corner solution σ = 1. RESULT 3 In equilibrium, σ = 1 and υP M = πDE M The MNC who has all the bargaining power fully acquires the incumbent by paying a fee equal to the profits that the public duopolist would yield in a hypothetical alternative oligopoly The result confirms Mattoo et. al. (2004), and depends crucially on the assumption that all the bargaining power lies in the hands of the MNC. Intuitively, the full acquisition makes the MNC reap the monopoly profits the market can sustain after capacity expansion. Under Direct Entry, instead, the public monopolist would still be there and make positive profits by producing the (constrained) quantity .

7

Domestic Welfare, Policy Implications and Extensions

As a matter of principle, there are three elements the Government must take into consideration when choosing the design of the liberalization process, allowing entry, either partial or full privatization of the public monopolist or direct entry of a second operator: quantities, prices and revenues from de-regulation (privatization fees and licenses). Under DE, it has been pointed out that the total number of connections supplied to the market is higher, as well as the market price is lower as compared to the quantity and the prices of monopoly as determined in the capacity-quantity sub-games. This results stems straight out of the realistic hypothesis that the country experiences capacity constraints in the supply of telecom connection. Mattoo, Olarreaga and Saggi (2004), on the contrary, emphasize that Direct Entry is always optimal as compared to Acquisition under the assumption in their model, but they assume away capacity constraints. The result obtained here, instead, highlights the role of MNC in removing the capacity constraint in the domestic market. Allowing entry either through privatization or demonopolization is always better that continuing the constrained public monopoly. Let us consider prices now. In this setting, prices after liberalization are slightly different under direct entry and acquisition. However, they could be either higher or lower than the original prices charged when capacity constraints were binding. In particular, the more serious the constraint the most likely is that final equilibrium prices are higher than before the liberalization process. This result depends mainly on the assumption of an inverse U-shaped demand function and would not characterize the market outcome under the assumption of a monotonically decreasing demand function. 22

This leaves room to a number of considerations about the importance of regulatory authorities to discipline the pricing mechanism of the telecom providers. A natural extension of the model would be to repeat the game once. Imagine that the outcome of the first game is acquisition. Then, the duopoly is formed by a constrained public ex-monopolist and a technology-rich foreign-owned firm. Then, imagine that the first time the game is played the Government does not want to introduce a completely private duopoly because it is competing with other Governments to attract the MNC, so that it decides to allow either direct entry or privatization but not both (which might explain also why the MNC has all the bargaining power). The Government could still decide to privatize the public monopoly at a later date, after the foreign owned company has entered, begun to transfer technology and expanded capacity. At this point, the entrance of a second operator through Greenfield FDI would imply a standard duopoly market structure where none of the companies is capacity constrained. In this case, it can be shown that the oligopolists would split the profits sustained by the market almost evenly. By delaying entrance of a second operator the Government obtains the complete removal of the capacity constraints, the transfer of technology, the privatization fees, the entry fees and manages to reach a Paretosuperior equilibrium by which prices are lower and quantities are higher than they would be otherwise under the circumstances detailed in this paragraph. However, this strategy is not risk-less because the Government might be too weak from an institutional point of view to pursue the public national interest independently of the pressures of the established operator. This political economy argument might explain, in turn, why back in the 1980s and early 1990s many Governments of TLDC have granted exclusivity periods or delayed privatization until more contingent needs of fresh cash have forced them to move intensify the liberalization by allowing further entries.

8

Empirical Test

The analysis is carried out at sector level, solely, using the proprietary dataset ISLA-Telecom, compiled by the author, containing information on 46 countries in Central and Eastern Europe, North Africa, Middle East, Latin America, Central America and in the Caribbean12 . Panel data area vailable for 1989-2002. The time series have different length so that, for econometric purposes, the complete panel dataset is available only for 12 year (1989-2000). To complement the ISLA-Telecom database, indicators on telecommunications have been elaborated upon data published in the ITU World Telecommunication Indicators 2002 CDROM and the World Development Indicator 2002 of the Worldbank. The variables from the database that have been used in the econometric analysis are listed in Table 1. 1 2 Listed

in the appendix.

23

[Table 1 about here] Dependent variables represent the available indicators of efficiency for the telecom sector of TLDC. They include (1) Teledensity (f _td), the number of mainlines per capita, is the basic indicator in applied analysis, being it the most reported variable as a synthetic measure of the degree of development of the telecom sector of a country.A mainline is “a telephone line connecting the subscriber’s terminal equipment to the public switched network and which has a dedicated port in the telephone exchange equipment.” It indicates the level of penetration of telephone service in a country. As an indicator of access to telecom services, teledensity has a number of drawbacks, including the fact that many people have access to several lines (at home, at work, phone, fax), and the fact that access can be obtained through other means such as public phones and call centers where many people use a unique line; (2) the number of fixed lines installed (f _f ixedlines); (3) Teledensity growth (f _tdg) is the annual rate of growth of teledensity; (4) the teledensity/staff ratio (f _td/staf f ) weights teledensity by the number of people employed in the sector; (5) the number of cellular subscriptions per 100 persons (c_td) is the equivalent of teledensity for wireless services. Control variables include: (1) GDP per capita (gdpuspc), (2) Population (pop), and (3) Percentage of the total population living in urban areas (urbpop), and are used to take into account country differences in terms of level of well-being, size, and urbanization, the latter being thought to ease network expansion. Since private investors can be domestic of foreign, originally, both shares of the incumbent owned by private investors (f _privshare) and foreign investors (f _f dishare)have been computed ending up to be very correlated. This correlation is natural given the strong involvement of foreign operators in telecom reform of transition, emerging and developing country but is problematic for the empirical analysis in such correlation does not allow to disentangle the effect of foreign control from the effect of private control, given the fact that if control. A selection of these variables has been summarized in panels 1, 2 and 3, distinguishing the 4 macro-regions the 46 countries in the panel belong in. [Panel 1, 2, and 3 about here] Panel 1 refers to the timing of privatization of the incumbent (f _yearpriv ). Typical privatization reforms in developing countries involve selling a controlling stake in the national telecom operator to a Western operating company, usually in exchange for a large front-up payment plus binding promises to aggressively update and expand service levels after gaining control. Thus, most privatizations are initially partial. From both tables and graphs it is clear that Latin America Countries have been the front-runners of the process of privatization, that has began in the second half of the 1980s. Central and Eastern European countries, 24

instead, have privatized very quickly in the second half of the 1990s, rapidly catching up and surpassing South and Central American Countries; finally, Mediterranean countries have been lagging behind and still count just a few operators with private participation. It is relevant to note that the average share of privatization has reached 40% only in 2001, showing that many countries are only shy privatizers. Overall, however, the trend has been growing. The second institutional reform that has been emphasized, the establishment of separate and possibly independent regulators (ysepregul) has followed similar patterns in the regions considered. South and Central American countries have been the early reformers, followed by CEECs. The MED countries have been catching up, however, showing an almost unexpected reforming path. Finally, Panel 3 reports average teledensity and fixed lines by regional group. Trends have generally been increasing, with a marked growth of the absolute number of mainlines, particularly in South America. According to teledensity data, CEECs countries have the best endowment of communication infrastructure followed by the MED, and far away from both CA and SA. I presents the results of the estimation organizing them by telecom indicator, i.e. by dependent variable. For all dependent variables, the Hausman specification test does not lead to the rejection of the Fixed Effects model13 . [Table 2-6 about here] Results for teledensity (f _td) are reported in Table 2 for the FE model, the RE model and OLS. Control variables are significant except for population (pop): GDP per capita (gdpuspc) is positively correlated with teledensity, as well as the percentage of the population living in urban areas (urbpop). This is consistent with the informal evidence provided in Figure 1, that shows the positive correlation between GDP per capita of a country and its endowment of connections. As for reform related variables, initial privatization processes (f _ypriv) turns out to be non significant, while the establishment of a separate regulator (ysepregul) has a positive significant effect on teledensity. The foreign-owned share of the incumbent (f _f dishare) has a positive significant sign, its square (f _f dishareSQ) a negative significant sign in all FE, RE and OLS. This would seem to suggest that there exist a positive concave relationship between the share of foreign ownership of the incumbent and teledensity, consistently with the theoretical model presented in the previous sections. As for the competition variable, if the number of wireless operators not owned by the incumbent (c_numcomp) is definitely not significant, the variable capturing FDI cellular penetration (c_f dipen) is, once again with a concave relationship, as captured by the squared 1 3 At

10% significance level.

25

term (c_f dipenSQ). Foreign penetration in the cellular market captures the competitive effect coming from foreign presence in the wireless market, and it is equal to the sum of the share of cellular operators owned by foreign telecom companies. Thus, the global presence of many foreign owned operators provide a competitive stimulus to the fixed operator, who apparently increases teledensity to respond to such a form of competition. The regression that makes use of teledensity growth (f _tdg ) as a dependent variable, brings substantially no significant coefficient, confirming one of Ros (1999)’s results. Only the percentage of urban population and the existence of a separate regulator turn out to be positively and significantly correlated to fixed teledensity growth. Turning to the third telecom indicator reported in Table 4, the number of fixed lines per units of employees in the telecom sector (f _td/staf f ), the results are very similar to the ones reported for teledensity with the control variables, GDP per capita, and urbanization, significantly and positively correlated to the indicator. Some of the other regressors maintain the same significance and signs of the previous regressions, in particular the year of establishment of a separate regulator, that can be thought as a proxy for telecom reforms. Table 6 contains the output of the regression run using as a regressor the number of cellular subscriptions per 100 persons (c_td), an indicator of teledensity for the wireless sector. Here the only significant control variable is GDP per capita (z_gdpuspc). Again, the establishment of a separate regulator (yseparegulator) has a positive effect on cellular teledensity. As expected, the number of operators present on the market (c_numop) is positively correlated to the indicators and significant, as well as the proxy for cellular FDI penetration (c_f dipen). In effect, the relationship, besides being positive, is be concave, the impact-effect being stronger when foreign penetration is lower.

9

Conclusions

There is mounting optimism at the international level on the potential relevance of the information technology revolution to help less developed countries “leapfrog” development. This has led to a new interest in the study of reforms in the telecom sectors. telecom are thought to help developing countries skip over stages of development and accelerate their pace of development with the aim of becoming members of the post-industrial society. However, it is well documented that many countries are still endowed with tiny networks, although, at the same time, network developments often take place rapidly. This observation raises a natural research question: “What is the impact of foreign capital and Multinational Corporations on the efficiency of telecom sectors of transition and developing countries?” To answer this question, I have presented a model based on three empirical regularities that characterize telecom sectors of transition and less developed countries: (1) The existence of public monopolies, and an on-going process of de-monopolization and privatization;

26

(2) Extended waiting lists reaching 4 years, and consumers willing to put down deposits for the privilege of waiting for a phone line; (3) The intensified activity of multinational corporations as active actors in the telecom sectors. Given these regularities, I infer that some countries experience capacity constraints due to past under-investment in telecom infrastructure. Thus, entry of foreign investors through Foreign Direct Investment might be a good policy instrument in the hands of governments who want to remove the under-investment constraints and improve the supply of telecom services, whereas different modes of entry might naturally have different impacts on domestic telecom development, ranging from differences in the extent of technology transfer and/or capacity expansion and/or competition implications. In general, there are different elements the government must take into consideration when choosing the design of the liberalization process, allowing entry, either partial or full privatization of the public monopolist or direct entry of a second operator. My model shows the effect of entry on quantities, prices and revenues (privatization fees and licenses) under the realistic assumption of capacity constraints, for these different options. The result obtained highlights the potential role of MNC in removing such capacity constraint in the domestic market. I have shown that, in theory, allowing entry either through privatization or de-monopolization is always better than continuing the constrained public monopoly. This however does not address a number of considerations about the importance of regulatory authorities for disciplining the pricing mechanism of the telecom providers, which I have not considered but is another important research area. To verify the empirical validity of my model, I have constructed a proprietary database called ISLA-Telecom and performed an econometric analysis based on a panel of 46 transition and emerging countries for the period 1989-2000. Using a set of different indicators for the telecom sector, I have shown that privatization processes are significantly correlated with increases in teledensity and that the share of foreign-ownership in the incumbent has a positive, concave impact on sectorial indicators. As for regulatory reforms, I have confirmed that the establishment of a separate regulator has a positive significant effect on teledensity of a magnitude close to that of privatization. As for competition, the variable “foreign penetration in the cellular market”, which captures the competitive effect coming from foreign presence in the wireless market, apparently increases teledensity, teledensity growth and the ratio between fixed lines and staff, possibly as a response to such a form of competition. Also the number of cellular subscription per 100 persons responds positively to the establishment of a separate regulator, to the number of operators present on the market and to cellular FDI penetration. To conclude, let me quote Noll (2000) who claims that the “main hole in research about neo-liberal reform of telephone service in developing countries is empirical knowledge. [...] The comparative performance of different methods for reorganizing the incumbent and different regulatory systems and their dependence on the history and circumstances of a country,

27

in some cases have not been identified by theory, and in other cases have not been quantified”. This paper contributes to fill in such hole by focusing on the specific role of foreign companies, which has been previously neglected by the literature both theoretical and empirical. Despite the research effort, a number of issues remain unresolved and open to further research. My theoretical analysis underestimates the role of regulation. Besides modeling the role of regulators in transition and developing countries, it would be useful to collect information on the type of regulation adopted by the countries I study, because the variation is without doubt large. In addition, no explanation is given to the empirical fact that most countries actually limit the share of FDI in the telecom sector. The most straightforward extension of my model would be to change the structure of the bargaining game and remove the assumption that the MNC has all the bargaining power. This would certainly allow explain why there exist caps on foreign equity (and voting) participation. As for the pure empirical analysis, it would be important to collect firmspecific data, rather than country data that are relatively easier to access, but do not provide a more detailed view of the effects of privatization, competition and regulation on firms’ strategies. In particular, I expect that regulatory changes might have different effect on the governance structures of privatized telecom, on investment patterns and on capital structure variations. Finally, the econometric studies carried out so far neglect the possible effect of endogeneity in the regression analyses. The same factors affecting telecom performance might well affect reforms, competition, privatization and regulation, also, and more refined econometric techniques are expected to control for endogeneity. It should also be understood that the quality of data collected for non-developed countries is widely acknowledged to be poor and many results stemming from empirical analyses might be negatively affected by such data problems. The chief research agenda is now to combine the richness of institutional detail with a large and detailed enough statistical sample to support stronger conclusion about the direct links between distinct policy decisions and sector performance.

References [1] Aghion, Philippe, and Mark Schankerman (2000), “On the Welfare Effects and Political Economy of Competition-Enhancing Policies,” Economic Journal, vol. 114 (October 2004), 804-834. [2] Auriol, Emmanuelle, and Pierre M. Picard (2002), “Privatizations in Developing Countries and the Government’s Budget Constraint”, WP, IDEI Toulouse. [3] Bjorvatn, Kjetil (2004), “Economic integration and the profitability of cross-border mergers and acquisitions,” European Economic Review, Volume 48, Issue 6 (December), Pages 1211-1226.

28

[4] Bortolotti, Bernanrdo, Juliet D’Souza, Marcella Fantini, and Domenico Siniscalco (2002), “Sources of Performance Improvement in Privatised Firms: A Clinical Study of the Global Telecommunications Industry”, Telecommunications Policy. [5] Boylaud, Olivier, and Giuseppe Nicoletti (2000), “Regulation, Market Structure and Performance in Telecommunications”, OECD Economic Department WP No. 237. [6] Brainard, Lael (1993), “A Simple Theory of Multinational Corporations and Trade with a trade-off between Proximity and Concentration”, NBER WP No. 4269. [7] Buckley, Peter J. ad Mark C. Casson (1998), “Analyzing Foreign Market Entry Strategies: Extending the Internalization Approach”, Journal of International Business Studies, 29:3, 539-562. [8] Contessi, Silvio, Claudia Guagliano and S. Haller (2004), “Modes of International Entry in Theory and Practice: A survey”, manuscript. [9] Economides, Nicholas, (1996), "The Economics of Networks," International Journal of Industrial Organization, vol. 14, no. 6 (October 1996), pp. 673-699. [10] Fink, Carsten, Aaditya Mattoo, and Randeep Rathindran (2002), “Liberalizing Basic telecommunications: The Asian Experience”, HWWA-Institut fur Wirtschaftsforschung, Discussion Paper No. 163. [11] Görg, Holger (2000), “Analysing foreign market entry: The choice between greenfield investment and acquisitions”, Journal of Economic Studies, 27:3, 165-181. [12] Graham, Edward (2001), “Subsidies, Market Closure, Cross-Border Investment, and Effects on Competition: The Case of FDI in the Telecommunications Sector”, Institute for International Economics Working Paper 2001-2. [13] Hamilton, Jacqueline (2003), “Are main lines and mobile phones substitutes or complements? Evidence from Africa”, Telecommunications Policy, 27:109-133. [14] Horn, Henrik and Lars Persson (2001), “Endogenous Mergers in Concentrated Markets”, International Journal of Industrial Organization, 2001. [15] Kreps, David M. and Jose’ A. Scheinkman (1983), “Quantity precommittment and Bertrand Competition yields Cournot Outcomes”, Bell Journal of Economics, 14:326-337. [16] Kornai, Janos (1979), “Resource Constrained versus Demand-Constrained Systems”, Econometrica, 47:801-19. [17] Mattoo, Aaditya, Marcelo Olarreaga and Kamal Saggi (2004), “Mode of foreign entry, technology transfer, and FDI policy”, Journal of Development Economics, Volume 75, Issue 1, (October), pages 95-11. [18] Noll, Roger G. (2000), “Telecommunications Reforms in Developing Countries”, in Anne O. Kreuger Ed., Economic Policy Reform: The Second Stage, University of Chicago Press.

29

[19] Norbäck, Pehr-Johan and Lars Persson (2004), “Privatization and Foreign Competition”, Journal on International Economics, Vol. 62, 409-416. [20] Norbäck, Pehr-Johan and Lars Persson (2002), “Cross-Border Acquisitions and Greenfield Entry”, IUI WP No. 570. [21] Ramamurti, Ravi (2000), “Telecom Reform Options: Privatization Vs. Deregulation”, Columbia Journal of World Business. [22] Rohlfs, Jeffrey (1974), “A Theory of Interdependent demand for Communication Service”, Bell Journal of Economics, 5:16-37. [23] Roller, Lars-Hendrik and Leonard Waverman (2001), “Telecommunications Infrastructure and Economic Development: A simultaneous Approach”, American Economic Review, 91:4:September:909-923. [24] Ros, Agustin (1999), “Does Ownership or Competition Matter? The Effects of Telecommunications Reform on Network Expansion and Efficiency”, Journal of Regulatory Economics, 15:1:65-92. [25] Shy, Oz (2000), The Economics of Network Industries, Cambridge University Press. [26] Wallsten, Scott (2001), “An Econometric Analysis of Telecom Competition Privatization, and Regulation in Africa and Latin America”, Journal of Industrial Economics, 49:1:1-20. [27] Wallsten, Scott (2002), “Does Sequencing Matter? Regulation and Privatization in Telecommunications Reforms”, World Bank Working Paper.

30

List of Countries Central and Eastern Europe (CEEC): (1) Albania, (2) Bulgaria, (3) Croatia, (4) Czech Republic, (5) Estonia, (6) Hungary, (7) Latvia, (8) Lithuania, (9) Poland, (10) Romania, (11) Slovak Republic, (12) Slovenia; Mediterranean Countries (MED) : (13) Algeria, (14) Cyprus, (15) Egypt, (16) Israel, (17) Jordan, (18) Lebanon, (19) Libya, (20) Malta, (21) Morocco, (22) Syria, (23) Tunisia, (24) Turkey; South America (SA): (25) Argentina, (26) Bolivia, (27) Brazil, (28) Chile, (29) Colombia, (30) Ecuador, (31) Paraguay, (32) Peru, (33) Uruguay, (34) Venezuela; Central America and Caribbeans (CA): (35) Barbados, (36) Costa Rica, (37) Cuba, (38) El Salvador, (39 ) Guatemala, (40) Haiti, (41) Honduras, (42) Jamaica, (43) Mexico, (44) Nicaragua, (45) Panama, (46) Trinidad and Tobago.

Figure 1 Correlation between teledensity and GDP per-capita (178 countries) 45000 40000 35000 30000 25000 20000 15000 10000 5000 0

0

20

40

60

80

100

Figure 2 p

p

c c-t

c

q



K

K



Effect of the reduction of marginal costs

Effect of capacity expansion due

due to technology transfer

to the enlargement of the network

36

Figure 3 p

p

MC

pˆ M

pˆ PM

CM+r CM + r D(p)

CM-t+r

CM+r-t D(p)

qˆ M

1



qˆ M

MR

1



MR

Figure 5

p

p MC

MC



pˆ M

D(p)

CM + r

CM+r

CM-t+r

D(p)

qˆ MM

1

1



qˆ MDE MR

37

DE qˆ MNC

MR



Table 1. List of variables: Description and source

VARIABLE

TO BE READ AS

SOURCE

f_fixedlines

Number of fixed lines installed

World Telecommunications Indicators (2002)

f_td

Teledensity = (Number of fixed lines installed)/(Population)

World Telecommunications Indicators (2002)

f_tdg

Teledensity growth = (f_tdt - f_tdt-1) / f_tdt-1

World Telecommunications Indicators (2002)

f_td/staff

Teledensity per Tlc worker =

World Telecommunications Indicators (2002)

Teledensity / staff employed in the Tlc sector c_td

Number of Cellular subscriptions per 100 person

World Telecommunications Indicators (2002)

gdpuspc

GDP per capita in US Dollars at 1995 prices.

World Development Indicators (2002)

pop

Population/1,000,000

World Development Indicators (2002)

urbpop

Percentage of the Total Population living in urban areas

World Development Indicators (2002)

f_yearpriv

Year of initial Privatization of the incumbent, possibly partial (Dummy Variable)

ISLA-Tlc database

ysepregulator

Year of establishment of a separate regulator (Dummy Variable)

ISLA-Tlc database

f_fdishare

Share of foreign Tlc companies in the incumbent at or after privatization

ISLA-Tlc database

c_numcomp

Number of cellular operators not owned by the incumbent

ISLA-Tlc database

c_fdishare

Average share of FDI in cellular operators

ISLA-Tlc database

c_numop

Number of cellular operators

ISLA-Tlc database

c_fdipen

Foreign penetration in the cellular market, equal to the sum of the FDI shares in cellular operators

ISLA-Tlc database

c_fdipenSQ

Square of c_fdipen

ISLA-Tlc database

38

Panel 1. Partial Privatization of the Incumbent Year of Initial Privatization of the Incumbent by region No. GROUP 1989 12 CEE 0 12 MED 0 10 SA 1 12 CA 4 46 Total

5

1990 0 0 3 4

1991 0 0 3 4

1992 0 0 3 4

1993 2 0 3 4

1994 2 0 4 4

1995 3 0 5 5

1996 3 1 5 5

1997 3 1 5 6

1998 4 2 6 8

1999 8 2 6 8

2000 10 3 6 8

7

7

7

9

10

13

14

15

20

24

27

2001 2002 10 11 3 3 6 6 9 9 28

29

Average Share of Privatization of the Incumbent by Region

CEE MED SA CA

1989 0.0 0.0 8.8 24.8

1990 0.0 0.0 13.4 26.6

46 Average

8.4

10.0

1991 0.0 0.0 20.8 26.6

1992 0.0 0.0 19.3 26.6

1993 8.3 0.0 19.3 26.6

1994 10.4 0.0 29.3 26.6

1995 14.4 0.0 39.3 26.6

1996 14.4 3.3 39.3 26.6

1997 14.4 3.3 39.3 30.7

1998 21.0 6.7 44.4 55.7

1999 34.9 6.7 44.4 55.8

2000 41.8 9.6 44.4 55.8

2001 45.3 10.3 44.4 59.2

12

11.5

13.5

16.6

20.1

20.9

21.9

31.9

35.4

37.9

39.8

Year of Initial Privatization of the Incum bent by Region 12 10 CEE

8

MED

6

SA

4

CA

2 2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

1989

0

Year of Initial Privatization of the Incum bent (All Countries)

40 30 20 10

39

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

0 1989

12 12 10 12

Panel 2. Separate Regulators Countries with separate regulators Number by regional group 1995 3 1 8 4

1996 3 1 8 9

1997 3 3 8 9

1998 6 4 8 9

1999 6 4 8 9

2000 9 6 8 9

2001 11 7 8 9

2

3

3

4

5

13

18

20

21

21

23

24

1998 50 33.3 66.7 75

1999 50 33.3 66.7 75

2000 75 50 66.7 75

2001 91.67 58.3 66.7 75

1990 0 0 8.3 8.3

1991 0 0 16.7 8.3

Average number of fixed lines by regional group 1992 1993 1994 1995 1996 1997 8.3 25 25 25 25 25 0 0 0 8.3 8.3 25 16.7 25 33.3 66.7 66.7 66.7 8.3 8.3 8.3 33.3 75 75

C o u n tr i e s w i th se p a r a te r e g u l a to r s (S h a r e i n th e r e g i o n a l g r o u p ) 100 90 80 70

MED

60 50 40

SA

30 20

CA

CE E

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

10 0

T ra n si ti o n a n d E m e r g i n g C o u n tr i e s w i th se p a ra te r e g u l a to rs (N u m b e r )

45 40 35 30 25 20 15 10 5

40

2001

2000

1999

1998

1997

1996

1995

1994

1993

0 1992

12 12 10 12

1994 3 0 4 1

1991

CEE MED SA CA

1989 0 0 0 8.3

1993 3 0 3 1

1991

1

1992 1 0 2 1

1990

Total

1991 0 0 2 1

1990

46

1990 0 0 1 1

1989

GROUP 1989 0 CEE 0 MED 0 SA 1 CA

1989

No. 12 12 10 12

Panel 3. Fixed lines and Teledensities by Region Average teledensity by regional group No. 12 12 10 12

GROUP CEE MED SA CA

46 Average

1989 1990 1991 1992 1993 1994 1995 14.83 15.53 16.39 17.51 18.69 20.30 22.11 13.09 13.66 14.36 15.14 15.92 16.75 17.73 5.95 6.32 6.72 7.37 8.03 8.79 9.59 6.44 6.98 7.41 7.80 8.30 8.98 9.59 10.08

10.62

11.22

11.96

12.73

1996 24.28 19.12 10.72 10.31

1997 26.38 20.27 12.02 11.60

1998 1999 2000 2001 28.26 29.70 30.73 30.52 21.48 22.34 23.05 23.23 12.96 13.64 14.53 15.33 12.36 13.09 13.93 14.48

13.70 14.76 16.11 17.57

18.77

19.69

20.56

20.89

Average number of fixed lines by regional group

1.10

1.19

1.30

1.43

1.57

1.74

1.91

1997 2.16 2.37 3.86 1.05

2.12

2.36

1998 1999 2000 2001 2.39 2.57 2.68 2.72 2.59 2.79 2.94 3.10 4.34 4.92 5.67 6.44 1.14 1.26 1.41 1.55 2.61

Average Teledensity by region 45 40 35 30

CEE

25

MED

20

SA

15

CA

10 5 2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

0

Average num ber of m ainlines by region (m illions) 6 5 CEE

4

MED

3

SA

2

CA

1

41

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

0 1991

Average

1989

46

1989 1990 1991 1992 1993 1994 1995 1996 1.12 1.18 1.25 1.34 1.44 1.59 1.75 1.95 0.98 1.10 1.26 1.42 1.61 1.79 1.96 2.15 1.78 1.90 2.03 2.23 2.42 2.70 2.99 3.42 0.53 0.59 0.65 0.72 0.81 0.90 0.95 0.98

1990

CEE MED SA CA

1989

12 12 10 12

2.88

3.17

3.45

Table 2. Dependent variable: Teledensity

β (SE)

Fixed Effects t

P>|t|

β (SE)

Random Effects t

OLS P>|t|

β (SE)

t

P>|t|

gdpuspc

0.002 (0.0001)

11.75

0.000

0.002 (0.0002)

13.00

0.000

0.003 (0.0001)

21.57

0.000

pop

0.044 (0.082) 0.275 (0.058) 0.094 (1.016) 1.277 (0.458) 0.0669 (0.046) -0.001 (0.0005) -.0097 (0.346) 0.0259 (0.0049) -0.00001

0.54

0.592

-1.39

0.166

0.000

0.000

4.46

0.000

-0.04

0.969

0.09

0.926

-0.05

0.957

-0.77

0.439

2.79

0.006

3.56

0.000

1.24

0.215

1.45

0.147

1.52

0.127

1.56

0.119

-2.07

0.039

-2.15

0.032

-2.48

0.013

-0.28

0.780

-0.31

0.753

-1.23

0.220

5.26

0.000

5.41

0.000

-0.070 (0.014) -0.0011 (0.029) -1.708 (2.203) 1.102 (.888) 0.146 (0.093) -0.002 (0.0009) -0.751 (0.611) 0.0236 (0.011)

-5.09

4.73

2.21

0.028

-2.01

0.0045

-2.16

0.031

-0.000001 (0.00001)

-0.11

0.913

-3.15

0.002

-0.0576 (0.041) 0.221 (0.0494) -0.539 (1.011) 1.56 (0.438) 0.069 (0.012) -0.0011 (0.0005) -0.107 (0.340) 0.027 (0.005) -0.00002 (-.000001) -6.679 (3.28)

-2.04

0.042

5.533 (1.676)

3.30

0.001

urbpop f_ypriv yseparreg f_fdishare f_fdishareSQ c_numcomp c_fdipen c_fdipenSQ

(0.000001)

cons

-11.446 (3.6289)

σu σe ρ F(46, 494) Prob>F

9.878 2.970 0.917 69.71 0.000

Hausman test χ2( 9) Prob>χ2 R2 Within Between Overall t = 1989-2000 i = 46

χ2(10) Prob>χ2

8.7880 2.9696 0.8975 732.46 0.000

12.89 0.23

0.58 0.37 0.39

0.58 0.49 0.50

42

0.58

Table 3. Dependent variable: Teledensity growth

β (SE) gdpuspc pop urbpop f_ypriv yseparreg f_fdishare f_fdishareSQ c_numcomp c_fdipen c_fdipenSQ cons

00025 (0.0004) 0.130235 (0.1867) 0.2521 (0.1317) 4.4156 (2.3045) -0.1169 (1.0392) -0.1482 (0.1046) 0.0020 (0.0012) -1.0384 (0.7859) 0.0033 (0.0112) -0.00001 (0.00002) -11.836 (8.23)

σu σe ρ F(10, 496) Prob>F

Fixed Effects t

P>|t|

β (SE)

0. 0.64

0.521

0.70

0.486

1.91

0.056

1.92

0.056

-0.11

0.910

-1.42

0.157

1.74

0.082

-1.32

0.187

0.30

0.767

-0.85

0.398

-0.0001 (0.0002) 0.03173 (0.0171) -0.0545 (0.0349) 2.0347 (1.996) 0.5463 (0.8173) -0.0730 (0.0853) 0.0009 (0.0008) -0.9111 (0.6063) 0.017 (0.0097) -0.00002

OLS P>|t|

β (SE)

t

P>|t|

-0.67

0.504

-1.27

0.204

1.85

0.064

2.87

0.004

-1.56

0.119

-2.66

0.008

1.02

0.308

0.68

0.495

0.67

0.504

-0.13

0.897

-0.86

0.392

-0.82

0.412

1.13

0.258

1.11

0.267

1.50

0.133

-1.71

0.087

1.75

0.080

2.58

0.010

-1.42

0.156

-0.0002 (0.0001) 0.0335 (0.011) -0.0657 (0.025) 1.2713 (1.862) -0.0969 (0.7506) -0.0649 (0.079) -0.0649 (0.079) -0.8860 (0.517) 0.02327 (0.009) -0.00003

-1.67

0.096

7.84

0.000

(0.00002)

-1.44

7.32 6.73 0.54 2.96 0.01

0.151

10.25393 (2.0344)

χ2(10) Prob>χ2

Hausman test χ2( 10) Prob>χ2 R2 Within Between Overall t = 1989-2000 i = 46

Random Effects t

(0.00002)

5.04

0.000

11.107 (1.417 )

2.36 6.73 0.11 20.88 0.02

20.61 0.02

0.04 0.005 0.0001

0.02 0.21 0.06

43

0.063

Table 4. Dependent variable: Teledensity/ staff Fixed Effects t

P>|t|

β (SE)

0.0008 (0.0001) -0.0933 (0.0338) 0.0789 (0.0238) 0.1166 (0.4172) 0.3394 (0.1881) 0.01801 (0.0189) -0.0001 (0.0002) 0.0036 (0.1422) -0.0047 (0.0020)

11.44

0.000

-2.76

0.001

3.31

0.006

0.28

0.780

1.80

0.072

0.95

0.342

-0.87

0.383

0.03

0.980

-2.34

0.020

0.000006 (0.000002)

2.22

0.027

-2.5745 1.4899

-1.73

0.085

0..0008 (0.0001) -0.0755 (0.0222) (0.0567) (0.0221) 0.1174 (0.4191) 0.3508 (0.1842) 0.0204 (0.0189) -0.0002 (0.0002) -0.0156 (0.1417) -0.0049 (0.002) 6.47e-06 2.94e-06 -1.569 (1.572)

β (SE) Gdpuspc Pop Urbpop f_ypriv Yseparreg f_fdishare f_fdishareSQ c_numcomp c_fdipen c_fdipenSQ cons σu σe ρ F(10,496) Prob>F

5.9469 1.2191 0.9596 22.79 0.0000

χ2(10) Prob>χ

Hausman test χ2( 9) Prob>χ2 R2 Within Between Overall t = 1989-2000 i = 46

Random Effects t

OLS P>|t|

β (SE)

t

P>|t|

12.14

0.000

17.99

0.000

-3.40

0.001

-6.56

0.000

2.57

0.010

-7.59

0.000

0.28

0.779

1.93

0.054

1.90

0.057

-2.62

0.009

1.08

0.281

1.06

0.290

-0.96

0.336

-0.67

0.506

-0.11

0.912

0.002 (0.00009) -0.055 (0.008) -0.134 (0.0176) 2.569 (1.3314) -1.407 (0.5367) 0.0599 (0.0565442 -0.0004 (0.0005) 1.2277 (0.369) -0.0291 (0.006) 0.000020 (0.00001) 7.724 (1.0129)

3.32

0.001

-4.51

0.000

1.72

0.085

7.63

0.000

-2.43 2.20

0.015 0.028

-1.00

0.318

5.321 1.219 0.950 22.79 0.0000

F(10, 541)

47.7

Prob>F

0.000

16.82 0.078

0.31 0.26 0.26

0.31 0.29 0.29

44

0.47

Table 5. Dependent variable: Fixed lines

gdpuspc pop urbpop f_ypriv yseparregul f_fdishare f_fdishareSQ c_numcomp c_fdipen c_fdipenSQ cons

β (SE) 50.64 (43.06) 586125 (20667) -3641 (14582) 915131 (255150) -387212 (115066.5) -34158 (11578) 365 (129) 175527 (87012) 2302 (1238) -2.007 (1.7887) -8318470 (911231)

σu σe ρ

Fixed Effects t

P>|t|

1.18

0.240

28.36

0.000

-0.25

0.803

3.59

0.000

-3.37

0.001

-2.95

0.003

2.83

0.005

2.02

0.044

1.86

0.064

-1.12

0.262

-9.13

0.000

β (SE) 73.43 (53.34) 155544 (9895) 15349 (14498) 1016176 (347612) 188253 (147667) -61193 (15508) 731 (169) 449986 (116294) 3417 (1692) -4.21 (2.464) -2678118 916411

13565815 745683 0.997

F(10,496) Prob>F

131.71 0.0000

OLS P>|t|

1.38

0.169

15.72

0.000

1.06

0.290

2.92

0.003

1.27

0.202

-3.95

0.000

4.31

0.000

3.87

0.000

2.02

0.043

-1.71

0.087

-2.92

0.003

β (SE) 112 (29.02) 101954 (2686) 6595 (5679) 178893 (429042) 167382 (172949) -24437 (18221) 196 (172) 292069 (119073) 6064 (2081) -5.96 (3.56) -1098591 (326407)

t

P>|t|

3.88

0.000

37.95

0.000

1.16

0.246

0.42

0.677

0.97

0.334

-1.34

0.180

1.14

0.254

2.45

0.014

2.91

0.004

-1.67

0.095

-3.37

0.001

1378838 745683 .77371 χ2(10) Prob>χ

Hausman test χ2(10) Prob>χ2 R2 Within Between Overall t = 1989-2000 i = 46

Random Effects t

519 0.0000

783.65 0.0000

0.73 0.82 0.73

0.52 0.82 0.75

45

0.77

Table 6. Dependent variable: Cellular teledensity Fixed Effects t

P>|t|

β (SE)

9.16

0.000

-0.36

0.719

-1.34

0.180

1.76

0.080

5.22

0.000

1.19

0.235

-4.81e-06 (0.00001)

-0.39

0.699

-2.134 (6.302)

-0.34

0.735

0.0013 (0.0001) -.0119 (0.013) -.0654 (0.027) 1.786 (0.6121) 3.763 (0.606) (0.0062 (0.0076) -1.33e-06 (0.00001) -3.200 (1.6)

β (SE) gdpuspc pop urbpop yseparreg c_numop c_fdipen c_fdipenSQ cons

0.0027 (0.0003) -0.0495 (0.137) -0.134 (0.100) 1.330 (0.757) 3.563 (0.683) 0.010 (0.009)

σu σe ρ F(7,499) Prob > F

5.17 5.16 0.50 52.51 0.0000

Wald χ2 (7)

Prob > χ2

Hausman test χ2( 9) Prob>χ2 R2 Within Between Overall t = 19892000 i = 46

Random Effects t

P>|t|

β (SE)

t

P>|t|

9.95

0.000

11.48

0.000

-0.92

0.360

-1.56

0.119

-2.47

0.014

-2.18

0.030

2.92

0.004

3.08

0.002

6.21

0.000

6.36

0.000

0.82

0.414

0.31

0.759

-0.11

0.911

0.06

0.950

-2.00

0.045

0.0011 (0.0001) -0.014 (0.0091) -0.04 (0.02) 1.768 (0.57) 3.536 (0.557) 0.002 (0.007) 7.40e-07 (0.00001) -3.5 (1.17)

-2.99

0.003

F( 7, 544) Prob > F

49.37 0.0000

1.71 5.16 0.1 343.72 0.0000

OLS

76.64 0.0000

0.42 0.54 0.34

0.40 0.53 0.39

46

0.39

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