Download Digital Divide in ASEAN Countries

Digital Divide in ASEAN Countries: How wide is the gap and what is
the role of independent regulator?
Chalita Srinuan, Ibrahim Kholilul Rohman, Pratompong Srinuan and Erik Bohlin
Abstract
Currently, the Information and Communication Technology (ICT) sector is a
vigorous engine of economic growth. While the penetration rate, investment and
development of technology have increased considerably, the gap between people in
society regarding access, use and benefit from ICT is increasing. In particular, there
is unequal access to ICT even though the sector is rapidly diffusing.
The present study examines determinants of this digital divide in ASEAN countries
(Brunei, Cambodia, Indonesia, Lao, Philippines, Malaysia, Myanmar, Thailand,
Singapore and Vietnam). To explain the evolution of the ASEAN digital divide, the
study focuses on potential causes which are the GDP per capita, the urban
proportion of the population, the competition level and the independent regulator.
Statistically, the first three of these factors explain the divide in the region concerned
while the role of independent regulator is not statistically significant suggesting the
need for the more effective role of regulator in conducting the market.
2
1.
Introduction
The term "digital divide" refers to the gap between individuals, households,
businesses and geographic areas at different socioeconomic levels with regard to
opportunity to access information and communication technologies (ICTs) and to
their use of the Internet (OECD, 2001). Factors which determine the existence of a
digital divide include individual and household income, education, age, gender and
linguistic background.
In recent years, it has been accepted that ICTs are significant inputs to economic
growth. Moreover, the efficiency of ICTs in the development of international
competitiveness, health and education, and in creating new job possibilities, is
considered to be a significant component in determining the socioeconomic structure
of countries, and a way of decreasing poverty (World Bank, 2006). ICTs are not just a
producing sector as such, but are used in all sectors, e.g. education, health,
environment and government. Thus, inadequate ICT use makes it impossible to
optimize benefits. This digital divide issue can increase the inequality in economic
performance between developed countries and developing nations.
This paper examines whether a digital divide exists between developing
countries, which in this case are represented by ASEAN countries1. Since the digital
divide is not a technological problem but an economic, social, and political issue, an
econometric model is applied to analyze the effect of the digital divide among these
countries. The structure of the paper is as follows. Section 2 provides a literature
review of the digital divide. Telecommunication services in ASEAN countries are
described in section 3. Section 4 deals with the methodology and techniques. Section
5 explains and discusses the results. Section 6 draws conclusions.
2. Literature review
Studies of digital divide can be separated into domestic and international
dimensions. A domestic digital divide refers to a digital divide between groups
within a country, while the international digital divide refers to a gap between
1
The members of ASEAN consist of 10 countries: Brunei Darussalam, Cambodia, Indonesia, Laos, Malaysia,
Myanmar, the Philippines, Singapore, Thailand and Vietnam.
regions, countries, or continents. This study concentrates on the international digital
divide, in particular ASEAN countries.
Several studies have assessed ICT diffusion in an international dimension (e.g.,
Caselli and Coleman, 2001; Chinn and Fairlie, 2004, 2006; Guillen and Suarez, 2001,
2005; Hargittai, 1999; Quibria et al., 2003; Wong, 2002; Noh and Yoo, 2008). These
studies examine digital inequality as a function of macro indicators such as gross
domestic product per capita (GDP per capita), human capital and industrial
competitiveness. Many studies indicate differences in social development and
economic growth among developing and developed countries. For example, Africa
contains 14.1% of the world population (57 countries), yet it has only 2.3% of Internet
users while the world average is 15.7% (Fuchs and Horak, 2008). Other differences
exist in the physical infrastructure available to a country, the number of Internet
users, literacy, and costs of a local call; see for instance Cilan et al. (2008).
Concerning the impact of policy reform in ICT on performance, privatization and
competition and autonomous regulatory agency have also been considered as the
variables (Fink et al., 2002; Mariscal, 2005). Especially among Asian countries, the
state of privatization, competition and regulation has led to higher levels of main
line availability, service quality and labor productivity.
The Association of Southeast Asian Nations (ASEAN) was established on 8
August 1967 in Bangkok. As of 2006, the ASEAN region has a population of about
560 million, a total area of 4.5 million square kilometers, a combined gross domestic
product of almost US$ 1,100 billion, and total trade of about US$ 1,400 billion2. One
of the aims of the association is to accelerate economic growth, social progress and
cultural development in the region. This purpose shows a relationship between ICT
access and utilization, on the one hand, and socioeconomic order in the era of
globalization on the other hand. A gap in one aspect will create a gap in another
aspect, and vice versa. Therefore, the issue of ICT gaps all around the world
including in ASEAN countries needs to be handled carefully, because it can create
substantial impact on the socioeconomic and even political balance among the
ASEAN countries.
2
http://www.aseansec.org/64.htm
3
Although the total number of Internet users is continuously increasing in ASEAN
countries, there is no evidence to confirm that digital divide among these countries
can be neglected. However, if the digital divide exists and is very wide, it may
provide useful data for regulators and governments in order to take action to
develop and implement policies reducing the current digital divide among member
countries. In the end, the policy should accelerate economic growth, social progress
and cultural development in the region.
3. Telecommunication services in ASEAN countries
3.1 Overview of basic telecommunication service
This study concentrates on the main telecommunication services of fixed line
telephone, mobile phone and Internet. Among ASEAN countries, the distribution of
the fixed telephone, mobile phone and Internet users is uneven. The leading country
in all services is Singapore. Apart from Singapore, there are advanced countries in
some specific services which also have a higher rate than the world average, for
example Vietnam (32.65%) and Brunei (20.99%) in fixed telephone lines, and
Thailand (123.77%), Malaysia (87.86%), Brunei (78.92%) and Philippines (58.88%) in
mobile service. Moreover, Malaysia (55.67%), Brunei (40.64%), Thailand (21%) and
Vietnam (20.45%) also have a higher rate for Internet users than other countries
among ASEAN countries and the world average. In contrast, Myanmar, Cambodia
and Lao PDR (Laos) have the lowest penetration rate compared to other ASEAN
countries. Figures 1, 2 and 3 depict the evidence of digital divide across ASEAN
countries.
Figure 1 Here Figure 1: Fixed-line growth in ASEAN countries is different from that in most
developed countries. The latter‘s negative growth is not the case for Vietnam,
Brunei, Indonesia, Lao PDR, Myanmar and Cambodia. In particular, Vietnam has a
higher growth than the ASEAN average and world average in 2007, which are 13%
and 21.3%. One reason is the effect of country openness.
4
For ASEAN, it becomes interesting to evaluate the path of Vietnam development
in every aspect of telecommunication services. Further, Vietnam has the highest
compound annual growth rate (CAGR) for 2002-2007 in all telecommunication
services, as shown in Figures 2 and 3.
Figure 2 Here
Figure 3 Here
National GDP per capita is often used as a proxy to represent the average level
of personal income in each country. ASEAN countries differ in income distribution
as shown in Figure 4. There is no doubt why Singapore has the highest penetration
rate whereas Myanmar, Cambodia and Laos have the lowest penetration rate among
ASEAN countries. Mariscal (2005) argued that the countries with similar GDP do
not have the same teledensity. In this case, Mariscal recommends the researcher to
uses the Gini coefficient instead of GDP per capita, since it can explain the income
distribution better. Figure 4 suggests that higher GDP yields higher Internet
penetration.
Figure 4 Here
3.2 Current telecommunications market structure
A means to decrease the digital divide is through opening the sector to
competition. The effectiveness of telecommunication policy depends on the role of
the regulator to promote the competitiveness in the market, and also on the
government. For ASEAN, only five countries have full competition, i.e. Indonesia,
Malaysia, Philippines, Singapore and Vietnam. The remaining ASEAN countries
have partially competitive and monopoly structure. Moreover, only Brunei,
Malaysia, Philippines, Singapore and Thailand have an independent regulator. The
market environments are summarized in Table 1.
Table 1 Here
5
Many scholars have argued that the ways to bridge the digital divide in the
developing countries should follow the developed countries. A famous policy is to
close the digital divide within a decade by privatizing telecommunications markets
and increasing the foreign ownership in telecom operators, but it is not successful in
African countries (Fuchs and Horak, 2008).
However, the way to close the digital divide in the developing countries may be
direct intervention by their governments. Moreover, the independent regulators
should support the government policies on digital divide since it will close digital
gap indirectly, for example, by giving the incentive for the operators in order to do
their business in the rural areas. The benefit will occur with the rural population
who usually far from ICT services.
Different policies are applied in ASEAN countries to bridge the digital divide.
For example, in Thailand, the Ministry of Information Technology (MICT) has
adopted the Bridging Digital Divide Strategic Plan (2008-2010) to increase ICT
accessibility, promote research and development, increase Web accessibility, develop
an assistive technology industry, and increase access to assistive technology and
related technology3. Moreover, the National Electronics Computer and Technology
Centre, a specialized national center under the National Science and Technology
Development Agency, has developed wireless technology to allow remote areas
better communication4. The Malaysian government introduced a universal service
provision program – the ―Infodesa‖ and ―Internet Desa‖ programs that target rural
population and computer infrastructure for rural schools. Besides these programs,
the government encouraged the use of ICT through its ―PC Ownership Campaign‖5.
Further, the Ministry of Information and Communication of Vietnam will spend
VND1 trillion deploying public telecom services in rural and remote areas in 20086.
In addition, there is an increasingly dynamic software sector that is being supported
by the government‘s commitment to the sector in the form of setting up software
3
www.apectelwg.org/jsp/download.jsp?seq=5091&board_id=GPA_TEL_DOCUMENT&doc_seq=1
4
http://www.ntc.or.th/index.php?option=com_content&task=view&id=147&Itemid=73
5
http://dspace.wul.waseda.ac.jp/dspace/bitstream/2065/2949/3/Honbun-3972.pdf
6
http://english.vietnamnet.vn/tech/2008/07/793180/
6
parks and creating targeted tax incentives7. Singapore, which has highest
penetration in ICTs and still builds a bridge for the digital divide according to the
independent regulators, has committed $25 million as its contribution towards the
movement over the next three years. They will concentrate efforts on bridging the
digital fault-lines of income, language and mindsets. In most cases, they will
collaborate with various organizations, with particular emphasis on key population
segments – senior citizens, homemakers, workers and special interest groups8.
3.3 Digitization Index
To compare ASEAN countries, a digitization index is constructed to measure
ASEAN digitization. The formula is expressed in the following equation.
(1)
where
Dit is the digitization index for country i at time t;
xjt is the achieved penetration rate for xj devices at time t where (j=1, 2, 3 are
fixed line, cellular and Internet penetration rate);
X is the goal setting for the penetration rate in each service, which is based on
ITU (2005). For j=1, 2, 3 the goal setting will be 60, 100 and 85 respectively.
This study will utilize the methodology of compiling Digital Access Index (DAI)
which has been introduced by the International Telecommunication Union (ITU)
since 2003. The difference is that, while ITU calculates whole variables that are
presumed to have an effect on the accessibility, i.e. infrastructure, affordability
(pricing), knowledge (education), quality and usage, this study will only focus on
infrastructure (the access to fixed line and cellular mobile) and usage (the number of
Internet users per 100 inhabitants). Nevertheless, the benchmark value for each
7
Building Institutional Capacity In Asia, The Research Institute for Asia and the Pacific, Executive
Summary ―Vietnam ICT‖ Sept. 2001
8
http://www.ida.gov.sg/News%20and%20Events/20060926113231.aspx?getPagetype=21
7
variable will refer to what ITU sets as goal target.9 The index will be elaborated in
Appendix 1.
Figure 5 Here
Even though there is no clear evidence on how economic performance influences
the digitization index, Figure 5 represents a strong hypothetical relationship between
individual wealth that is measured by GDP per capita (PPP US$) and the digitization
index in each ASEAN country. Apart from Singapore, which has less GDP but
higher index than Brunei, as well as the comparison between Vietnam and
Indonesia, in most cases higher GDP per capita will promote digital access in a better
way.
4. Model and methodology
This study analyses the relation between economic growth, level of urbanization,
level of competition in ICTs services, market, independent regulator, and the level of
digitization through a panel data analysis. We use all data of ASEAN countries from
the ITU database during 1990-2005. Our model is adapted from Mariscal (2005) as
shown in equation (2):
Yit =Xit + Zi +
it
(2)
where
Yit
Xi
β
Zi
it
i
t
dependent variables, with a matrix size of (NT x i)
k-regressors of exogenous variables not including the constant
(NT x k)
parameters (k x 1)
heterogeneity or individual effect i which consists of constant i.
error term (NT x 1)
cross-section member
time
9
International Telecommunication Union (ITU) (2005), World Telecommunication Development Report:
Access Indicator for Telecommunication Society, Chapter 5.
8
In addition, the implemented equation regressed in this study derived from Mariscal
(2005) with different value of dependent variable can be presented as follows:
Digital = 0+ 1*GDPCAPit-1+ 2*URPOPit+ 3*DUMREGit+ 4*DUMOPit+
it
(3)
where
Digital
Index Value
GDPCAP
Lag of GDP per capita (purchasing power parity constant in
1995 US $)
URPOP
Proportion of urban to total population (
DUMREG
dummy variables = 1 for the existence of an independent
regulator; 0 otherwise
DUMOP
1 for monopoly, 0 otherwise10
it
)
error term (NT x 1)
All variables are in natural logarithms except for dummies. The expected impact
of all independent variables is positive.
However, the problem of endogeneity in the panel data is not addressed well by
the Mariscal study. Many studies clearly suggest that the performance of ICT
structure will directly influence the performance of the economy (OECD, 2003)11.
Kanamori (2004), Cette (2004), Smith (2002), Pitkowski (2003) and Vu (2004) also
provide different perspectives which point to a clear conclusion that, besides the fact
that economic growth will promote penetration rate and ICT progress, the opposite
explanation can be supported. Consequently, what Mariscal suggested did not
address the analysis of the potential endogeneity problem, particularly in terms of
the GDP variable.
The fact that the panel data model itself is constructed to solve the endogeneity
problem has been investigated in some research. Olley and Pakes (1996) investigate
the endogeneity problem in determining the production function in
telecommunication sector. He resumed that the endogeneity problem is solved by
10
With less stressing of analysis, this study also represent dummy variable of com2 for partial
competition and com3 for full competition (with the base dummy of monopoly).
11 OECD (2003), ―Information and Communication Technologies: ICT and Economic Growth
Evidence from OECD Countries, Industries and Firms‖, OECD Report.
9
disappearing the labor in production function while introducing the level
investment to act as instrumental variable.12 Griliches and Mairesse investigated
general aspect of endogeneity problem in production function.13 Griliches and
Mairesse (1998) explain the various sources of endogeneity in production function
and suggest the used of panel data in solving the problem. The main message of
their research is that the capital and labor in traditional Cobb-Douglass production
function are not exogenous thus need the instrument variable to solve the problem.
In this study, we estimate equation (2) by assuming that GDP is influenced by
the lag of it‘s value as an instrumental variable (instrument relevant) and also
assuming that the lag of GDP has no covariant with error term in equation 3
(instrument validity). We express these two requirements by stating the following
assumptions:
Cov(GDPi, t-2,
it)
=0,
(4)
Cov(GDPi, t-2, LGDPi, t-1) 0
(5)
Thus the instrumental variable of panel data will solve the first equation by
regressing the following equation (6):
GDPit-1 = 0+ 1*GDPCAPit-2 + vit
(6)
5. Results
Our result indicates that every variable has a relationship with the digitization
index as indicated in the following Table 2.
Table 2 Here
Table 2 represents the output that is derived from Appendix 2. This output
somewhat revises Mariscal (2005) by paying more attention to the endogeneity
problem, which is sourced from GDP. The general conclusion is that the endogeneity
12
Olley, S. and Pakes, A. (1996) ‗The dynamics of productivity in the telecommunications equipment
industry‘, Econometrica 64, 1263-1297.
13 Griliches Z. and J. Mairesse (1998). ‗Production functions: The Search for Identification,‘ in
Econometrics and Economic Theory in the Twentieth Century: The Ragnar Frisch Centennial
Symposium, 169-203. Cambridge University Press.
10
problem, when comparing Appendices 2 (without endogeneity) and 3 (with
endogeneity), shows higher magnitude as well as goodness of fit from the regression
(as shown by the value of R2). This finding is actually consistent with some research
which uses instrumental variable as the tools of analysis. For instance, it is also
suggested by Griliches that the IV will create lesser parameter in the production
function hence tends to reject the hypotheses of constant return to scale. It is
somewhat a direction that IV tries to avoid overestimation in determining the
parameter.
We can conclude that most of the coefficients are consistent with our hypothesis
as well as previous findings by Mariscal. Since the dependent variable is in natural
logarithms, each explanation in this study will refer to the growth of the digitization
index and not the level of the index. We can explain the detailed results from the
table as follows:
Lag of GDP is reported to be 0.891 which means that as the GDP per capita
increases by 1 per cent, the digitization index in ASEAN countries will increase by
0.89 per cent. This is a strong suggestion that the effect of GDP in generating
penetration rate for each ICT device is very large. Higher GDP per capita yields a
higher digitization index.
Log of urban population also plays an important role in driving the digitization
index. An increase of 1 per cent in urban population will increase the penetration
rate by 2.52 per cent. This means that, given the easier level of infrastructure
installment in urban region, the digitization index will be also stimulated.
The level of market competition, which is represented by the dummy of the
operator, leads to a finding of coherent result as well. As the market becomes more
competitive, the digitization index tends to increase. Taking the relative effect of the
dummy of DUMOP as (e -1)*100%, the relative effect is then 58 per cent. This means
that a country which has a monopoly market has 58 per cent lower growth in
digitization index.
11
In addition, role of the regulator tends to have a negative impact in promoting
the digitization index. The relative effect of the independent regulator is 13 per cent,
meaning that for a country which has an independent regulator, the digitization
index growth would be 13 per cent less. It has to taken into account that as the result
is not statistically significant.
Furthermore, appendix 2 also provides the comparative relative effect of dummy
of operator which also consistent with the earlier analysis. Taking dummy variables
that is derived from table 1, com2 is the dummy variable represents proxy of the
partial competition and com3 represents the proxy of full competition. The result is
very strong in encouraging the market to be competitive. The relative effect is 1.27
for com2 and 3.17 for com3 respectively. The intuition is that for a country which has
the partial competition, the digitization index is 1.27 times bigger while a full
competition brings the digitization index 3.18 times bigger compared to monopoly.
This finding is very close to the result of Mariscal (2005), except the fact the most
parameters resulted from this study are higher and the non-significant role of
independent regulator in ASEAN countries. However, the comparison between this
study and Mariscal (2005) is somewhat different because Mariscal (2005) only pays
attention to fixed line, whereas this study provides the composite index of all
devices. Nevertheless, it can be inferred that the effect of GDP is higher than in the
Mariscal (2005), suggesting that the impact of income (demand) is greater in ASEAN
than in Latin America which has the magnitude of GDP around 0.79 per cent. The
urban population has a similar result, where in the case of Latin America the
magnitude is about 2.41.
The impact of the independent regulator has the opposite sign. It may imply that
independent regulators in Latin America play stronger role on closing digital gap
than the regulator in ASEAN countries since the existence of autonomous regulator
in Latin America create 16 percent higher for promoting the penetration rate.
In addition, the dummy of privatization in Latin America is reported 0.15 which
then created the relative effect of 22.7 per cent. It means that for the country which
implements the privatization, penetration rate will be 22.7 per cent bigger. As it is
explained earlier, the dummy of competition in ASEAN has 58 per cent relative
12
effect hence assuming that privatization will create competition, we conclude that
the level of competition in ASEAN countries create the better magnitude in
promoting digitization index.
In summary, the market economy perspective as GDP clearly determines the
penetration or digitization index. There is an assurance that economic growth will
close the digital divide in ASEAN countries in terms of cellular, fixed line and
Internet. Even though the results disclose that more economic growth promotes the
telecommunications market by regulation, the digital divide in the international
dimension will be decreased. It does not mean that the digital divide on the domestic
level will disappear, since income inequality still exists among ASEAN countries.
6. Conclusion
This paper has examined the role of GDP per capita, the urban proportion of
population, the competition level of the telecommunications market, and the
independent regulator as a dummy variable, in explaining the digital divide for a
group of ASEAN countries.
ASEAN countries are used as a sample of the developing countries to investigate
the digital divide. The telecommunication services examined (fixed line, mobile
phone and Internet) in ASEAN countries are spread unequally. Only five countries
have full competition (i.e. Indonesia, Malaysia, Philippines, Singapore and Vietnam)
and independent regulators (i.e. Indonesia, Malaysia, Philippines, Singapore and
Thailand). This information is an important factor to explain and resolve the digital
divide. We introduce the digitization index for each country in order to present the
level of digitization in three main telecom services.
There are three major findings: firstly, income influences the digital divide as it
relates to higher use of fixed, mobile phones and the Internet. Secondly, the
regulator and the market have specific consequences. Market competition has
significant relationship with a digitization index in ASEAN countries. It means that
as the market become more competitive, the digitization index is also increase.
However, the role of the independent regulator is not statistically significant. This
result implies that the roles of the regulator are still needed in order to get rid of
digital gap. In addition, supported by the result of urban population variable, it
13
reveals that as more people live in the urban areas, the digitization index will
increase. Thus, digitization policy is also depends on how government implement
infrastructure sector in the road map of development program.
Furthermore, each country should be concerned that the digital divide will still
exist and will get even worse, not only on the international level but also within the
nation itself.
14
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17
Appendix 1
Creating the digitization Index in ASEAN countries
The index is constructed on the basis of three telecommunications services, i.e. fixed
line, mobile and Internet. The formula for calculating the index can be presented as follows:
(1)
where
Dit is the digitization index for country i at time t
xjt is the achieved penetration rate for xj devices at time t (where j=1, 2, 3 are
fixed line, cellular and Internet penetration rate)
X is the goal setting of penetration rate in each service, which is based on ITU
(2005).
The justification is based on ITU (2005), which suggests the benchmark standards for
each service as follows:
Services
Benchmark
Fixed Line
60
Cellular/Mobile
100
Internet user
85
Source: ITU (2003)
The variables are derived from the following data:
Fixed line
Main telephone lines (fixed line) per 100 inhabitants
Cellular/mobile
Mobile cellular subscribers per 100 inhabitants
Internet
Internet users per 100 inhabitants
Thus, supposing a country X has the figures for fixed line 35%, cellular 65% and
Internet 15% respectively, the index will be calculated as follows:
ITU
Sub Digitization
Country X
Attainment benchmark Index
Index
Fixed Line
35
60 0.583
Cellular/Mobile
65
100 0.650
Internet user
15
85 0.176 0.470=47%
18
The digitization index for ASEAN countries using the above formula can be
presented as follows.
Countries
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Indonesia
0.985
1.289
1.601
1.786
2.176
2.749
3.744
4.701
6.421
9.014
Thailand
4.095
5.049
5.975
6.064
6.881
8.182
11.713
14.246
21.103
24.562
Malaysia
10.931
12.624
14.808
17.275
20.872
26.788
31.661
35.420
38.472
43.842
Philippines
1.393
1.895
2.267
3.132
4.008
5.825
8.539
10.493
13.482
17.681
Singapore
26.517
30.772
37.299
41.987
49.576
62.392
66.465
72.016
75.378
79.181
Brunei
17.953
20.388
20.698
21.400
23.546
26.552
29.161
30.230
33.693
40.298
Lao P.D.R.
0.212
0.256
0.316
0.364
0.475
0.557
0.797
1.060
1.473
2.038
Myanmar
0.201
0.230
0.274
0.293
0.316
0.315
0.343
0.414
0.441
0.540
Vietnam
0.599
0.917
1.053
1.368
1.699
2.229
3.143
4.210
5.579
11.749
Cambodia
0.093
0.160
0.215
0.303
0.380
0.481
0.722
1.147
1.415
2.242
19
Appendix 2
Panel Data Regression with instrumental variable
. xtivreg ldigital (llaggdp=ll2gdp) lurpop com1 dregu
G2SLS random-effects IV regression
Group variable: id
Number of obs
Number of groups
=
=
130
10
R-sq:
Obs per group: min =
avg =
max =
13
13.0
13
within = 0.8412
between = 0.9175
overall = 0.8773
corr(u_i, X)
Wald chi2(4)
Prob > chi2
= 0 (assumed)
ldigital
Coef.
llaggdp
lurpop
com1
dregu
_cons
.8913038
2.519668
-.860237
-.1306183
-19.43552
.1710085
.4034708
.0988926
.1588512
1.196631
sigma_u
sigma_e
rho
.50246397
.3107191
.72337586
(fraction of variance due to u_i)
Instrumented:
Instruments:
Std. Err.
z
5.21
6.24
-8.70
-0.82
-16.24
P>|z|
0.000
0.000
0.000
0.411
0.000
=
=
554.53
0.0000
[95% Conf. Interval]
.5561332
1.72888
-1.054063
-.441961
-21.78088
1.226474
3.310457
-.6664111
.1807244
-17.09017
llaggdp
lurpop com1 dregu ll2gdp
. xtivreg ldigital (llaggdp=ll2gdp) lurpop com2 com3 dregu
G2SLS random-effects IV regression
Group variable: id
Number of obs
Number of groups
=
=
130
10
R-sq:
Obs per group: min =
avg =
max =
13
13.0
13
within = 0.8630
between = 0.9044
overall = 0.8750
corr(u_i, X)
Wald chi2(5)
Prob > chi2
= 0 (assumed)
ldigital
Coef.
llaggdp
lurpop
com2
com3
dregu
_cons
.7934321
2.475657
.8217928
1.43068
-.1915659
-19.39779
.1622253
.3761747
.0922257
.1574378
.1480422
1.104024
sigma_u
sigma_e
rho
.48968796
.29763523
.73023189
(fraction of variance due to u_i)
Instrumented:
Instruments:
Std. Err.
z
4.89
6.58
8.91
9.09
-1.29
-17.57
P>|z|
0.000
0.000
0.000
0.000
0.196
0.000
=
=
663.62
0.0000
[95% Conf. Interval]
.4754763
1.738369
.6410338
1.122107
-.4817232
-21.56164
1.111388
3.212946
1.002552
1.739252
.0985914
-17.23394
llaggdp
lurpop com2 com3 dregu ll2gdp
20
Appendix 3
Panel Data Regression without instrumental variable
. xtreg ldigital llaggdp lurpop com1 dregu
Random-effects GLS regression
Group variable: id
Number of obs
Number of groups
=
=
140
10
R-sq:
Obs per group: min =
avg =
max =
14
14.0
14
within = 0.8540
between = 0.9225
overall = 0.8810
Random effects u_i ~ Gaussian
corr(u_i, X)
= 0 (assumed)
Std. Err.
Wald chi2(4)
Prob > chi2
ldigital
Coef.
z
llaggdp
lurpop
com1
dregu
_cons
.9261893
2.552911
-.8923931
-.2188032
-19.81041
.1620085
.3662114
.0971738
.1497458
1.1278
sigma_u
sigma_e
rho
.51366841
.3249313
.71421175
(fraction of variance due to u_i)
5.72
6.97
-9.18
-1.46
-17.57
P>|z|
0.000
0.000
0.000
0.144
0.000
=
=
665.32
0.0000
[95% Conf. Interval]
.6086585
1.835149
-1.08285
-.5122996
-22.02086
1.24372
3.270672
-.7019359
.0746933
-17.59996
.
. xtreg ldigital llaggdp lurpop com2 com3 dregu
Random-effects GLS regression
Group variable: id
Number of obs
Number of groups
=
=
140
10
R-sq:
Obs per group: min =
avg =
max =
14
14.0
14
within = 0.8710
between = 0.9093
overall = 0.8781
Random effects u_i ~ Gaussian
corr(u_i, X)
= 0 (assumed)
Std. Err.
Wald chi2(5)
Prob > chi2
ldigital
Coef.
z
llaggdp
lurpop
com2
com3
dregu
_cons
.8081975
2.593517
.8517896
1.437416
-.312317
-19.93665
.1548647
.3446132
.091886
.1560604
.1425107
1.033348
sigma_u
sigma_e
rho
.49416781
.31246168
.7143869
(fraction of variance due to u_i)
5.22
7.53
9.27
9.21
-2.19
-19.29
P>|z|
0.000
0.000
0.000
0.000
0.028
0.000
=
=
770.57
0.0000
[95% Conf. Interval]
.5046682
1.918088
.6716963
1.131543
-.5916328
-21.96197
1.111727
3.268947
1.031883
1.743289
-.0330012
-17.91132
21
Figures and Tables
Source: ITU, 2008
Note: The dashed line is the ASEAN average
Figure 1 Fixed telephone lines per 100 inhabitants
Source: ITU, 2008
Note: Dashed line is the ASEAN average
Figure 2 Mobile subscribers per 100 inhabitants
22
Source: ITU, 2008
Note: The dashed line is the ASEAN average
Figure 3 Internet users per 100 inhabitants
Source: ITU, 2008
23
Figure 4 ASEAN GDP per capita and Internet penetration
Figure 5 GDP per Capita among ASEAN Countries
Table 1 Telecom Regulators and Market Structure in ASEAN Countries
Country
Brunei
Policy-making body
Minister of Communications
Darussalam
Regulatory body (year of
establishment)
Jabatan Telekom
Market structure in 2007
Partial competition
Authority for InfoCommunications Technology
Industry
Cambodia
Indonesia
Lao P.D.R.
Malaysia
Myanmar
Ministry of Posts and
Ministry of Posts and
Telecommunications
Telecommunications
Minister of
Communication and
Information Technology
Badan Regulasi
Ministry of Communication,
Ministry of Communication,
Post, Transport and
Post, Transport and
Construction
Construction
Ministry of Energy, Water
and Communications
Communications and
Ministry of
Ministry of Communications,
Communications, Posts and
Posts and Telegraphs
Partial competition
Full competition
Telekomunicasi Indonesia
Partial competition
Full competition
Multimedia Commission
Monopoly
Telegraphs
Philippines
National Telecommunications
Full competition
Commission
24
Singapore
Thailand
Vietnam
Ministry of
Communication,
Information and Technology
Ministry of Information
and Telecommunication
Technology
Infocomm Development
Ministry of Posts and
Ministry of Posts and
Telematics
Telematics
Full competition
Authority of Singapore
National Telecommunications
Partial competition
Commission
Full competition
Source: ITU (2008)
Table 2 Regression result
Coefficients
SD.
t-ratio
Constant
-19.44
1.196
0.000*
GDP t-1
0.891
0.171
0.000*
URPOP
2.519
0.403
0.000*
DUMOP
-0.869
0.098
0.000*
DUMREG
0.131
0.159
0.411
Variable
Note: *, ** significant at 1% and 5% respectively
25