Service-Quality in Brazilian Mobile Telephony:

an Efficiency-Frontier Analysis TD. 013/2004

Marcelo Resende

Henrique Cesar Tupper

STextos pa o

Universidade Federal do Rio de J a neiro Instituto de Economia

érie ra Discussã

Service-Quality in Brazilian Mobile Telephony: an Efficiency-Frontier Analysis*

Marcelo Resende

Instituto de Economia, Universidade Federal do Rio de Janeiro,

Av. Pasteur 250, Urca, 22290, Rio de Janeiro-RJ, Brazil

mresende@ie.ufrj.br

Henrique César Tupper

Av. Oswaldo Cruz 28/205, Flamengo, 22250-060, Rio de Janeiro-RJ, Brazil

hctupper@terra.com.br

Abstract

The mobile telephony sector is characterised by the dynamic interplay of rapid changes in

technology and an apparently growing competition as indicated by the fierce non-price

competition and yet associated with the entry of new operating companies in some cases. In

that context, a relevant and neglected issue is to assess how service-quality respond to an

increasingly competitive environment. This study utilises Data Envelopment Analysis (DEA) to

assess the quality-efficiency of mobile telephony companies in Brazil during the 2000-2003

period. Window analysis was conducted for the entire period, taking as reference different

quality indicators pertaining different forms of complaints and calls completed and interrupted.

The efficiency measurement was made feasible by interpreting the indicators reflecting a

positive dimension of quality as outputs ad those reflecting negative aspects of quality as inputs.

This adaptation allows to generate efficiency frontiers for service-quality in the mobile sector.

Given potential heterogeneities across firms that relate to the frequency band and to the

technology (TDMA, CDMA among others), the paper considered adjusted efficiency scores. The * The authors acknowledge conversations with Eduardo Tude, but the usual disclaimer applies.

Tobit model for censored data was estimated to control for the aforementioned aspects.

Rescaled residuals from the econometric estimation produced efficiency scores for service-

quality. The evidence indicated, an overall improvement of efficiency over time. Nonparametric

tests indicated that significant shifts in the frontier occurred over time even for shorter sub-

periods.

Key-words: service-quality, efficiency, mobile telephony

1. Introduction

The characterization of telecommunications in terms of a natural monopoly structure has

been increasingly challenged, especially in terms of long-distance telephony and most obviously

in the mobile segment. Moreover, it is important to stress that the newer technologies in mobile

telephony greatly increased the efficiency in the use of spectrum and therefore contributed to

the rapid expansion in mobile access [see Hausman (2002) and Gruber and Valletti (2003) for

overviews on the sector]. The fast diffusion of mobile telecommunications was generally

associated with a more competitive market structure in both developed and developing

countries as typically one observed an initially duopolistic structure that later evolved to broader

oligopolies.

It is worth mentioning that a typically light-handed regulation has been practiced in that

segment but important regulatory challenges remain, especially in terms of the establishment of

appropriate interconnection rules with fixed telephony operators. The apparently fierce

competition in mobile telephony and associated aspects need to be further assessed especially

in developing countries with a less mature regulatory environment.1 In particular, the quality

performance of mobile telephony operating companies – MTOC has been subject to limited

quantitative investigations, with exceptions provided by Ai and Sappington (2002), Banerjee

(2003) and Façanha and Resende (2004) for the U.S. local telephony, and Resende and

Façanha (2004) for the Brazilian telephony.2 The latter two papers contrast with the remaining

of literature by advancing the possibility of generating synthetic indicators for service-quality by

means of a adaptation of Data Envelopment Analysis-DEA in that context.

The present paper considers the possibility of service-quality assessment with efficiency

frontier methods in the context of Brazilian mobile telephony. Moreover, the possibility of

1 Even though some strengthening of competition appears to have occurred in the sector there is evidence that multimarket contact and cross-ownership are important in explaining noncompetitive prices as indicated by Parker and Roller (1997) 2 Overviews on quality in the context of regulation appear in Sappington (2003) and Façanha and Resende (2004)

fruitfully combining those methods with econometric estimation is addressed with the aim at

controlling for relevant technological heterogeneity between the different MTOCs.

The paper is organized as follows. The second section provides some basic background on

mobile telecommunications and discusses the essential institutional and regulatory features in

the Brazilian case. The third section discusses how DEA models as combined with econometric

analysis can provide a useful route for generating synthetic service-quality indicators. The fourth

section discusses the data construction procedures and presents the empirical results. The fifth

section brings some final comments.

2. Mobile Telephony in Brazil: Institutional and Regulatory Background

2.1- Mobile Telephony: a Brief Digression

The mobile telephony sector is characterised by the dynamic interplay of rapid changes in

technology and an apparently growing competition as indicated by the fierce non-price

competition and intense price promotions. Therefore, any overall characterisation of the sector

needs to portray the main technological and regulatory features of that segment.

The technical change in the mobile segment has been very intense and it is possible to

highlight three generations of mobile technology..

The first generation relied on analogue technology in terms of the AMPS (Advanced Mobile

Phone Service) system developed in the U.S.. An important advantage of that technology refers

to good spectrum efficiency properties and it initially became the most popular standard in

different national networks. In the AMPS system, the communication between a mobile terminal

and radio station base - RSB is implemented in 800MHz frequency range by means of analogue

signals in 30KHz channels.

The second generation of mobile telephony was marked by the initial introduction of digital

technologies; Among those, one should mention digital AMPS (DAMPS) that was introduced in

the U.S. to assure a smooth transition from an analogue to a digital system. The DAMPS

system is compatible with the analogue system and is based on the TDMA technology (Time

Division Multiple Access). This standard was developed to increase the capacity of the AMPS

system by means of a wider number of users sharing the 30 KHz channel. The use of digital

communication channels between the mobile terminal and the RSB allows that up to 3 users

share a same channel by using distinct time slots. The CDMA system (Code Division Multiple

Access) is an alternative digital system (not compatible with DAMPS). and it is a standard that

revolutionized communication between mobile terminals and RSB. Instead of splitting the

available band in channels that allow for reuse of frequencies, the CDMA system is able to

reach a larger capacity in a different approach. The number of users in each cell is limited by

the prevailing interference level that is managed by power control and other techniques. The

goal is to reduce interference in adjacent cells that utilise the same frequency band but different

dispersion codes.

In addition to the aforementioned standards, it is worth mentioning the European

technology GSM (Global System for Mobile Communication). GSM is currently the second

generations standard with the largest number of subscribers (more than 1 billion). This

technology was developed in Europe to replace different analogue standards used in the

European countries in terms of the 800 MHz and 450 MHz frequency bands. GSM uses 200

KHz channels in the 900 MHz band and later had developed an adapted version for the 1800

and 1900 MHz bands. Comparisons between the GSM and CDMA are difficult. Nevertheless,

the advantage of the former over the latter is significant [see e.g. Garg and Wilkers (1996) and

Webb (1998)].

The first and second generations of mobile telephony systems were designed mostly for

voice transmission. The next step was the development of systems that were more suited for

data transmission. Among the technologies in this generation, one should point out WCDMA

and CDMA 1xEV. These provide data transmission services at the speed of up to 2 Mbp/s.

The implementation of the previously mentioned technologies depend not only on

investments of the MTOCs, but also on authorisations established by the regulatory setup.

In the Brazilian case, technological heterogeneity is evident and therefore any efficiency

assessment needs to properly control for differences in frequency band and technology across

the various MTOCs. Next we present some basic information pertaining the Brazilian case.

2.2- Brazilian Mobile Telephony: Institutional and Regulatory Background

Mobile telephony in Brazil was initiated in 1991 with the implementation analogue AMPS in

terms of the so-called band A. 3 . In July 1997, the regulatory agency [Agência Nacional de

Telecomunicações – ANATEL] was created by means of the General Telecommunications Law

no. 9.472. The corresponding institutional design following the privatization process in 1997

initially established a duopolistic structure in terms of 10 regions. The technology adoption

process in the Brazilian mobile sector has been heterogeneous. In fact, since the beginning of

the privatization process, one observed a growing adoption of digital technology involving the

mixed prevalence of CDMA and TDMA technologies with reduced importance to analogue

technology (AMPS). These technology differences may determine important efficiency

differentials that must be acknowledged. In Brazil the spectrum is currently divided in 4

frequency bands and an extension subrange as indicated in table 1 in appendix 4

The initial configuration of the Brazilian mobile segment known as Mobile Cellular Service

(Serviço Móvel Celular-SMC), established the division of the national territory into 10 operation

areas in terms of a duopolistic structure, as summarized the next table 2 in appendix.

The MTOCs in the SMC, that initially were all at band A,, were separated from the fixed

telephony companies and then privatised. Procurement bids were also made for operation in

band B and in the majority of the cases the operations started in 1998. The concession

contracts were established for a 15 years period for MTOCs in bands A and B.

Initially, the technology utilized among the operators in band B was the TDMA system, with

the exception of Global Telecom in area 5. The privatized operating companies in band A

shifted to CDMA in areas 1, 2, 3 and 9 and to the TDMA in all other regions. More precisely,

3 The exception was the state of Rio de Janeiro that used the B band but in 1997 was to migrate to band A.. 4 A fifth band (band C) was predicted but no interested operators presented bids. That band is defined in terms of the 1725-1740 MHz range for mobile terminal and 1820-1835 MHz for ERB

one observed dual technologies for mobile terminals (AMPS/TDMA or AMPS/CDMA) in order to

guarantee roaming between the different areas.5.

It is worth mentioning that the quality standards are defined in terms of the Commitment

Protocol agreed with the regulator ANATEL. That legal instrument established a set of 9 quality

indicators to be informed in a monthly basis. The referred indicators constitute the data base

used in this study.

ANATEL decided in 2001 to review the institutional design of mobile telephony in Brazil.

For that purpose it created new rules by means of the so-called Personal Mobile Service

(Serviço Móvel Pessoal-SMP)..

Among the main changes introduced by the SMP in comparison to the SMC one should

mention the change in operation areas.

The quality commitments under the SMP are similar to those established for fixed

telephony as one needs to comply with service-quality targets defined by General Plan for

Quality Targets (Plano Geral de Metas de Qualidade-PGMQ-SMP), defined by ANATEL, All

companies in the SMP are subject to this monitoring procedure and in principle could imply in

fine charges in case of deficient performance. PGMO-SMP encompasses 16 quality indicators

that are informed in a monthly basis since September 2003. The empirical exercise undertaken

in section 4 considers the quality indicators for the SMC system. In fact, the introduction of the

new set of indicators is very recent so that it can be premature to advance a clear service-

quality assessment.

3. Data Envelopment Analysis: Some Conceptual Aspects

The generation of relative efficiency scores by means of Data Envelopment Analysis has

encountered a wide range of applications [see e.g. Copper et al (1994) for a list]. Applications in

the context of telecommunications include, for example, Majumdar (1995), Resende (2000). and 5 The protocol IS-41 guaranteed ‘roaming” between the areas covered by different concessionaries in mobile telephony under TDMA and AMPS technologies. In Brazil all operating companies in band A keep AMPS channels in the totality of its coverage area so as guarantee national “roaming” for all subscribers.

Resende and Façanha (2002). The present paper intends to advance the use of DEA efficiency

scores in the context of service-quality assessment in mobile telecommunications in Brazil. This

possibility was initially advanced by Resende and Façanha (2004) for fixed telephony in the

U.S. and also applied by Façanha and Resende (2004) to the Brazilian fixed telephony.

The application that is undertaken here will consider a windows analysis procedure within a

standard DEA framework. The simpler DEA model advanced by Charnes, Cooper and Rhodes-

CCR (1978) can be described in terms of n decision making units-DMUs (j = 1,…, n), m inputs

and s outputs and can be expressed as the usual dual formulation indicated below for a

selected DMU0 (in the input orientation version of the problem).6

)1(min θ

subject to

)2(0 jtj jtt XX λθ ∑≥

)3(0 jtj jtt YY λ∑≤

)4(0≥jtλ

The time subscript t readily generalises the DEA model in terms of windows analysis. In

that case, each DMU is not only compared with the others but also with itself in different

periods. In the general case, of T periods, one can consider at most T- p + 1 windows for a

given p, where p denotes the window width. In the present application, we consider p = T = 14

and therefore a unique window. The motivation for that procedure is the short time period

involved.7

The adaptation of DEA efficiency frontiers to quality assessment and its fruitful combination

with econometric analysis can be summarised in terms of a three-steps procedure:

6 See Cooper et al (2000) and Thanassoulis (2001) for introductions to DEA methods.

7 There is a growing interest in the application of windows analysis. See for example Asmild et al (2004)

a) Consider quality indicators that positively contribute to overall quality as outputs and

variables that negatively contribute to quality as inputs. Please note that this interpretation does

not require any direct transformation of the inputs into outputs. This approach was advanced by

Resende and Façanha (2004) and Façanha and Resende (2004) in the context of fixed

telephony in the U.S. and Brazil respectively. A generic motivation for interpreting “positive”

factors as outputs and “negative” factors as inputs was also provided in Retzlaff-Roberts (1997);

b) Control for heterogeneities by means of a Tobit regression model that explicitly handles

censoring at 1. In our particular application, we control for heterogeneities related to the

frequency band and the type of technology. The combination of DEA with the estimation a Tobit

model in terms of a two-steps procedure has been considered before by Dusansky and Wilson

(1994), Pollitt.(1996) and Resende (2000) among others;

c) Introduce a third-step where one considers rescaled residuals from the Tobit estimation

as adjusted efficiency scores. The rescaling of the residuals was inspired by Greene (1980) and

suggested by Gasparini and Ramos (2003). Tupper and Resende (2004) recently adopted that

approach. Specifically, the adjusted DEA efficiency scores are rescaled to belong to the [0,1]

interval so that for each DMU i.8 The present paper applies that three-

step procedures for mobile telephony in Brazil. The results are presented in the next section.

)max1( iiiADJ

i εεθ −+=

4. Empirical Analysis

4.1- Data Sources

The main data source was the Brazilian regulatory agency in telecommunications [Agência

Nacional de Telecomunicações-ANATEL] that collected nine quality indicators in a monthly

basis during the period February 2000-May 2003. Due to data availability, we considered

quarterly data starting in February, May, August and November. Since there were reporting

8 Tupper and Resende (2004) also considered these adjusted DEA efficiency scores to devise a yardstick scheme that rewarded units that were relatively more efficient in Brazilian water and sewarage utilities. In principle, one could conceive some yardstick scheme to reward quality performance in telecommunications. However, one has to bear in mind that mobile telephony is essentially deregulated.

inconsistencies, we considered 8 of those that are listed below with the corresponding

assignment as “inputs” or “outputs” as explained in the previous section. Specifically:

Inputs

. COMP: complaints rate (%),

. . . COV: the coverage/congestion per 1000 lines

. COMPB: the complaints on bills per 1000 issued bills

. CINT: call interruption (%);

outputs:

. CONT: contacts handled within 5 days (%),

. CUSTS: customers serviced in 10 minutes;

. CCALL: completed calls (%);

. CEST: call establishment (%).

Table 3 presents the summary statistics for the previous variables and indicates a high

level of heterogeneity across firms. The appendix presents the list of companies in our sample.

It is important to emphasize that service-quality assessments in mobile telephony seem to

be absent in the literature. An exception is provided by Resende (2003) that considered

aggregate indicators for Brazilian mobile telephony according to the different operation areas. In

this work, on the other hand, we construct a firm-level synthetic quality indicator.

4.2. Empirical Results

The empirical analysis followed the three-steps procedure outlined in a previous section.

Once the quality-efficiency scores are obtained it is important to control for additional factors

that may affect quality-efficiency so as to obtain proper adjusted efficiency scores. For that

purpose a Tobit model that accommodates censoring at 1 was estimated. The model

considered the transmission frequency-band and type of technology (AMPS, TDMA and CDMA

in isolated or combined form) to construct explanatory variables for the quality-efficiency scores.

In fact, a higher frequency and less sophisticated digital or analogue technologies are

associated with higher costs. In particular, as previously mentioned, band A, the hybrid

networks comprising analogue AMPS and digital (TDMA or CDMA) technologies will have

mixed effects on costs. In one hand lower frequencies are associated with broader coverage but

on the other hand the obligations of MTOCs in band A to keep to some extent analogue is less

cost effective.9

In contrast, operators within band B have costs disadvantages associated with lower

coverage in high frequencies, but had advantages related to the exclusive use of digital

technology (TDMA or CDMA).

It is worth mentioning that different frequency bands and technology configurations can

have important direct or indirect impacts on service-quality given the aforementioned remarks

on cost impacts. In that sense it is in principle important to control for those kinds of

heterogeneity.

Given the previous reasoning, the raw quality efficiency scores were corrected by

considering an auxiliary econometric estimation that aimed at controlling for frequency band and

technology. For that purpose, we explicitly accounted for censoring at 1 by using a Tobit model.

The control variables were defined as follows:

. BANDB: dummy variable that assumes value 1 for companies operating in band B and 0

otherwise (for band A);

. ATDMA: dummy variable that assumes value 1 for companies operating in hybrid

networks comprising AMPS and TDMA technologies and 0 otherwise; (AMPS and CDMA);

. CDMA: dummy variable that assumes value 1 for companies operating with exclusive use

of CDMA technology. and 0 otherwise (TDMA);

The related results appear in table 4 in appendix.

Even though the overall adjustment seems to be moderate, the controls for frequency band

and technology are, as a rule, highly significant and important contrasts between the raw and

the adjusted quality efficiency scores were observed. In fact, the rescaled residuals obtained

from the Tobit model estimation allowed to generate adjusted quality-efficiency scores that can

9 The intention of the regulator was to secure roaming in the different regions.

be interpreted as proper efficiency scores. These adjusted scores can portray a more adequate

picture of the evolution of service-quality in Brazilian mobile telecommunications. The results

are summarised in table 5 and table 6 in appendix, on the other hand, shows the results for

Wilcoxon signed-rank test

Some suggestive patterns emerge from the inspection of the previous tables:

a) There is a substantial number of underperforming firms, indicating that one should be

concerned with service-quality in the mobile segment;

b) For the majority of MTOCs one can observe a general improvement of the quality

efficiency scores towards the end of the sample period, though that trend is not always

monotonic. In fact, for some companies one observe some deterioration of quality around

2003.;

c) Nonparametric tests were conducted by means of comparisons between Feb. 2000/Nov.

2001, Nov. 2001/May 2003 and yet Feb. 2000/May 2003. In all cases, the rejection of the null

hypothesis is strong and therefore indicates that important shifts in the overall quality-efficiency

have occurred.

The study seems to indicate that after controlling for technological heterogeneity, one can

detect improvements in service-quality over time. It appears that the competitive pressures

exerted in the firms within the mobile segment have produced some positive effects.

5. Final Comments

The paper intended to construct synthetic service-quality efficiency scores for the mobile

telephony in Brazil.. The possibility of re-interpreting quality indicators as inputs or outputs was

previously considered by Resende and Façanha (2004) and Façanha and Resende (2004) in

the context of fixed telephony. In the present application, we combined DEA methods with

econometric estimation so as to control for heterogeneities related to the frequency band and

technology under which the different companies operate. The referred procedures allowed to

obtain adjusted scores that indicated a general improvement of service quality during the

sample period. Even though the improvements were not monotonic for all the companies, it

appears that overall service-quality improved over time.

Possible directions for future research include an attempt to uncover the catch-up and pure

frontier shifts that compose the observed quality changes. This extension could be implemented

in terms of Malmquist indexes, but this would more desirable in the future when the time-span of

sample increases.

Finally, this kind of exercise might have practical relevance, as the regulator could

potentially devise a yardstick scheme that rewards units that show better quality performance.

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Table 1: Mobile Telephony Spectrum in Brazil

.

Transmission Freqüency (MHz) Móbile Station RSB

Band A 824-835 845-846.5

869-880 890-891.5

Band B 835-845 846.5-849

880-890 891.5-894

Band D 1710-1725 1805-1820 Band E 1740-1755 1835-1850 Extension

subranges 1775-1785 1870-1880

Source:: Authors´ elaboration upon Souza and Tude (2003)

Table 2: Mobile Cellular Service in Brazil – Operation Areas

Area State Coverage 1 São Paulo – metropolitan area 2 São Paulo

3 Rio de Janeiro Espírito Santo

4 Minas Gerais

5 Paraná Santa Catarina

6 Rio Grande do Sul

7 Acre, Goiás, Mato Grosso, Mato Grosso do Sul, Rondônia, Tocantins

8 Amapá, Amazonas, Maranhão, Pará, Roraima

9 Bahia, Sergipe

10 Alagoas, Ceará, Paraíba, Pernambuco, Piauí, Rio Grande do Norte

Source: ANATEL

Table 3: Service-Quality Indicators for Brazilian Mobile Telephony-Summary Statistics

Minimum Maximum Mean Std. deviation

COMP 0.08 10.21 1.58 1.34 COV 0.00 21.01 1.25 2.42 COMPB 0.11 47.93 5.11 4.34 CINT 0.18 6.08 1.47 0.58 CONT 53.57 100.00 98.84 3.76 CUSTS 0.00 100.00 86.19 14.70 CCALL 22.65 69.11 57.82 5.11 CEST 56.90 99.95 95.63 2.63

Table 4: Adjusted Quality Efficiency Scores-Brazilian Mobile Telephony

Company Feb/00 May/00 Aug/00 Nov/00 Feb/01 May/01 Aug/01 Nov/01 Feb/02 May/02 Nov/02 May/02 Feb/03 May/03

Ama 0.200 0.290 0.250 0.390 0.290 0.480 0.540 0.790 0.740 0.870 0.850 0.790 0.690 0.580

Ama 2 0.200 0.270 0.310 0.330 0.340 0.400 0.500 0.640 0.610 0.800 0.830 0.900 0.810 0.540

Ama 3 0.230 0.190 0.200 0.360 0.410 0.610 0.650 0.760 0.650 0.870 0.890 0.830 0.690 0.540

Ama 4 0.180 0.260 0.130 0.270 0.480 0.440 0.610 1.000 0.650 0.900 0.850 1.000 0.760 0.680

Ama 5 0.260 0.430 0.390 0.660 0.510 0.520 0.710 0.800 0.620 0.700 0.870 0.830 0.960 0.700

Americel 0.264 0.314 0.314 0.294 0.284 0.214 0.704 0.484 0.364 0.294 0.334 0.374 0.434 0.384

ATL 0.204 0.344 0.574 0.364 0.474 0.414 0.314 0.294 0.364 0.294 0.334 0.374 0.684 0.644

BCP 0.474 0.694 0.614 0.604 0.384 0.504 0.474 0.694 0.594 0.664 0.834 0.544 0.374 0.474

BSE 0.604 0.664 0.544 0.634 0.744 0.694 0.564 0.584 0.554 0.554 0.484 0.474 0.514 0.904

Celular CRT 0.220 0.400 0.350 0.450 0.470 0.530 0.600 0.520 0.510 0.500 0.580 0.640 0.640 0.520

Global Telecom 0.312 0.392 0.432 0.352 0.342 0.462 0.542 0.482 0.612 0.752 0.772 0.892 0.872 0.632

Maxitel 0.254 0.304 0.524 0.434 0.504 0.354 0.314 0.464 0.564 0.594 0.644 0.604 0.594 0.634

Maxitel 2 0.254 0.384 0.244 0.424 0.304 0.244 0.174 0.324 0.614 0.734 0.764 0.554 0.524 0.534

Norte Brasil 0.344 0.484 0.614 0.974 0.974 0.974 0.594 0.564 0.684 0.974 0.894 0.934 0.974 0.974

Sercomtel 0.380 0.230 0.570 0.820 0.830 0.920 0.760 0.770 0.880 0.730 0.650 0.670 0.790 0.730

Telasa 0.550 0.810 0.410 0.440 0.270 0.330 0.330 0.430 0.400 0.510 0.620 0.590 0.600 0.550

Tele Centroeste 0.450 0.410 0.610 0.480 0.560 0.420 0.500 0.400 0.500 0.670 0.620 0.680 0.730 0.750

Teleacre 0.330 0.210 0.380 0.630 0.790 0.630 0.510 0.570 0.510 0.640 0.760 1.000 0.920 1.000

Telebahia 0.446 0.416 0.466 0.506 0.506 0.546 0.566 0.566 0.546 0.486 0.516 0.586 0.616 0.546

Teleceará 0.330 0.330 0.330 0.380 0.360 0.370 0.360 0.370 0.380 0.440 0.550 0.530 0.520 0.430

Telegoiás 0.350 0.180 0.220 0.250 0.930 0.340 0.500 0.490 0.540 0.880 0.740 0.680 0.840 0.860

Telemat 0.380 0.180 0.370 0.320 0.330 0.410 0.290 0.430 0.530 0.730 0.410 0.540 0.730 0.710

Telemig 0.230 0.300 0.360 0.350 0.460 0.490 0.440 0.480 0.520 0.550 0.640 0.670 0.740 0.670

TeleMs 0.380 0.140 0.280 0.600 0.580 0.630 0.610 0.580 0.690 0.620 0.650 0.620 0.750 0.650

Telepisa 0.360 0.350 0.380 0.420 0.370 0.390 0.340 0.420 0.450 0.610 0.640 0.760 0.700 0.480

Telergipe 0.386 0.406 0.426 0.526 0.556 0.536 0.626 0.626 0.636 0.486 0.566 0.636 0.616 0.586

Telerj 0.366 0.386 0.396 0.426 0.386 0.406 0.486 0.476 0.506 0.546 0.566 0.566 0.626 0.606

Telern 0.680 0.310 0.340 0.390 0.330 0.360 0.340 0.400 0.470 0.450 0.510 0.500 0.530 0.490

Teleron 0.280 0.210 0.310 1.000 0.910 0.720 0.830 1.000 1.000 1.000 1.000 0.560 1.000 1.000

Telesp 0.566 0.616 0.646 0.736 0.656 0.546 0.536 0.526 0.606 0.656 0.706 0.756 0.706 0.696

Telest 0.396 0.476 0.496 0.516 0.576 0.526 0.596 0.596 0.636 0.726 0.666 0.766 0.896 0.736

Telet 0.654 0.824 0.974 0.764 0.694 0.714 0.824 0.884 0.874 0.904 0.874 0.974 0.924 0.974

Telpa 0.520 0.840 0.440 0.420 0.280 0.390 0.320 0.410 0.490 0.520 0.590 0.620 0.450 0.490

Telpe 0.420 0.800 0.350 0.380 0.270 0.290 0.260 0.320 0.340 0.430 0.440 0.510 0.470 0.440

Tess 0.394 0.574 0.974 0.974 0.344 0.334 0.394 0.414 0.334 0.424 0.374 0.414 0.544 0.574

TIM SUL 2 0.220 0.300 0.360 0.500 0.530 0.460 0.870 0.690 0.760 0.660 0.730 0.710 0.660 0.690

TIM SUL 3 0.360 0.380 0.440 0.730 0.490 0.980 1.000 0.870 1.000 1.000 0.890 1.000 1.000 0.700TIM SUL 4 0.190 0.190 0.260 0.420 0.460 0.510 0.530 0.700 0.790 0.640 0.910 0.740 0.870 0.890Triang Cel(CTBC) 0.260 0.310 0.410 1.000 1.000 0.400 0.850 0.730 0.800 0.660 0.660 0.550 0.760 0.760

Table 5: Tobit model estimates (dependent variable: CCR efficiency

score)

Coefficient Std. error

p-value

Constant 0.354 0.026 0.000 BANDB 0.234 0.022 0.000 ATDMA 0.207 0.028 0.000 CDMA -0.109 0.061 0.074 Adjusted R2 = 0.098 No. of observations:

546

Table 6: Wilcoxon Nonparametric Tests for Shifts on the Quality

Efficiency Frontier

Periods Compared Feb00/Nov01 Nov01/May03 Feb00/May03

Test Statistic

- 4.438 -2.467 -5.138

p-value 0.000 0.013 0.000 Note: exact p-values were considered

Appendix: List of Operating Companies in SMC Companies S

MC A

rea

Band

Technology State

Amazônia Celular – Roraima (AMA 1)

8 A AMPS/TDMA RR

Amazônia Celular – AM (AMA 2)

8 A AMPS/TDMA AM

Amazônia Celular – PA (AMA 3)

8 A AMPS/TDMA PA

Amazônia Celular – AP (AMA 4)

8 A AMPS/TDMA AP

Amazônia Celular – MA (AMA 5)

8 A AMPS/TDMA MA

Americel 7 B TDMA AC/RO/MT/MS/GO/TO/

DF ATL 3 B TDMA ES/RJ BCP 1 B TDMA SP

(partial) BSE 1

0 B TDMA CE/PE/R

N/PI/AL/PB Celular CRT 6 A AMPS/TDMA/C

DMA RS

(partial) Global Telecom 5 B CDMA PR/SC Maxitel – MG (Maxitel 1) 4 B TDMA MG Maxitel – BA/SE (Maxitel 2) 9 B TDMA BA/SE Norte Brasil 8 B TDMA AM/RR/P

A/AP/MA Sercomtel 5 A AMPS/TDMA PR

(partial) Telasa 1

0 A AMPS/TDMA AL

Tele Centroeste 7 A AMPS/TDMA/CDMA

DF

Teleacre 7 A AMPS/TDMA/CDMA

AC

Telebahia 9 A AMPS/CDMA BA Teleceará 1

0 A AMPS/TDMA CE

Telegoiás 7 A AMPS/TDMA/CDMA

GOIÁS (partial)/TO

Telemat 7 A AMPS/TDMA/CDMA

MT

Telemig 4 A AMPS/TDMA MG (partial)

TeleMs 7 A AMPS/TDMA/CDMA

MS (partial)

Telepisa 10

A AMPS/TDMA PI

Telergipe 9 A AMPS/CDMA SE Telerj 3 A AMPS/CDMA RJ Telern 1

0 A AMPS/TDMA RN

Teleron 7 A AMPS/TDMA/CDMA

RO

Telesp 1, 2

A AMPS/CDMA SP (partial)

Telest 3 A AMPS/CDMA ES Telet 6 B TDMA RS Telpa 1

0 A AMPS/TDMA PA

Telpe 10

A AMPS/TDMA PE

Tess 2 B TDMA SP (partial)

TIM – Telepar (TIM Sul 1) 5 A AMPS/TDMA PR (partial )

TIM – CTMR (TIM Sul 2) 6 A AMPS/TDMA RS (partial )

TIM – Telesc (TIM Sul 3) 5 A AMPS/TDMA SC Triângulo Celular – CTBC 2

, 4, 7A AMPS/TDMA Partially

in MG, SP, GO, MS