Broadband Economic Impact in Brazil: a Simultaneous Equations

Hildebrando Rodrigues Macedo,

Broadband Economic Impact in Brazil: Broadband Economic Impact in Brazil: a Simultaneous Equations Analysisa Simultaneous Equations Analysis

Broadband Economic Impact in Brazil: a

Simultaneous Equations AnalysisHildebrando R. Macedo and Alexandre X. Y. Carvalho 5th ACORN-REDECOM Conference Lima,Peru, May 19-20th, 2010 1

Hildebrando Rodrigues Macedo,

Anatel, Anatel, BrazilBrazil

Alexandre Xavier Ywata de Carvalho, PhD

IPEA, IPEA, BrazilBrazil

19 November 201119 November 2011

AgendaAgenda

•• Introduction , Motivation and Introduction , Motivation and ObjectivesObjectivesObjectivesObjectives

•• ReferencesReferences•• Methodology: ModelMethodology: Model•• Results and AnalysisResults and Analysis•• Conclusion and CommentsConclusion and Comments



•• Conclusion and CommentsConclusion and Comments

•• Main Objective: Main Objective: Evaluate the broadband Evaluate the broadband economic impact in Brazil using official economic impact in Brazil using official statistics data from statistics data from AnatelAnatel (the Brazilian (the Brazilian

Main Objective and Results Main Objective and Results

statistics data from statistics data from AnatelAnatel (the Brazilian (the Brazilian telecom regulatory agency)telecom regulatory agency)••Main result:Main result:••11p.p.p.p. (percentage point) (percentage point) increase in increase in

broadband penetration related to GDP broadband penetration related to GDP



broadband penetration related to GDP broadband penetration related to GDP growth between growth between 0.038 to 0.18p.p.0.038 to 0.18p.p., and , and GDP per capita growth between GDP per capita growth between 0.196 0.196 to 0.362p.p.to 0.362p.p...

•• Too high economic impact found.Too high economic impact found.•• Data used are Data used are “problematic”“problematic”•• The The lack of reliable data lack of reliable data for some of for some of

Limitations of the StudyLimitations of the Study

•• The The lack of reliable data lack of reliable data for some of for some of the variables and the need to the variables and the need to estimate the missing dataestimate the missing data brings brings additional imprecision to the results, additional imprecision to the results,



additional imprecision to the results, additional imprecision to the results, which must be interpreted in a more which must be interpreted in a more cautiouscautious way.way.

Broadband Price EstimationBroadband Price Estimation•• Model based on results Model based on results of of CETICCETIC survey on survey on maximum declared maximum declared priceprice

for for internet adoptioninternet adoption. . Broadband price-demand sensitivity - 2008

70

80

Per

centa

ge

of hom

es w

her

e use

rs w

ere

willing to

Demand curve x Price estimated by regression

Demand x Price (survey data)

30

40

50

60

Per

centa

ge

of hom

es w

her

e use

rs w

ere

willing to

Subsc

ribe

the

inte

rnet

acc

ess se

rvic

e (%

)

Demand x Price (survey data)

y = 90.62617.e--0.018205.x

R2 = 0.992638



0

10

20

0 50 100 150 200 250 300 Maximum declared value declared by user (home) willing to subscribe

to the internet access service (R$).

Per

centa

ge

of hom

es w

her

e use

rs w

ere

willing to

Subsc

ribe

the

inte

rnet

238513.00

14.80

14

16

2500

3000

Num

ber o

f B

roadband A

ccess

es

Num

ber o

f B

roadband P

rovid

ers

Evolution of the Number of Broadband Accesses

and Providers

Number of Broadband Providers

Broadband in Brazil: OverviewBroadband in Brazil: Overview

562

815

1208

1802

2385

4.39

5.92

8.71

11.40

13.00

4

6

8

10

12

1000

1500

2000

2500

Num

ber o

f B

roadband A

ccess

es

(Millions)

Num

ber o

f B

roadband P

rovid

ers

Number of Broadband Providers

Number of Broadband Accesses



66 195298

414

562

0.12 0.36 0.590.97

3.16

4.39

0

2

4

0

500

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Num

ber o

f B

roadband A

ccess

es

Num

ber o

f B

roadband P

rovid

ers

YearSource: (ANATEL-SICI).

Broadband Penetration Worldwide(2008)Broadband Penetration Worldwide(2008)

CountryCountryBroadband Penetration Broadband Penetration

(number(number of accesses of accesses per 100 inhabitantsper 100 inhabitants))

RegionRegion

Broadband Penetration Broadband Penetration in the Region (numberin the Region (numberof accesses per 100 of accesses per 100

inhabitantsinhabitants))ArgentinaArgentina 7.97.9

BrazilBrazil 5.915.91 Latin Latin AmericaAmerica

5.55.5BrazilBrazil 5.915.91

ChileChile 8.48.4ColombiaColombia 4.24.2

Mexico Mexico 7.17.1CanadaCanada 29.029.0 NorthNorth

AmericaAmerica27.827.8USAUSA 26.726.7

SpainSpain 20.820.8FranceFrance 28.028.0



EuropeEurope 24.824.8FranceFrance 28.028.0

PortugalPortugal 16.016.0United KingdomUnited Kingdom 28.528.5

AustraliaAustralia 25.425.4Asia and Asia and OceaniaOceania

14.014.0South KoreaSouth Korea 32.032.0MalaysiaMalaysia 4.64.6

South AfricaSouth Africa 0.80.8AfricaAfrica 1.61.6MoroccoMorocco 1.51.5

Broadband Broadband

Accesses per Accesses per

1000 Inhabitants 1000 Inhabitants

For each For each

Municipality Municipality

((2008)2008)< 1



Source: Elaborated by the

authors from Anatel – SICI data

>=100

Backhaul Backhaul

Infrastructure Infrastructure

(2007) (2007)

Backhaul to Backhaul to

be Deployedbe Deployed



Existing BackhaulExisting Backhaul

Source: PNBL – Plano Nacional de Banda Larga (National

Broadband Plan, p. 40)

58.41

50

60

70

Per

cen

tage

(%)

Percentage of broadband accesses according to the population of the municipalities

Percentage of inhabitants according to the size of the municipalities population

Distribution of the broadband accesses according to the range of population of the municipalities (4th Quarter 2008).

Distribution of the country´s of inhabitants living in cities according to its size of population.

10.49 11.837.01 8.2

15.93

7.12 7.29 5.59 9.89 14.89

29.16

10

20

30

40

50

Per

cen

tage

(%)

(%)



2.24 2.39 1.91 2.19 1.72

7.01 8.2 7.12 7.29 5.59

3.71

0

10

Up to 10000

inhab.

From 10000

To 20000

Inhhab.

From 20000

to 30000

inhab.

From 30000

To 40000

inhab.

From 40000

to 50000

inhab.

From 50000

to 100000

inhab.

From 100000

to 200000

inhab.

From 20000

to 500000

inhab.

>500000 inhab.

Range of population of the municipalities

Source: Elaborated by the authors from Anatel and IBGE data.

58.41

45.97 50

60

70

Perc

enta

ge

(%)

Percentage of broadband accesses according to the population of the municipalities

Percentage of municipalities by size of its population

Distribution of the broadband accesses according to the range of population of the municipalities (4th Quarter 2008).

Distribution of the percentage of municipalities according to the range of its population.

24.89

10.24 15.93

8.27.01

45.97

10

20

30

40

Perc

enta

ge

(%)

(%)



2.24 2.39 1.91 2.19 1.72

5.73 5.552.84 2.46 1.65 0.66

7.01

0

10

Up to 10000

inhab.

From 10000 to 2000

inhab.

From 20000

To 30000

inhab.

From 30000

to 40000

inhab.

From 40000

to 50000

inhab.

From 50000

to 100000

inhab.

From 100000

to 200000

inhab.

From 20000

to 500000

inhab.

>500000

inhab.

Range of population of the municipalities

Fonte: Elaborado a partir de dados de (ANATEL-SICI) e IBGE

••KoutroumpisKoutroumpis (2009)(2009)••Broadband economic impact on Broadband economic impact on 22 22

OECD countries OECD countries from 2002 to 2007.from 2002 to 2007.••Used Used supplysupply and and demanddemand

simultaneous equations simultaneous equations system system

Main Reference Main Reference

simultaneous equations simultaneous equations system system with endogenous variables to with endogenous variables to capture acapture a simultaneous effectsimultaneous effect::•• Investments in telecom Investments in telecom lead to lead to

economic growth , economic growth , at the same at the same time time economic growth economic growth demands demands



time time economic growth economic growth demands demands telecom investment. telecom investment. ••Result: approx. Result: approx. 0,025p.p0,025p.p. de . de GDPGDP

increaseincrease for each for each 1p.p. 1p.p. broadband broadband penetration increasepenetration increase (p. 478)(p. 478)

•• KOUTROUMPISKOUTROUMPIS, , PantelisPantelis, , ““The Economic Impact of The Economic Impact of Broadband on Growth: A Broadband on Growth: A Simultaneous ApproachSimultaneous Approach”, ”, Telecommunications Policy Telecommunications Policy , num. , num.

33, pp.47133, pp.471––485, Elsevier, Oct.485, Elsevier, Oct. 20092009

(Koutroumpis,2009) (Koutroumpis,2009) Reference ModelReference Model•• Uses Uses 44 simultaneous equations: simultaneous equations: •• Aggregated Production Function Aggregated Production Function –– GDP.GDP.lnln((GDPGDPtt) = ) = ββββββββP0P0 + + ββββββββP1P1.ln(K.ln(K t t )+)+ββββββββP2P2.ln(LF.ln(LF tt) + ) + ββββββββP3P3.ln(.ln(PENPENtt) + ) + εεεεεεεεPPtt P0P0 P1P1 t t P2P2 tt P3P3 tt PP

•• Demand for Broadband Infrastructure.Demand for Broadband Infrastructure.lnln((PENPENtt)=)=ββββββββDD00 ++ββββββββDD11.ln(GDP.ln(GDP__PERPER__CAPITACAPITA t t ) + ) + ββββββββDD22.(.(BBBB__PRICEPRICEtt) )

+ + ββββββββDD33.(.(EDUEDUtt) +) +ββββββββD4D4.(.(URBURBtt) + ) + ββββββββD5D5.(.(R&DR&Dtt) + ) + εεεεεεεεDD

•• Supply of Broadband Infrastructure.Supply of Broadband Infrastructure.lnln((BBIBBI ) =) =ββββββββ ++ββββββββ .ln(BB.ln(BB PRICEPRICE ) + ) + ββββββββ .ln(.ln(REGULATIONREGULATION ) + ) +



lnln((BBIBBItt) =) =ββββββββOO00 ++ββββββββOO11.ln(BB.ln(BB__PRICEPRICE t t ) + ) + ββββββββOO33.ln(.ln(REGULATIONREGULATIONtt) + ) +

+ + ββββββββOO22.ln(COMPETITION.ln(COMPETITION__TECHTECH tt) + + ) + + εεεεεεεεOO

•• Broadband Infrastructure Production FunctionBroadband Infrastructure Production Function

( )0 1

1

ln lntPBL PBL t PBL

t

PENBBI

PENβ β ε

−

= + ⋅ +

(Koutroumpis,2009) (Koutroumpis,2009) Reference ModelReference Model•• KK t t : : Stock of telecommunications investment.Stock of telecommunications investment.

•• LFLF tt : : Labor force. Population between 15 and 64 years old. Labor force. Population between 15 and 64 years old.

•• PENPENtt : Broadband penetration. Number of broadband accesses per : Broadband penetration. Number of broadband accesses per

100 inhabitants. .100 inhabitants. .

•• BB_PRICEBB_PRICE : : Average price of a 1Mbps broadband connection. Average price of a 1Mbps broadband connection. •• BB_PRICEBB_PRICEtt : : Average price of a 1Mbps broadband connection. Average price of a 1Mbps broadband connection.

•• EDUEDUtt and and R&DR&Dtt : : Percentage of the GDP spent annually on Percentage of the GDP spent annually on

education and research and development. .education and research and development. .

•• URBURBtt : : Percentage of the population living in areas with Percentage of the population living in areas with

demographic density ≥ 500 demographic density ≥ 500 inhabinhab./km./km22..

•• BBIBBItt : : Broadband annual investment. .Broadband annual investment. .



•• BBIBBItt : : Broadband annual investment. .Broadband annual investment. .

•• COMPETITION_TECHCOMPETITION_TECHtt :: HerfindahlHerfindahl--Hirschman index, HIRSCHMAN Hirschman index, HIRSCHMAN (1964), for the competition among broadband technologies as DSL, (1964), for the competition among broadband technologies as DSL, WiFiWiFi, , WiMAXWiMAX, fiber optics, 3G cellular and others, fiber optics, 3G cellular and others

•• REGULATIOnREGULATIOntt : : Percentage of broadband accesses offered through Percentage of broadband accesses offered through

unbundlingunbundling

Models Used in the Present StudyModels Used in the Present Study••Used Used 6 models 6 models ((33 for the for the GDP GDP and and 33 for for

the the GDP per CapitaGDP per Capita))•• Model Model 11//22:: GDP/GDP/GDP per CapitaGDP per Capita:: Without price variable.Without price variable.Model Model 11//22:: GDP/GDP/GDP per CapitaGDP per Capita:: Without price variable.Without price variable.

•• Model Model 33//44 : : GDP/GDP/GDP per CapitaGDP per Capita: : With price variable. With price variable. •• Model Model 55//66 :: GDP/GDP/GDP per CapitaGDP per Capita: : With price variable With price variable

but but without without the variables regarding the variables regarding demographic demographic densitydensity and and educationeducation level because lack of expected level because lack of expected results:results:



results:results:•• Possible cause: pricePossible cause: price has bigger impact compared to has bigger impact compared to

other variables other variables (price elasticity in Brazil from (price elasticity in Brazil from --1 1 toto--3,36, Ávila (2008)), 3,36, Ávila (2008)), reducing the importance of reducing the importance of educationeducation and and demographic densitydemographic density in the model.in the model.

Model EquationsModel Equations•• Aggregated Production Function Aggregated Production Function –– GDP:GDP:

•• lnln((GDPGDPtt) = ) = ββββββββP0P0 + + ββββββββP1P1.ln(.ln(INVEST_BBINVEST_BBtt) + ) +

ββββββββP2P2.ln(POP_15_YR_8_YR_EDU.ln(POP_15_YR_8_YR_EDUtt) + ) + ββββββββP3P3.ln(DENS_BB.ln(DENS_BB tt) + ) + εεεεεεεεPP

•• lnln((GDP_PER_CAPTAGDP_PER_CAPTAtt) = ) = ββββββββP0P0 + + ββββββββP1P1.ln(.ln(INVEST_BBINVEST_BBtt) ) •• lnln((GDP_PER_CAPTAGDP_PER_CAPTAtt) = ) = ββββββββP0P0 + + ββββββββP1P1.ln(.ln(INVEST_BBINVEST_BBtt) )

++ββββββββP2P2.ln(POP_15_YR_8_YR_EDU.ln(POP_15_YR_8_YR_EDU tt) + ) + ββββββββP3P3.ln(DENS_BB.ln(DENS_BB tt) + ) + εεεεεεεεPP

•• Demand for Broadband Infrastructure:Demand for Broadband Infrastructure:

lnln(DENS(DENS__BBBB tt) = ) = ββββββββD0D0 ++ββββββββD1D1.ln(.ln(GDPGDP__PERPER__CAPTACAPTAtt) + ) + ββββββββD4D4.ln(.ln(PRICEPRICEtt) )

+ + ββββββββD2D2.(.(PERCENT_EDUPERCENT_EDUtt) + ) + ββββββββD3D3.ln(POP_50K.ln(POP_50K tt) + ) + εεεεεεεεDD

•• Supply of Broadband Infrastructure: Supply of Broadband Infrastructure:



•• Supply of Broadband Infrastructure: Supply of Broadband Infrastructure:

lnln((INVEST_BBINVEST_BBtt) = ) = ββββββββO0O0 + + ββββββββO1O1.ln(.ln(REV_BBREV_BBtt) + ) + ββββββββO2O2.ln(.ln(PRICEPRICEtt)+ )+ εεεεεεεεOO

•• Broadband Infrastructure Production Function:Broadband Infrastructure Production Function:

PBLPBLPBL

t

t BBINVESTBBDENS

BBDENSεββ +⋅+=

−

)_ln(_

_ln 10

1

VariablesVariables•• GDPGDPtt , , GDP_PER_CAPTAGDP_PER_CAPTAtt: : GDP and GDP per GDP and GDP per captacapta

per State from per State from 2000 to 20082000 to 2008. . Source IBGESource IBGE. . Obs. : Obs. : 2008 data estimated.2008 data estimated.

•• INVEST_BBINVEST_BB and and REV_BBREV_BB : : Broadband annual Broadband annual •• INVEST_BBINVEST_BBtt and and REV_BBREV_BBtt : : Broadband annual Broadband annual investments and Gross annual operational revenue investments and Gross annual operational revenue (2000 to 2008) (2000 to 2008) of the broadband providers. Data of the broadband providers. Data aggregated for the whole country. aggregated for the whole country. Source: ANATEL.Source: ANATEL.

•• POP_15_YR_8_YR_EDUt POP_15_YR_8_YR_EDUt , , PERCENT_EDUPERCENT_EDU : :



•• POP_15_YR_8_YR_EDUt POP_15_YR_8_YR_EDUt tt , , PERCENT_EDUPERCENT_EDUtt : :

population and percentage of the State population population and percentage of the State population

at least 15 years old and with 8 years or more of at least 15 years old and with 8 years or more of

complete education. complete education. Source: IBGE PNADSource: IBGE PNAD. .

Variables (cont.)Variables (cont.)•• POP_50KPOP_50K tt: : Share of the State population living in Share of the State population living in

cities with at least 50.000 inhabitants. cities with at least 50.000 inhabitants. Proxy for Proxy for

population concentration, replacing the variable used by population concentration, replacing the variable used by

KoutroumpisKoutroumpis (2009) of the share of the population living (2009) of the share of the population living KoutroumpisKoutroumpis (2009) of the share of the population living (2009) of the share of the population living

in areas where density ≥ 500 in areas where density ≥ 500 inhabinhab./ km./ km22. . Source: IBGE.Source: IBGE.

•• PRICEPRICEtt: : EstimatedEstimated average price charged for the average price charged for the

broadband access. broadband access. Source: Estimated from Source: Estimated from CETIC.BR CETIC.BR anualanual surveys from 2005 to 2008.surveys from 2005 to 2008.



•• DENS_BBDENS_BBtt : : Broadband density. Number of Broadband density. Number of accesses per 1000 inhabitants, for each State, accesses per 1000 inhabitants, for each State, between 2000 and 2008. between 2000 and 2008. Source Source AnatelAnatel (SICI). (SICI). Obs.: data from 2000 to 2006 estimated.Obs.: data from 2000 to 2006 estimated.

150

200

Bro

adband P

enet

ration p

er S

tate

(2000 to

20008) (bro

adband a

cces

ses per

1000 in

hab.)

Broadband Penetration X GDP Per Capita

Broadband Penetration X GDP Per Capita (other States)

Brazilian Capital District

Trend Line

Variables: Variables: GDP per Capita X Broadband PenetrationGDP per Capita X Broadband Penetration

y = 0,0029x - 10,796

R2 = 0,594

50

100

150

Bro

adband P

enet

ration p

er S

tate

(2000 to

20008) (bro

adband a

cces

ses per

1000 in

hab.)

Trend Line



-50

0

R$ 0 R$ 10,000 R$ 20,000 R$ 30,000 R$ 40,000 R$ 50,000

Bro

adband P

enet

ration p

er S

tate

(2000 to

20008) (bro

adband a

cces

ses per

1000 in

hab.)

GDP Per Capita per State UF (2000 to 2008) (R$)

160

180

200

Bro

adband P

enet

ration p

er S

tate

(2000 to

20008) (b

roadband a

cces

ses per

1000 in

hab.)

Broadband Penetration X Education

Broadband Penetration X Education (other States)


Trend Line (exponential)

Variables: Variables: Broadband Penetration X Education Broadband Penetration X Education

y = 0,0407e13,891x

R2 = 0,556

60

80

100

120

140

160

Bro

adband P

enet

ration p

er S

tate

(2000 to

20008) (b

roadband a

cces

ses per

1000 in

hab.)


or : ln(y) = -3,2 + 13,891.x

R2 = 0,556



0

20

40

0.1 0.2 0.3 0.4 0.5 0.6Bro

adband P

enet

ration p

er S

tate

(2000 to

20008) (b

roadband a

cces

ses per

1000 in

hab.)

Share of Population in Each State at Least 15 Years old and With at Least 8

Years of Complete Education (2000 to 2008)

5

6

ln(B

roadband P

enet

ration p

er S

tate

) (2

000 to

20008) (b

roadband a

cces

ses per

1000 in

hab.)

ln(Broadband Penetration) X Education

ln(Broadband Penetration) X Education (other States)


Trend Line (linear)

Variables: Variables: lnln(Broadband Penetration) X Education (Broadband Penetration) X Education

y = 13.891x - 3.2006

R² = 0.5558

0

1

2

3

4

ln(B

roadband P

enet

ration p

er S

tate

) (2

000 to

20008) (b

roadband a

cces

ses per

1000 in

hab.)



-3

-2

-10.1 0.2 0.3 0.4 0.5 0.6

ln(B

roadband P

enet

ration p

er S

tate

) (2

000 to

20008) (b

roadband a

cces

ses per

1000 in

hab.)

Natural Logarithm of the Share of Population in Each State at Least 15 Years

old and With at Least 8 Years of Complete Education (2000 to 2008)

R$ 35,000

R$ 40,000

R$ 45,000

GD

P P

er C

apita p

er S

tate

(2000 to 2

008) (R

$)

GDP per Capita X Education

GDP Per Capita X Education (other States)



Variables: Variables: GDP per Capita X EducationGDP per Capita X Education

y = 851,78e6,2109x

R2 = 0,859

R$ 10,000

R$ 15,000

R$ 20,000

R$ 25,000

R$ 30,000

R$ 35,000

GD

P P

er C

apita p

er S

tate

(2000 to 2

008) (R

$)


or ln(y) = 6,747 + 6,2109.x

R2 = 0,859



R$ 0

R$ 5,000

R$ 10,000

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

GD

P P

er C

apita p

er S

tate

(2000 to 2

008) (R

$)

Share of Population in Each State at Least 15 Years old and With at

Least 8 Years of Complete Education (2000 to 2008)

Dependent Dependent VariablesVariables

Coef.Coef.ModelModel 11 ModelModel 33 ModelModel 55

GMMGMM 3SLS3SLS GMMGMM 3SLS3SLS GMMGMM 3SLS3SLSAggregated Production Function Aggregated Production Function –– GDP Per CapitaGDP Per Capita

INVEST_BBINVEST_BBtt ββββββββP1P1 0,3840,384(48,365)(48,365) 0,3810,381(26,139)(26,139) 0,3860,386(53,844)(53,844) 0,3920,392(29,163)(29,163) 0,3810,381(51,346)(51,346) 0,3970,397(29,672)(29,672)

POPPOP__1515__YR_8YR_8__YRYR__EDUEDUt t ββββββββP2P2 1,0101,010(86,521)(86,521) 1,0951,095(47,894)(47,894) 1,1031,103(96,447)(96,447) 1,0931,093(51,880)(51,880) 1,1161,116(91,913)(91,913) 1,0841,084(51,745)(51,745)

DENS_BBDENS_BB tt ββββββββP3P3 0,1330,133(7,806)(7,806) 0,1800,180(8,670)(8,670) 0,0970,097(6,708)(6,708) 0,1040,104(5,613)(5,613) 0,0380,038(2,228) (2,228) ** 0,1090,109(5,860)(5,860)

Demand for Broadband Demand for Broadband

1,0881,088 0,7840,784 1,7131,713 1,5851,585 1,4531,453 1,2441,244

Regression Results: GDPRegression Results: GDP


GDP_PER_CAPITAGDP_PER_CAPITAtt ββββββββD1D1 1,0881,088(6,998)(6,998) 0,7840,784(5,796)(5,796) 1,7131,713(20,328)(20,328) 1,5851,585(18,552)(18,552) 1,4531,453(42,766)(42,766) 1,2441,244(46,685)(46,685)

PERCENT_EDUPERCENT_EDUtt ββββββββD2D2 0,1490,149(17,000)(17,000) 0,1490,149(16,465)(16,465) --0,0290,029((--4,368)4,368) --0,0220,022((--2,471)2,471) –– ––

POP_50KPOP_50K tt ββββββββD3D3 --3,2983,298((--11,347)11,347) --2,6222,622((--9,661)9,661) --0,3740,374**((--2,325)2,325) --0,4580,458((--2,512)2,512) –– ––

PRICEPRICE tt ββββββββD4D4–– –– --2,1112,111((--29,581)29,581) --1,8711,871((--22,634)22,634) --2,1282,128((--38,059)38,059) --1,7891,789((--39,769)39,769)

Broadband SupplyBroadband Supply

ConstantConstant ββββββββO0O0 4,7104,710(9,126)(9,126) 3,3773,377(6,925)(6,925) –– –– –– ––

REV_BBREV_BBtt ββββββββO1O1 0,7390,739(33,039)(33,039) 0,7970,797(37,704)(37,704) 0,8900,890(309,895)(309,895) 0,9010,901(211,142)(211,142) 0,8890,889(278,367)(278,367) 0,9020,902(211,302)(211,302)

PRICEPRICE tt ββββββββO3O3–– –– 0,2460,246(19,626)(19,626) 0,1960,196(10,183)(10,183) 0,2480,248(17,776)(17,776) 0,1910,191(9,926)(9,926)

Broadband Infrastructure Production Function Broadband Infrastructure Production Function




INVEST_BBINVEST_BBtt ββββββββPBL1PBL1 0,0230,023(19,384)(19,384) 0,0220,022(16,399)(16,399) 0,0220,022(21,954)(21,954) 0,0220,022(16,121)(16,121) 0,0220,022(21,124)(21,124) 0,0210,021(16,090)(16,090)

RR22

Aggregated Production Aggregated Production 0,9440,944 0,9400,940 0,9440,944 0,9450,945 0,9400,940 0,9450,945

DemandDemand 0,6410,641 0,6520,652 0,8540,854 0,8730,873 0,8130,813 0,8650,865

SupplySupply 0,8530,853 0,8560,856 0,8380,838 0,8530,853 0,8390,839 0,8540,854

Infrastructure Production Infrastructure Production --0,0310,031 --0,0250,025 --0,0250,025 --0,0250,025 --0,0250,025 --0.026 0.026

All coefficients at 1% significance level . Exceptions: * 5% significance.All coefficients at 1% significance level . Exceptions: * 5% significance.

Dependent Dependent VariablesVariables

Coef.Coef.Model 2Model 2 ModelModel 44 ModelModel 66

GMMGMM 3SLS3SLS GMMGMM 3SLS3SLS GMMGMM 3SLS3SLSAggregated Production Function Aggregated Production Function –– GDP Per CapitaGDP Per Capita

INVEST_BBINVEST_BBtt ββββββββP1P1 0,3010,301(23,248)(23,248) 0,3210,321(16,891)(16,891) 0,2910,291(23,375)(23,375) 0,3140,314(16,462)(16,462) 0,3070,307(27,641)(27,641) 0,3270,327(18,751)(18,751)

POPPOP__1515__YR_8YR_8__YRYR__EDUEDUtt ββββββββP2P2 0,1260,126(6,226)(6,226) 0,0880,088(2,989)(2,989) 0,1460,146(7,505)(7,505) 0,1180,118(3,952)(3,952) 0,1360,136(7,663)(7,663) 0,1040,104(3,809)(3,809)

DENS_BBDENS_BB tt ββββββββP3P3 0,3210,321(13,731)(13,731) 0,3620,362(12,664)(12,664) 0,2600,260(12,980)(12,980) 0,2380,238(9,432)(9,432) 0,1960,196(8,353)(8,353) 0,2030,203(8,015)(8,015)


Regression Results: GDP per CapitaRegression Results: GDP per Capita


GDP_PER_CAPITAGDP_PER_CAPITAtt ββββββββD1D1 1,0031,003(6,028)(6,028) 0,4880,488(3,235)(3,235) 2,1092,109(17,375)(17,375) 2,0052,005(17,337)(17,337) 1,3191,319(39,890)(39,890) 1,3401,340(44,020)(44,020)

PERCENT_EDUPERCENT_EDUtt ββββββββD2D2 0,1540,154(17,625)(17,625) 0,1640,164(17,734)(17,734) --0,0560,056((--5,416)5,416) --0,0450,045((--4,155)4,155) –– ––

POP_50KPOP_50K tt ββββββββD3D3 --3,1583,158((--9,920)9,920) --2,0902,090((--6,915)6,915) --0,9720,972((--4,275)4,275) --0,9240,924((--4,299)4,299) –– ––

PRICEPRICE tt ββββββββD4D4–– –– --2,1562,156((--22,467)22,467) --2,0712,071((--21,273)21,273) --1,928 1,928 ((--35,367)35,367) --1,9501,950((--37,986)37,986)

Broadband SupplyBroadband Supply

ConstantConstant ββββββββO0O0 4,6364,636(8,835)(8,835) 2,9612,961(5,985)(5,985) –– –– –– ––

REV_BBREV_BBtt ββββββββO1O1 0,7420,742(32,631)(32,631) 0,8150,815(38,014)(38,014) 0,8960,896(275,698)(275,698) 0,9010,901(209,549)(209,549) 0,890,89(245,745)(245,745) 0,9000,900(208,769)(208,769)

PRICEPRICE tt ββββββββO3O3–– –– 0,2160,216(15,272)(15,272) 0,1920,192(9,909)(9,909) 0,2070,207(12,835)(12,835) 0,1990,199 (10,221)(10,221)



PRICEPRICE tt ββββββββO3O3–– –– 0,2160,216(15,272)(15,272) 0,1920,192(9,909)(9,909) 0,2070,207(12,835)(12,835) 0,1990,199 (10,221)(10,221)


INVEST_BBINVEST_BBtt ββββββββPBL1PBL1 0,0240,024(19,379)(19,379) 0,0220,022(16,391)(16,391) 0,0210,021(20,657)(20,657) 0,0220,022(16,424)(16,424) 0,0230,023(22,062)(22,062) 0,0220,022(16,362)(16,362)

RR22

Aggregated Production Aggregated Production 0,4200,420 0,3890,389 0,4470,447 0,4650,465 0,4560,456 0,4630,463DemandDemand 0,6420,642 0,6420,642 0,8460,846 0,8560,856 0,8520,852 0,8500,850SupplySupply 0,8530,853 0,8540,854 0,8480,848 0,8540,854 0,8490,849 0,8530,853Infrastructure Production Infrastructure Production --0,0330,033 --0,0250,025 --0,0280,028 --0,0250,025 --0,0270,027 --0,0250,025

All coefficients at 1% significance level. All coefficients at 1% significance level.

Results: CommentsResults: Comments••High economic impact. Possible reasons:High economic impact. Possible reasons:•• Data problems: estimated values instead of Data problems: estimated values instead of

real ones: real ones: Ex.: Broadband Penetration per Ex.: Broadband Penetration per State; Broadband prices.State; Broadband prices.State; Broadband prices.State; Broadband prices.•• Historical series too recent (few samples): Historical series too recent (few samples): •• Annual data from 2000 to 2008 only.Annual data from 2000 to 2008 only.•• Low broadband penetration in Brazil: Low broadband penetration in Brazil: •• 2007: 45.8 accesses/100 2007: 45.8 accesses/100 inhabinhab. . High growth of High growth of



•• 2007: 45.8 accesses/100 2007: 45.8 accesses/100 inhabinhab. . •• 2008: 59.1 accesses/100 2008: 59.1 accesses/100 inhabinhab. . •• Important omitted variables: Important omitted variables: •• Ex.: Backhaul availability dataEx.: Backhaul availability data

High growth of High growth of penetration penetration level ( level ( ≈≈≈≈≈≈≈≈ 30% ) 30% ) over a small over a small base of base of subscribers.subscribers.

Thank You!Thank You!Thank You!Thank You!HildebrandoHildebrando R. R. MacedoMacedo -- ANATELANATEL

[email protected]@anatel.gov.br



AlexandreAlexandre X.YwataX.Ywata de de CarvalhoCarvalho -- [email protected]@ipea.gov.br

Additional Additional Additional Additional SlidesSlides



SlidesSlides

IntroductionIntroduction•• Broadband networks Broadband networks became important became important

developmentdevelopment aid tools for the countries, allowing aid tools for the countries, allowing to transform the existing economic activities as to transform the existing economic activities as well to create new ones.well to create new ones.well to create new ones.well to create new ones.

•• Several countries, like Several countries, like USA, Brazil, Australia, Spain USA, Brazil, Australia, Spain and others started to implement and others started to implement public policies public policies aiming increase the broadband penetration.aiming increase the broadband penetration.

•• Those initiatives had fundament on Those initiatives had fundament on economic economic



•• Those initiatives had fundament on Those initiatives had fundament on economic economic impact studiesimpact studies showing the importance of showing the importance of broadband networks broadband networks to boost economic to boost economic development. development.

Introduction and MotivationIntroduction and Motivation•• Several countries, like Several countries, like USA, Brazil, Australia, Spain USA, Brazil, Australia, Spain

and others started to implement and others started to implement public policies public policies aiming increase the broadband penetration.aiming increase the broadband penetration.

•• Those had fundament on Those had fundament on economic impact studieseconomic impact studies•• Those had fundament on Those had fundament on economic impact studieseconomic impact studiesshowing the importance of showing the importance of broadband networks broadband networks to to boost economic boost economic development. development.

•• The The properproper design of national design of national public policies public policies to to expand broadband penetration need expand broadband penetration need individualindividual



expand broadband penetration need expand broadband penetration need individualindividualEconomic Impact Economic Impact studies for each country to take studies for each country to take into account its particularities.into account its particularities.

•• This was the motivation to study the broadband This was the motivation to study the broadband economic impact in Brazil.economic impact in Brazil.

•• This study tried to address these This study tried to address these questions, for the questions, for the BrazilianBrazilian case:case:

•• Identify if there is a positive link between Identify if there is a positive link between

Objectives of the StudyObjectives of the Study

•• Identify if there is a positive link between Identify if there is a positive link between the increase in the broadband penetration the increase in the broadband penetration and the local economic development. and the local economic development.

•• Evaluate the broadband economic impact Evaluate the broadband economic impact



•• Evaluate the broadband economic impact Evaluate the broadband economic impact in Brazil using official statistics data from in Brazil using official statistics data from AnatelAnatel (the Brazilian telecom regulatory (the Brazilian telecom regulatory agency)agency)

ReferencesReferences•• World Bank study World Bank study ((QiangQiang

and others, 2009, and others, 2009, p. 35 to 50) *p. 35 to 50) *

Increase of Increase of 1,381,38 p.p. on the p.p. on the •• Increase of Increase of 1,381,38 p.p. on the p.p. on the GDP per capita growth rateGDP per capita growth ratefor each for each 1010 p.p. increase in p.p. increase in the broadband penetration the broadband penetration for developing countries for developing countries



for developing countries for developing countries (p. 45) .(p. 45) .

•• * * QIANGQIANG, Christine , Christine ZhenZhen--WeiWei; ; ROSSOTTOROSSOTTO, Carlo M. e , Carlo M. e KIMURA,KIMURA, KaoruKaoru, “, “EconomicEconomic

ImpactsImpacts ofof BroadbandBroadband”, em ”, em ICAD2009 ICAD2009 -- InformationInformation andand Communications for Communications for

DevelopmentDevelopment, Capítulo 3 : , Capítulo 3 : ExtendingExtending ReachReach andand IncreasingIncreasing ImpactImpact, pp. 35 a 50, , pp. 35 a 50, TheTheWorld World BankBank, Washington,DC, , Washington,DC, 20092009

ReferencesReferences

•• Crandall and others (2007) Crandall and others (2007)



Crandall and others (2007) Crandall and others (2007)

•• Increase between Increase between 0,2 to 0,30,2 to 0,3 p.p. in the p.p. in the employment level for each employment level for each 11 p.p. increase in p.p. increase in the broadband penetration the broadband penetration (p. 2)(p. 2)

ReferencesReferences•• KoutskyKoutsky and Ford and Ford (2005) (2005) •• KOUTSKYKOUTSKY , , ThomasThomas MM. e . e FORD ,FORD ,GeorgeGeorge SS., "., "Broadband and Broadband and

Economic Development: A Municipal Case Study from FloridaEconomic Development: A Municipal Case Study from Florida" , " , Review of Urban & Regional Development StudiesReview of Urban & Regional Development Studies, Vol. 17, No. 3, , Vol. 17, No. 3, pp. 219pp. 219--229, 2005, 229, 2005, Journal of the Applied Regional Science Journal of the Applied Regional Science pp. 219pp. 219--229, 2005, 229, 2005, Journal of the Applied Regional Science Journal of the Applied Regional Science CConferenceonference

•• Approximately Approximately 100% 100% increase in the increase in the economic economic activity activity of of Lake County, Florida (USA)Lake County, Florida (USA) after after public investment in the deployment of public investment in the deployment of extensive fiber optics network.extensive fiber optics network.

•• This when compared to similar localities that This when compared to similar localities that



•• This when compared to similar localities that This when compared to similar localities that had not had not such investment. such investment.

•• Evaluated broadband economic impact Evaluated broadband economic impact on on 22 OECD22 OECD, , countries with data from countries with data from 2002 to 20072002 to 2007. .

(Koutroumpis,2009) (Koutroumpis,2009) Reference StudyReference Study

2002 to 20072002 to 2007. . •• Reproduced Reproduced RöllerRöller e e WavermanWaverman (2001(2001) )

study which evaluated economic impact study which evaluated economic impact of fixed line telephone networks.of fixed line telephone networks.

•• Results :Results :



•• Results :Results :Each Each 1p.p.1p.p. increase in the broadband increase in the broadband penetration was related to about penetration was related to about 0,025p.p.0,025p.p. GDP increase (p. 477). GDP increase (p. 477).

Reference ModelReference Model•• ReplicatedReplicated (Koutroumpis,2009) (Koutroumpis,2009)

modelmodel with data from Brazilwith data from Brazil––Model: Model: Simultaneous equations of supply Simultaneous equations of supply

and demand with endogenous variables. and demand with endogenous variables. ––Model: Model: Simultaneous equations of supply Simultaneous equations of supply

and demand with endogenous variables. and demand with endogenous variables. –– Justification: Justification: To capture the simultaneous To capture the simultaneous

effect of telecom investment on the effect of telecom investment on the economy:economy:•• Investment in telecommunications Investment in telecommunications lead to lead to

increase in the economic developmentincrease in the economic development



increase in the economic developmentincrease in the economic developmentAt the same time:At the same time:•• Economic development Economic development of the country of the country

increases demand for increases demand for investment in investment in telecommunications infrastructure. telecommunications infrastructure.

60.0

70.0

80.0M

arket Shares (%

)

Broadband Market Shares per Access Speeds

Broadband Accesses per SpeedBroadband Accesses per Speed

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 20100.0

10.0

20.0

30.0

40.0

50.0

Market Shares (%

)



2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

0 a 64Kbps 75.8 33.3 30.6 34.6 26.9 20.1 19.5 12.6 11.6 11.8 10.4

64K a 512Kbps 15.4 62.5 66.1 61.7 45.0 52.6 51.0 59.9 37.1 28.6 21.1

512K a 2Mbps 5.8 3.1 2.6 3.2 27.0 26.5 27.6 25.5 42.3 44.9 49.6

2M a 34Mbps 2.1 0.8 0.5 0.4 0.9 0.6 1.7 1.6 8.3 14.0 18.6

> 34Mbps 0.9 0.4 0.3 0.2 0.2 0.2 0.2 0.3 0.7 0.7 0.3

TOTAL (%) 100 100 100 100 100 100 100 100 100 100 100

0.0

YearSource: (ANATEL-SICI).

Broadband Accesses per TechnologyBroadband Accesses per Technology

50

60

70

Mark

et S

hare

s (%

)

Broadband Market Shares per Technology

0

10

20

30

40

Mark

et S

hare

s (%

)



2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Other Technologies 48.21 19.91 18.1 27.69 30.36 29.65 16.4 12.43 12.55 11.72 9.8

xDSL 10.57 60.56 61.96 54.95 60.94 61.76 66.32 66.01 65.13 66.58 59.23

Wireless 11.08 7.16 5.03 3.59 2.79 2.77 1.75 4.09 2.9 3 5.13

Cable Modem 2.57 1.7 5.93 7.34 3.5 3.54 14.15 15.97 17.69 17.43 23.16

Sattelite 22.95 10.66 9.08 6.43 2.4 2.28 1.37 1.49 1.72 1.28 0.93

0

Year

Estimated Data UsedEstimated Data Used

•• Some Important Data had to be Some Important Data had to be Estimated: Estimated: Estimated: Estimated: ––Broadband penetration Broadband penetration

disaggregated by State from 2000 disaggregated by State from 2000 to 2006.to 2006.––GDP per State in 2008GDP per State in 2008



––GDP per State in 2008GDP per State in 2008––Broadband PricesBroadband Prices

Data Estimation: Broadband Penetration Data Estimation: Broadband Penetration per State from 2000 to 2006per State from 2000 to 2006

SSharehare of each of each one of the one of the 27 27

AApprpproximation:oximation:

Share Share of each of each SSharehare of each of each one of the one of the 27 27 Brazilian StatesBrazilian Stateson the total on the total internet accessesinternet accesses

≈≈≈≈≈≈≈≈Share Share of each of each one of the one of the 27 27 Brazilian States Brazilian States on the total on the total broadband broadband



internet accessesinternet accesses(broadband or (broadband or not) not) in thein the country country

broadband broadband accesses accesses in the in the country.country.

20072007 20082008STATESSTATES´́ SHARES ON THE COUNTRYSHARES ON THE COUNTRY´́SS TOTAL TOTAL NUMBER OF:NUMBER OF:

STATESTATEBROADBANDBROADBAND ACCESSESACCESSES

(4th Quarter(4th Quarter 2007) 2007) (%) (ANATEL(%) (ANATEL--SICI)SICI)

INTERNETINTERNET ACCESSESACCESSES(%) (IBGE (%) (IBGE --PNAD 2007)PNAD 2007)

BROADBANDBROADBAND ACCESSESACCESSES(4th Quarter(4th Quarter 2008) 2008) (%) (ANATEL(%) (ANATEL--SICI)SICI)

INTERNETINTERNET ACCESSESACCESSES(%) (IBGE (%) (IBGE --PNAD 2008)PNAD 2008)

ACAC 0.3330.333 0.1840.184 0.1550.155 0.2240.224ALAL 0.3710.371 0.4730.473 0.3570.357 0.6050.605

AMAM 0.4770.477 0.6080.608 0.4910.491 0.7010.701APAP 0.0360.036 0.1190.119 0.0480.048 0.1070.107

** BABA 2.7742.774 3.5763.576 2.8762.876 4.1624.162** BABA 2.7742.774 3.5763.576 2.8762.876 4.1624.162** CECE 1.7891.789 1.5591.559 1.6411.641 1.8961.896** DFDF 3.8603.860 2.5112.511 4.3484.348 2.4712.471

ESES 1.3451.345 2.0742.074 1.5771.577 2.0402.040** GOGO 2.4672.467 2.2492.249 2.5562.556 2.3662.366

MAMA 0.5390.539 0.7130.713 0.5190.519 0.9160.916** MGMG 8.3208.320 9.7749.774 9.0409.040 10.37210.372

MSMS 0.8310.831 1.0271.027 1.2131.213 1.0601.060MTMT 0.4080.408 0.9590.959 1.3131.313 1.3851.385PAPA 0.9750.975 1.0331.033 0.9840.984 1.1611.161PBPB 0.4940.494 0.7430.743 0.6200.620 0.9600.960

** PEPE 1.7311.731 2.0492.049 1.7151.715 2.1602.160PIPI 0.3930.393 0.4680.468 0.3970.397 0.5040.504



PIPI 0.3930.393 0.4680.468 0.3970.397 0.5040.504** PRPR 6.9846.984 7.2147.214 7.8167.816 7.3667.366** RJRJ 11.15111.151 13.16013.160 11.08711.087 12.77412.774

RNRN 0.4980.498 0.8190.819 0.5360.536 0.8700.870RORO 0.9410.941 0.4880.488 0.4350.435 0.4890.489RRRR 0.0230.023 0.1150.115 0.0230.023 0.1180.118

** RSRS 7.3947.394 6.8086.808 6.8846.884 6.5946.594** SCSC 5.5145.514 4.7374.737 4.4344.434 4.7744.774

SESE 0.4520.452 0.5860.586 0.4410.441 0.6430.643** SPSP 39.53539.535 35.68435.684 38.15138.151 32.97532.975

TOTO 0.3670.367 0.2700.270 0.3430.343 0.3110.311

20072007 20082008AA BB CC DD

STATESTATE

STATESSTATES´́ SHARES ON SHARES ON THE COUNTRYTHE COUNTRY´́S S

TOTAL TOTAL BROADBANDBROADBANDACCESSES (%)ACCESSES (%)

STATESSTATES´́ SHARES ON SHARES ON THE COUNTRYTHE COUNTRY´́S S TOTAL TOTAL INTERNETINTERNET

ACCESSES (%)ACCESSES (%)

STATESSTATES´́ SHARES ON SHARES ON THE COUNTRYTHE COUNTRY´́S S

TOTAL TOTAL BROADBANDBROADBANDACCESSES (%)ACCESSES (%)

STATESSTATES´́ SHARES ON SHARES ON THE COUNTRYTHE COUNTRY´́S S TOTAL TOTAL INTERNETINTERNET

ACCESSES (%)ACCESSES (%)

BABA 2.7742.774 3.5763.576 2.8762.876 4.1624.162** BABA 2.7742.774 3.5763.576 2.8762.876 4.1624.162** CECE 1.7891.789 1.5591.559 1.6411.641 1.8961.896** DFDF 3.8603.860 2.5112.511 4.3484.348 2.4712.471** GOGO 2.4672.467 2.2492.249 2.5562.556 2.3662.366** MGMG 8.3208.320 9.7749.774 9.0409.040 10.37210.372** PEPE 1.7311.731 2.0492.049 1.7151.715 2.1602.160** PRPR 6.9846.984 7.2147.214 7.8167.816 7.3667.366



** PRPR 6.9846.984 7.2147.214 7.8167.816 7.3667.366** RJRJ 11.15111.151 13.16013.160 11.08711.087 12.77412.774** RSRS 7.3947.394 6.8086.808 6.8846.884 6.5946.594** SCSC 5.5145.514 4.7374.737 4.4344.434 4.7744.774** SPSP 39.53539.535 35.68435.684 38.15138.151 32.97532.975

Estimation ResultsEstimation Results

•• StatesStates´́ Shares of Shares of BroadbandBroadband AccessesAccessesXXXX

•• StatesStates´́ Shares of Shares of InternetInternet AccessesAccesses

•• 2007: R2007: R22 = 0,86= 0,86



•• 2008: R2008: R22 = 0,79= 0,79

2628303234363840

Part

icip

ati

on (

%)

Share of each State on the country total broadband accesses

Share of each State on the country total homes with internet

2008 - Comparison: Shares of States on the country’s total broadband accesses X

Shares of States on the country total homes with internet access

2468

101214161820222426

Part

icip

ati

on (

%)



ComparisonComparison ofof eacheach statestate shareshare onon thethe countrycountry´́ss totaltotal numbernumber ofof broadbandbroadbandaccessesaccesses andand onon thethe totaltotal numbernumber ofof internetinternet accesses,accesses, forfor 20082008..SourceSource:: elaboratedelaborated byby thethe authorsauthors fromfrom AnatelAnatel andand IBGEIBGE datadata..

02

SP RJ MG PR RS SC DF BA GO PE CE ES MT MS PA PB RN MA AM SE RO PI AL TO AC AP RR State

242628303234363840

Part

icip

ati

on (

%)

Share of each State on the country total broadband accesses

Share of each State on the country total homes with internet

2007 - Comparison: Shares of States on the country total broadband accesses X

Shares of States on the country total homes with internet access

2468

1012141618202224

Part

icip

ati

on (

%)

(%)



ComparisonComparison ofof eacheach statestate shareshare onon thethe countrycountry´́ss totaltotal numbernumber ofof broadbandbroadbandaccessesaccesses andand onon thethe totaltotal numbernumber ofof internetinternet accesses,accesses, forfor 20072007..SourceSource:: elaboratedelaborated byby thethe authorsauthors fromfrom AnatelAnatel andand IBGEIBGE datadata..

02

SP RJ MG PR RS SC DF BA GO PE CE ES MT MS PA PB RN MA AM SE RO PI AL TO AC AP RR

State

2008 GDP States2008 GDP States´́ EstimatesEstimates

•• Only Only nationalnational 2008 GDP available but not 2008 GDP available but not GDP per State. GDP per State.

•• To estimate the GDP per To estimate the GDP per StateState of of 20082008: : •• To estimate the GDP per To estimate the GDP per StateState of of 20082008: : –– It was assumed that each It was assumed that each StateState would retain would retain

the same national GDP share of the same national GDP share of 20072007. . ––Hypothesis reinforced when compared data Hypothesis reinforced when compared data

of of 20062006 and and 20072007 for the participation of for the participation of



of of 20062006 and and 20072007 for the participation of for the participation of each State in the national GDP (each State in the national GDP (similar to similar to the first decimal casethe first decimal case) )

Shares of Each State on the National GDP (%) Shares of Each State on the National GDP (%) (Source: IBGE)(Source: IBGE)20022002 20032003 20042004 20052005 20062006 20072007

NORTENORTE 4.694.69 4.784.78 4.954.95 4.964.96 5.065.06 5.025.02RondôniaRondônia 0.530.53 0.570.57 0.580.58 0.600.60 0.550.55 0.560.56AcreAcre 0.190.19 0.190.19 0.200.20 0.210.21 0.200.20 0.220.22AmazonasAmazonas 1.471.47 1.471.47 1.561.56 1.551.55 1.651.65 1.581.58RoraimaRoraima 0.160.16 0.160.16 0.140.14 0.150.15 0.150.15 0.160.16ParáPará 1.741.74 1.751.75 1.831.83 1.821.82 1.871.87 1.861.86AmapáAmapá 0.220.22 0.200.20 0.200.20 0.200.20 0.220.22 0.230.23TocantinsTocantins 0.380.38 0.430.43 0.430.43 0.420.42 0.410.41 0.420.42TocantinsTocantins 0.380.38 0.430.43 0.430.43 0.420.42 0.410.41 0.420.42

NORDESTENORDESTE 12.9612.96 12.7712.77 12.7212.72 13.0713.07 13.1313.13 13.0713.07MaranhãoMaranhão 1.051.05 1.091.09 1.111.11 1.181.18 1.211.21 1.191.19PiauíPiauí 0.500.50 0.520.52 0.510.51 0.520.52 0.540.54 0.530.53CearáCeará 1.961.96 1.921.92 1.901.90 1.911.91 1.951.95 1.891.89Rio Grande do NorteRio Grande do Norte 0.830.83 0.800.80 0.800.80 0.830.83 0.870.87 0.860.86ParaíbaParaíba 0.840.84 0.830.83 0.770.77 0.790.79 0.840.84 0.830.83PernambucoPernambuco 2.392.39 2.312.31 2.272.27 2.322.32 2.342.34 2.342.34AlagoasAlagoas 0.660.66 0.660.66 0.660.66 0.660.66 0.660.66 0.670.67SergipeSergipe 0.640.64 0.640.64 0.630.63 0.630.63 0.640.64 0.630.63BahiaBahia 4.114.11 4.014.01 4.074.07 4.234.23 4.074.07 4.124.12

SUDESTESUDESTE 56.6856.68 55.7555.75 55.8355.83 56.5356.53 56.7956.79 56.4156.41Minas GeraisMinas Gerais 8.658.65 8.758.75 9.139.13 8.978.97 9.069.06 9.079.07Espírito SantoEspírito Santo 1.811.81 1.831.83 2.072.07 2.202.20 2.232.23 2.272.27



Espírito SantoEspírito Santo 1.811.81 1.831.83 2.072.07 2.202.20 2.232.23 2.272.27Rio de JaneiroRio de Janeiro 11.6011.60 11.0611.06 11.4811.48 11.5011.50 11.6211.62 11.1511.15São PauloSão Paulo 34.6334.63 34.1134.11 33.1433.14 33.8633.86 33.8733.87 33.9233.92

SULSUL 16.8916.89 17.7017.70 17.3917.39 16.5916.59 16.3216.32 16.6416.64ParanáParaná 5.985.98 6.446.44 6.316.31 5.905.90 5.775.77 6.076.07Santa CatarinaSanta Catarina 3.773.77 3.933.93 3.993.99 3.973.97 3.933.93 3.933.93Rio Grande do SulRio Grande do Sul 7.147.14 7.337.33 7.107.10 6.726.72 6.626.62 6.646.64

CENTROCENTRO--OESTEOESTE 8.778.77 9.019.01 9.119.11 8.868.86 8.718.71 8.878.87Mato Grosso do SulMato Grosso do Sul 1.031.03 1.131.13 1.091.09 1.011.01 1.031.03 1.061.06Mato GrossoMato Grosso 1.421.42 1.641.64 1.901.90 1.741.74 1.491.49 1.601.60GoiásGoiás 2.532.53 2.522.52 2.472.47 2.352.35 2.412.41 2.452.45Distrito FederalDistrito Federal 3.803.80 3.713.71 3.643.64 3.753.75 3.783.78 3.763.76

BRASILBRASIL 100.00100.00 100.00100.00 100.00100.00 100.00100.00 100.00100.00 100.00100.00

Broadband Price EstimationBroadband Price Estimation•• No No reliablereliable, , disaggregateddisaggregated with with historical historical

series series data available in Brazil data available in Brazil

•• The The few data few data available were scattered from available were scattered from •• The The few data few data available were scattered from available were scattered from several sources, mainly from several sources, mainly from sporadicsporadicsurveyssurveys performed by telecom equipment performed by telecom equipment manufacturers, consultant companies or manufacturers, consultant companies or other organizations.other organizations.



•• For academic purposes is desirable to count For academic purposes is desirable to count on official and more reliable data. on official and more reliable data.

•• AnatelAnatel started to collect prices data in 2011 started to collect prices data in 2011 only only

•• Alternative : Alternative : estimate prices from survey estimate prices from survey data done by data done by CETIC.BRCETIC.BR , which is part of , which is part of

Broadband Price EstimationBroadband Price Estimation

data done by data done by CETIC.BRCETIC.BR , which is part of , which is part of the the CGI.br CGI.br (internet management (internet management committee)committee)

•• Annual surveys from CETIC.br ask :Annual surveys from CETIC.br ask :

““MAXIMUM DECLARED VALLUE BY USERS MAXIMUM DECLARED VALLUE BY USERS



““MAXIMUM DECLARED VALLUE BY USERS MAXIMUM DECLARED VALLUE BY USERS WILLING TO SUBSCRIBE INTERNET WILLING TO SUBSCRIBE INTERNET ACCESS SERVICE”.ACCESS SERVICE”.

Broadband Price EstimationBroadband Price Estimation•• Price x Penetration Model Adjusted: Price x Penetration Model Adjusted:

Y = A . eY = A . e--B.X B.X , where:, where:

Y: Y: number of broadband accesses per 1000 number of broadband accesses per 1000 •• Y: Y: number of broadband accesses per 1000 number of broadband accesses per 1000 inhabitants.inhabitants.

•• X: X: maximum declared price to subscribe the maximum declared price to subscribe the service.service.



•• A :A : saturation. Penetration value when price saturation. Penetration value when price is zero.is zero.

•• B :B : decay factor.decay factor.


•• Approximation of the broadband price Approximation of the broadband price as a function of penetration :as a function of penetration :

( )ln YA

XB

= −



Broadband Price EstimationBroadband Price Estimation•• Same procedure for Same procedure for 20052005 to to 20082008..

Broadband price-demand sensitivity - 2005 to 2008

70

80 Per

centa

ge

of hom

es w

her

e use

rs w

ere

willing to

cces

s se

rvic

e (%

) 2008 20072006 2005General model

20

30

40

50

60

Per

centa

ge

of hom

es w

her

e use

rs w

ere

willing to

Subsc

ribe

the

inte

rnet

acc

ess se

rvic

e

General model

General model

y = 66,483939.e-0.014821.x

R2 = 0,960405



0

10

20

0 50 100 150 200 250 300

Maximum declared value declared by user (home) willing to subscribe

to the internet access service (R$).

Per

centa

ge

of hom

es w

her

e use

rs w

ere

willing to

to

Subsc

ribe

the

inte

rnet

(%)


•• For For 2000 to 2004 2000 to 2004 used used 2005 2005 curve due lack of curve due lack of survey data for these years.survey data for these years.

•• The curves show a trend of being shifted as The curves show a trend of being shifted as •• The curves show a trend of being shifted as The curves show a trend of being shifted as the times goes by and broadband prices the times goes by and broadband prices decrease.decrease.

•• Despite its limitations, it allowed to have a Despite its limitations, it allowed to have a glimpse of the effect of the broadband price glimpse of the effect of the broadband price



glimpse of the effect of the broadband price glimpse of the effect of the broadband price on the demand for the service.on the demand for the service.

•• Other studies used the same approach Other studies used the same approach ((CoutinhoCoutinho, Acorn, Acorn--RedecomRedecom 20102010).).

Models UsedModels Used•• Analysis without broadband prices: Analysis without broadband prices: initial initial

analysis because lack of analysis because lack of reliablereliable broadband broadband price data.price data.

•• Analysis with estimated broadband prices:Analysis with estimated broadband prices:because the because the impactimpact of price in the demand / of price in the demand / supply of the service, it was necessary to find supply of the service, it was necessary to find a way to estimate approximated prices using a way to estimate approximated prices using



a way to estimate approximated prices using a way to estimate approximated prices using survey data from survey data from CETIC (CGI).CETIC (CGI).

•• Prices estimated from maximum declared Prices estimated from maximum declared values of users willing to subscribe internet values of users willing to subscribe internet access service. access service.

Models UsedModels Used•• Analysis without Analysis without educationeducation and and demographicdemographic

density variables: density variables: •• Excluded variables in the third type of model Excluded variables in the third type of model

because did not present the expected results:because did not present the expected results:because did not present the expected results:because did not present the expected results:•• When including When including priceprice, both , both education education and and

demographic density demographic density had negative impact on had negative impact on broadband density.broadband density.

•• Possible cause: Possible cause: priceprice has bigger impact when has bigger impact when compared to other variables compared to other variables (price elasticity in (price elasticity in



compared to other variables compared to other variables (price elasticity in (price elasticity in Brazil from Brazil from --1 1 toto --3,363,36, , Ávila (2008)Ávila (2008))), reducing the , reducing the importance of importance of educationeducation and and demographic densitydemographic densityin the model.in the model.

Simultaneous Equations Model: Simultaneous Equations Model: Main Results Main Results

•• Each Each 1 p.p. 1 p.p. increase in the increase in the broadband penetration is related to broadband penetration is related to broadband penetration is related to broadband penetration is related to a a GDP growth GDP growth in Brazil between in Brazil between 0.0380.038 to to 0,180,18 p.p. p.p.

•• EachEach1 p.p. 1 p.p. increase in the broadband increase in the broadband



•• EachEach1 p.p. 1 p.p. increase in the broadband increase in the broadband penetration is related to a penetration is related to a GDP per GDP per Capita growth Capita growth in Brazil between in Brazil between 0.1960.196 to to 0,3620,362 p.p.p.p.

Simultaneous Equations Model: Simultaneous Equations Model: Main Results Main Results

•• However it was not possible to establish However it was not possible to establish causality relation between increase of causality relation between increase of causality relation between increase of causality relation between increase of the Broadband Penetration and the Broadband Penetration and economic growth.economic growth.

•• For that it would be necessary other For that it would be necessary other approach using long term relationship approach using long term relationship



approach using long term relationship approach using long term relationship (long term time series and (long term time series and Granger Granger causality testcausality test))

Comparison with Other StudiesComparison with Other StudiesValues of Regression CoefficientsValues of Regression Coefficients

Earlier StudiesEarlier Studies This StudyThis Study

Dependent Dependent Variable Variable

Explaining Explaining VariablesVariables

World Bank World Bank ((QiangQiang et. al, et. al, 2009, p. 44)2009, p. 44)

Koutroumpis (2009, Koutroumpis (2009, p.478)p.478)

Simultaneous Equations Simultaneous Equations

Simultaneous Simultaneous Equations Equations

2009, p. 44)2009, p. 44) Simultaneous Equations Simultaneous Equations

GDPGDP BroadbandBroadbandPenetration Penetration (number of (number of

accesses accesses per per

0,012, 0,012, 0.023, 0.023,

0.025 and 0.025 and 0.2040.204

0.038, 0.038, 0.097,0.097,0.109 , 0.104, 0.109 , 0.104,

0.133 and 0.133 and 0.1800.180

0.1380.138



per per inhabitants)inhabitants)GDP per GDP per

CapitaCapita

0.1380.138(developing(developing

countriescountries))

0.121 0.121 (developed(developedcountriescountries))

0.196 , 0.196 , 0.203 ,0.203 ,0.238, 0.260,0.238, 0.260,

0.3210.321 and and 0.3620.362

Results: CommentsResults: Comments•• Other possible reasons:Other possible reasons:•• Differences in in the historical moment when Differences in in the historical moment when

broadband networks became available:broadband networks became available:•• Developed countries: Developed countries: arrived when they already had arrived when they already had •• Developed countries: Developed countries: arrived when they already had arrived when they already had

a good telecom infrastructure with well developed a good telecom infrastructure with well developed fixed line and mobile phone networks:fixed line and mobile phone networks:•• So broadband economic impact was diluted So broadband economic impact was diluted as just one as just one

more development increase factor, because those more development increase factor, because those countries already had reached high development levels. countries already had reached high development levels.

•• Developing countries:Developing countries: broadband networks became broadband networks became



•• Developing countries:Developing countries: broadband networks became broadband networks became an important instrument to boost development an important instrument to boost development (“catch up” effect):(“catch up” effect):•• Helping develop education areas and others.Helping develop education areas and others.

Key Message Key Message ••Despite all limitations of this study:Despite all limitations of this study:–– It was a It was a first attempt first attempt to make this kind of study to make this kind of study

for for BrazilBrazil. Expectation that it would . Expectation that it would “open the “open the gates” gates” to further and to further and more precise more precise studies, studies, gates” gates” to further and to further and more precise more precise studies, studies, overcoming the limitations overcoming the limitations and errors of this one.and errors of this one.

–– It is important that It is important that each country make an effort each country make an effort to develop its own broadband impact evaluation to develop its own broadband impact evaluation studiesstudies, instead of using estimations made for , instead of using estimations made for



studiesstudies, instead of using estimations made for , instead of using estimations made for other countries with different realities. other countries with different realities. –– You have to know your own reality in order to You have to know your own reality in order to

develop adequate solutions for the problems that develop adequate solutions for the problems that need to be addressed.need to be addressed.

Regression Results: CommentsRegression Results: Comments•• It may occur RIt may occur R22 < 0 in models without a constant < 0 in models without a constant

(intercept) and which are unable to explain properly the (intercept) and which are unable to explain properly the dependent variable.dependent variable.

� 2( )n

y y−∑

•• : sample value : sample value ii of explaining variable of explaining variable yy..•• : estimated values by the regression model.: estimated values by the regression model.

� 2

2 1

2

1

( )

1 1

( )

i i

i

n

i

i

y ySSR

RSST

y y

=

=

−= − = −

−

∑

∑

�iy

iy



•• : estimated values by the regression model.: estimated values by the regression model.•• : average of sample values.: average of sample values.

�iy

y

Regression Results: CommentsRegression Results: Comments•• : squared sum of errors between estimated : squared sum of errors between estimated

and real sample values. and real sample values. •• : squared sum of differences between each : squared sum of differences between each

sample value and the average value of all samples. sample value and the average value of all samples.

� 2

1

( )n

i i

i

SSR y y=

= −∑

2

1

( )n

i

i

SST y y=

= −∑sample value and the average value of all samples. sample value and the average value of all samples.

•• When SSR > SST, the model errors are bigger than the When SSR > SST, the model errors are bigger than the errors obtained if the model was represented just by the errors obtained if the model was represented just by the average value of the samples. average value of the samples.

•• It may happen in the lack of a constant (intercept) in the It may happen in the lack of a constant (intercept) in the

1i=



It may happen in the lack of a constant (intercept) in the It may happen in the lack of a constant (intercept) in the equation model and when the model itself is insufficient equation model and when the model itself is insufficient to explain the dependent variable behavior. to explain the dependent variable behavior.

•• So, when RSo, when R22 <<<<<<<< 0, the 0, the RR2 2 loses its characteristic of “quality” loses its characteristic of “quality” indicator of the model. indicator of the model.

0 .0

0 .5

1 .0

1 .5

2 .0

LO G (D E NS _ B _ L A RG _ U F /D E NS _ B _ L A RG _U F (-1 ) )

2

3

4

5

D E NS _ B _ L A RG _U F /D E NS _ B _ L A RG _U F (- 1 )


( ) PBLtPBLPBL

t

t BBINVESTBBDENS

BBDENSεββ +⋅+=

−

_ln_

_ln 10

1

••Difficulty to Difficulty to match the model match the model

2 2 .0

2 2 .4

2 2 .8

2 3 .2

2 3 .6

LO G (IN V _ S E RV _ F IX )

2 2 .8

2 3 .0

2 3 .2

2 3 .4

2 3 .6

2 3 .8

2 4 .0

L OG (IN V _ TO T _ TE L E C OM )

-1 .0

-0 .5

0 .0

2 0 0 0 2 00 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5 2 0 0 6 2 0 0 7 2 0 0 80

1

2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5 2 0 0 6 2 0 0 7 2 00 8

match the model match the model with real data.with real data.

••Lack of intercept.Lack of intercept.



2 2 .0

2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5 2 0 0 6 2 0 0 7 2 0 0 8

2 2 .8

2 0 0 0 2 0 0 1 2 00 2 2 0 0 3 2 0 0 4 2 0 0 5 2 0 0 6 2 0 0 7 2 0 0 8

2 1 .2

2 1 .4

2 1 .6

2 1 .8

2 2 .0

2 2 .2

2 2 .4

2 2 .6

2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5 2 0 0 6 2 0 0 7 2 0 0 8

LO G (IN V E S T_ S C M )••That lead toThat lead toRR22 < 0< 0

Documents

Broadband Economic Impact in Brazil: a Simultaneous Equations