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Chalmers University of Technology
Session 5 Panel DiscussionSession 5. Panel Discussion
The broadband economy : Moving along the macro and micro o g a o g t e ac o a d c o
measurement
Erik BohlinDivision of Technology and Society
Department of Technology Management and EconomicsDepartment of Technology Management and Economics
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Chalmers University of Technology
Purpose
• Measuring the impact of the broadband for the E E i f GDPEuropean Economy in terms of GDP
• Forecasting the impact of the broadband penetration rate and broadband speed to economic growth at macro level
• Distinguishing the impact of the broadband speed in micro level (case Sweden)( )
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Methodology and data
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Chalmers University of Technology
Purpose 1
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Q1 MultiplierC
XA
Q1. Multiplieranalysis
X
1. Defining the ICT sectors(OECD 2008)
Step of analysis
(OECD, 2008)2. Assuming that ICT sectors
correspond to the broadbandeconomy
3. Comparing the ICT and non ICT sectors multiplier
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Source : Compiled by Rohman (2011)
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Q.1. Multiplier analysisQ p y1995 2000
2005
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ConclusionQ1. Multiplier analysis• If the evaluation of broadband deployment is conducted based strictly on
the analysis of sector performance the opportunity cost of broadbandthe analysis of sector performance, the opportunity cost of broadband investment is large in the sense that investment in other sectors will obtain a greater economic impact.
• But, since ICT is a general purpose technology (see Bresnahan and Trajtenberg, 1995), the ICT sectors will have the potential for pervasive use in a wide range of sectors, and its technological dynamism enables the generalized productivity gains to be transferred to the rest of economy. Thus, broadband policy is an important agenda to be addressed.
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Purpose 2
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Q.2/3. Impact of penetration and speedD t d i tiData description
1. All OECD countries (33 countries)
2. Quarterly data from 2008Q1 –2010Q4
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Broadband penetration rate (%), OECD (2010)
30
35
40
20
25
5
10
15
0
5
ustra
lia
Aus
tria
elgi
umC
anad
aC
hile
epub
licnm
ark
Esto
nia
Finl
and
Fran
ceer
man
yG
reec
eH
unga
ryIc
elan
dIr
elan
dIs
rael
Italy
Japa
nK
orea
mbo
urg
Mex
ico
erla
nds
zeal
and
Nor
way
Pola
ndor
tuga
llo
vaki
alo
veni
aSp
ain
Swed
enze
rland
Turk
eyin
gdom
d St
ates
S OECD
Au A B C
Cze
ch R
eD
e E F Ge H I
Luxe
m MN
ethe
New
z N P S l Sl SSw
eitz T
Uni
ted
Ki
Uni
ted
Source : OECD
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Chalmers University of Technology
Speed of Broadband (kbps), OECD (2010)
20000
25000
15000
5000
10000 Download_Kbps
0
S OECDSource : OECD
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Impact of penetration and speedImpact of penetration and speedGroup variable: id Number of groups = 31Fixed-effects (within) regression Number of obs = 365
corr(u_i, Xb) = 0.8729 Prob > F = 0.0000 F(15,319) = 51.20
overall = 0.9773 max = 12 between = 0.9752 avg = 11.8R-sq: within = 0.7065 Obs per group: min = 8
llf .2282831 .0531393 4.30 0.000 .1237353 .332831 lcap .6300417 .0725769 8.68 0.000 .4872518 .7728316 lgdp Coef. Std. Err. t P>|t| [95% Conf. Interval]
( , )
1% increase in broadband penetration rate will increase 0.04% economic growth for OECD
d 6 16980 2 01 63 6 11 60 0 000 198 96 1 10116 dum5 -.1481497 .012258 -12.09 0.000 -.1722664 -.1240329 dum4 -.1030123 .0095679 -10.77 0.000 -.1218364 -.0841882 dum3 -.0599621 .0071012 -8.44 0.000 -.0739332 -.0459911 dum2 -.0289151 .0048139 -6.01 0.000 -.0383862 -.019444 lspeed .0162494 .0033997 4.78 0.000 .0095607 .0229381 prate .0432579 .0767012 0.56 0.573 -.1076462 .194162
0 0 % eco o c g o o O Ccountries
1% increase in speed level corresponds to 0.02% increase in
d 12 2455179 0267286 9 19 0 000 2981045 1929312 dum11 -.2338624 .0248496 -9.41 0.000 -.2827522 -.1849725 dum10 -.221911 .0229717 -9.66 0.000 -.2671062 -.1767159 dum9 -.2120087 .0210896 -10.05 0.000 -.2535009 -.1705165 dum8 -.1986156 .019 -10.45 0.000 -.2359967 -.1612345 dum7 -.1837087 .0169488 -10.84 0.000 -.2170543 -.150363 dum6 -.1698042 .0146346 -11.60 0.000 -.1985967 -.1410116
pGDP growth, et ceteris paribus.
For comparison 1% mobile penetration rate for developing
rho .99959897 (fraction of variance due to u_i) sigma_e .01467352 sigma_u .73258742 _cons .383476 .8899209 0.43 0.667 -1.36738 2.134332 dum12 -.2455179 .0267286 -9.19 0.000 -.2981045 -.1929312
p p gcountries in Waverman study contributes to 0.075% GDP growth.
F test that all u_i=0: F(30, 319) = 576.44 Prob > F = 0.0000
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ConclusionQ2. Impact to growth• The broadband penetration rate contributed to growth of OECD
countries around 0 04%countries around 0.04%.• Speed level contributes to growth around 0.016%
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Purpose 3
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Q.3. Speed to productivity“Broadband Strategy for Sweden (2009) ; by 2020 ninety perBroadband Strategy for Sweden (2009) ; by 2020, ninety per cent of households and businesses in Sweden should have access to broadband at a rate of at least 100 Mbps, and that all households and b h ld h d l blbusinesses should have good opportunities to use electronic public services and other services via broadband”– Why should we spend a lot of money for broadband sector?y p y– Are there any evidence that the economy is growing thanks to the
broadband development?i b i b ff?– Is society becoming better‐off?
– Is broadband speed really important?– How to evaluate such the impacts?How to evaluate such the impacts?
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• Critiques towards the GDP
GDP h i thGDP emphasizes more on the achievement of material aspects, less on non‐income related indicator (Kuznets, 1941; Galbraith 1958; Samuelsson1941; Galbraith, 1958; Samuelsson, 1961; Mishan, 1967; Nordhaus and Tobin, 1972; Hueting, 1974; Hirsch, 1976; Daly 1977; Dasgupta 2000)1976; Daly, 1977; Dasgupta, 2000)
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• Recent studies on income and quality of life and happinessquality of life and happiness
Easterlin Paradox (1974) holds for many countries TRUE, that within the countries wealthier people are , on average, happier than poor ones.
BUT across countries very little ifBUT, across countries , very little, if any, relationship between increases in per capita income and average happiness (Graham, 2010, p.12)
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Broadbandaccess and
usage
Allison and Stewart (1974); Levin and
h
Quality
usageDasgupta, 1999; Landefeld and Fraumeni 2000,
Stephen 1991, Grimsrud, and Stein Gunnes, 2003.
P d ti it
Qualityof lifeCostanza et al, 2006.
Productivity
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Source : Costanxa, et al (2008)
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Order probit ModelOrder probit Model
Source : ADL (2011)
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Source : Chalmers for NTT Docomo (2011)
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Speed of broadband and productivity*C t
likelihoodComments
How to read this?A >20 MB/s subscriber has the likelihood for:
having the lowest probability for being “a medium level productive” person.p phaving the lowest probability for being “a lower level productive” person.ha ing the highest probabilit forhaving the highest probability for being “a high level productive” person.
NOTE:
* The investigation on income does not show any statistical evidences that there is a differences between income level due to the broadband. Likewise the type of broadband (DSL, fiber, dial up) also does not have any statistical impact . Hence the “Sweden Broadband strategy of Broadband (2009) that emphasizes more on the speed factor becomes a more relevant unit of analysis.
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Speed and productivity: Large cities* vsSpeed and productivity: Large cities* vs. Small cities
likelihoodC tComments
The impact of broadband policy varies between region.Broadband policy (through increasing speed) has clearly been benefitted by large cities :
increased the productivity level p yin large cities more than small cities.Decrease the medium productivity users in large citiesproductivity users in large cities compared to small cities
* Stockholm. Gothenburg. Malmo
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Speed of broadband andlikelihood Speed of broadband and productivity based on
incomeincomelikelihood
likelihood
Comments
The impact of broadband policy varies between income. Clearly higher income users (who has higher willingness to pay) can afford higher broadband speed enabling them for higher productivity gain
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