Communications - Mission Viejo City Council

ATS
Communications
Managing the Wireless Net
unicipal Agencies to Monetize
The 5 Reasons For
1.
2.
3.
4.
5.
To avoid the risk of lease termination
To fund capital improvements
To fund investment opportunities
To reduce debt
To obtain capital for operating costs
Risk Factors
Mergers AT&T/Cingular and Sprint/Nextel
New Technology WiFIJWiMax, DAS networks, Wireless mesh, Femtocells
Changes in Government Regulation
Operating Efficiency —Decommissioning of an old site may cost less than to upgrade to a new
site.
e) Rent reduction currently there are two companies that are actively working for the carriers
to reduce lease rents
a)
b)
c)
d)
—
—
—
CALIFORNIA OFFICE
22264 Lambert St., Suite 402, Lake Forest, CA 92630, Phone: (949) 305-7848 Fax: (949) 768-6984
Website www.atscomm.com + email: [email protected]
Table of Contents
Supporting Reference for Risk Factors
1.
ergers
2. New Technology
3. Changes in Government Regulations
Supporting Reference for Monetization
4. To Fund Investment Opportunities
5. To Fund Capital Improvements
Managing the Wireless Net
Supporting References for Risk Factors
Mergers
Consolidation is one of the greatest threats to continuing a landlord’s lease income. Mergers have effects
on the companies that join forces, some mergers happen smoothly and the newly acquired company fits
very nicely in the portfolio, while other companies have a hard time getting back on their feet after a large
number of internal changes occur. For example, many assets are acquired during a merger that add to
operating costs of expenses. As you will read in the articles below, “cell site leases represent the
first or second largest expense for wireless carriers internationally”. When two wireless
carriers merge many times their sites and coverage areas overlap, the high cost of operation incentivizes
the carrier to get the unnecessary sites off air in order to reduce their expenses.
“American Tower said an AT&T Wireless- Cingular merger would mean overlap on 350 of
its sites, resulting in an overlap of up to $9 million in annual revenue...”
“SpectraSite said that in a “worst-case churn scenario,” it would lose 450 leases, or 3 percent
of its portfolio.., due to an AT&T Wireless -Cingular merger.”
Source: RCR Wireless News, January 26, 2004
Why Carriers are Retaining Real Estate Asset Managers
“It’s time for American corporations to take a closer look at their real estate portfolios.”
Commercial Investment Real Estate
A reevaluation of the way corporations handle their real estate is especially important in
light of the anticipated growth in buying and selling, says a recent Coldwell Banker
Commercial/National Real Estate Investor corporate real estate survey reported in CIRE.
This forecast is particularly significant to the wireless communications industry. With
nearly 184,000 cell sites nationwide (which reflects a growth trend of 4.5% year over
year since 1985), wireless carriers have officially acknowledged the magnitude of their
real estate portfolios. In fact, cell site leases represent the first or second largest
exnense for wireless carriers internationally. Managing these costs has become a
number-one priority as carriers navigate their forward vlannin and the new technology
that will nrofoundlv impact the growth of their cell site networks.
A by-product of the wireless industry’s growth strategy since its inception, carriers’ real
estate portfolios have been a largely overlooked asset for 20 years. Now, the industry is
taking steps to manage their commercial real estate interests with the same savvy
indicative of corporations focused on maximizing their investments.
But commercial real estate is a complex business and building owners for decades have
tapped industry experts to represent their interests. Professional landlords or
partnerships that own small office buildings often employ their own brokerage listing
agents who monitor the competition’s lease terms and conditions, while large office
complexes owned by institutional investors employ professional property and asset
managers.
An estimated three to ten percent of brokers focus exclusively on representing tenants,
a more recent industry segmentation that equalizes access to critical market
information. Says CIRE magazine, most Fortune 1000 corporations utilize tenant rep
services.
“When tenants do not go to the marketplace to fully determine whether the renewal
terms and conditions are competitive, they almost always lose. Knowledgeable landlords
keep pace with the marketplace and fully appreciate the financial rewards to the
property owner when tenants enter lease renewal negotiations without a broker and
without bringing alternative locations into competitive play.”
This commercial real estate management strategy is overtaking the wireless industry
and a new niche has developed for the administration and evaluation of cell site leases
real estate asset managers for the wireless industry. With their sprawling nationwide
network that functions in dozens of markets simultaneously, carriers require yet
another level of specialized tenant representation.
—
© Copyright 2006
http:I/www.md7.comlrgp_articles.html
RCRXVi1e1ess News
Sprint Nextel moves into junk status, gets new CFO
By Kristen Beckman
Story posted: May 2, 2008 1:28 pm EDT
-
Standard & Poor’s Ratings Services lowered its corporate credit and senior unsecured ratings on Sprint Nextel Corp.
to BB from BBB- and removed the company’s ratings from CreditWatch with negative implications. The downgrade
moves Sprint Nextel out of the investment-grade category and into junk status.
“The downgrade is based on our assessment that Sprint Nextel’s business risk profile is no longer supportive of an
investment-grade rating given its deteriorating operating performance and lack of visibility in the wireless business,
along with increased financial leverage due largely to declining EBITDA,” said Standard & Poor’s credit analyst Allyn
Arden
The ratings firm placed Sprint Nextel on CreditWatch in February after the company warned of steep postpaid
subscriber losses. S&P said it expects Sprint Nextel’s operating and financial results to remain under pressure over
the next couple of years.
The downgrade coincided with the arrival of a new CFO for Sprint Nextel. Robert H. Brust was named its new CFO
effective immediately. Brust previously was CFO at Eastman Kodak Co. and CFO of Unisys Corp. He also spent 31
years with General Electric.
William Arendt, senior VP and controller, has been serving as interim CFO since Paul Saleh and two other executives
were ousted earlier this year in a management shakeup.
The company is expected to report first-quarter results May 12.
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New Technology
No one really knows what’s going to be happening 10 to 20 years from now. We have seen leaps in
technology within the past 20 years, which is when the Internet came into play. Going back vely few
would have been able to conceive of cell phones that would run our personal or business activities.
Recently, due primarily to cost, there have been new advances in new wireless infrastructure deployment.
Femtocells and open DAS networks will affect traditional macro-cell deployment. We have also seen
other technologies that have become obsolete due to new technological developments, such as analog and
frequency spectrums that have been re-allocated to the wireless industry (formerly broadcast television).
The development and deployment of signal combining technologies, which permit one antenna to sen/ice
multiple frequencies and, thereby, multiple customers, may reduce the need for our antenna space. In
addition, other technologies which may be developed and emerge may serve as substitutes and
alternatives to leasing which might otherwise be anticipated or expected on our sites had such
technologies not existed.
Source: RCR Wireless News, January 26, 2004
NE OR
‘RID
This story appeared on Network World at
http://www.networkworld.com/su pp/2006/ndc6/102306-ndc-wireless-mesh.html
Wireless mesh or WIMAX: Which MAN
technology is best?
Enterprises give wireless mesh a whirl
--
and they like the ride.
By Joanne Cummings, Network World, 10/23/2006
Not too long ago, enterprises had limited options when it came to making a wireless network part of the New Data
Center plan. In the local area, the choice was Wi-Fl 802.llb, g or a. In the larger campus or metropolitan area,
people anticipated widespread WIMAX deployments (aka 802.16d or 802.16e) because of the promise of
broadband-level bandwidth, improved flexibility and tight security.
-
Not so anymore. These days, metropolitan wireless mesh networks threaten to leave WIMAX at the gate. The
reasons are numerous: They follow the traditional Wi-Fi standard, so any Wi-Fl-enabled client can work with them,
users and analysts say. Plus, they don’t require wire runs to every node, they are designed to be self-organizing
and -healing, and they scale on the fly. If you need more capacity, add another node, and you’ve got it.
In addition, mesh gear is available from Cisco, Firetide, Strix Systems, Tropos Networks and others. WIMAX
products are not nearly as prevalent. Fixed WiMAX equipment is just coming to market, and mobile WIMAX gear is
not expected to arrive much before late 2007.
“I looked at WiMAX in the public safety arena.... It worked great in a stationary environment, especially for video
cameras, but once I tried it in a mobile environment, it didn’t work,” says Peter Collins, dO for the city of Austin,
Texas, which recently deployed a series of wireless meshes using Cisco Aironet 1500 series gear.
That’s not to say mesh is always the best choice. For most companies considering deploying in-building wireless
networks, the cost equation indicates traditional Wi-Fi is still the way to go if the wire is there and available for
the Wi-Fi access points. But when the infrastructure has not been wired, and running wire would be prohibitively
difficult or expensive, mesh makes sense. “Mesh works well, and we’re starting to see it in warehouses, loading
docks, logistics, transportation, those kinds of applications. We also see it in large, temporary setups, like outdoor
concert venues,” says Craig Mathias, principal at the Farpoint Group.
-
For example, North American Midway Entertainment, a large amusement company in Los Angeles, sets up Firetide
wireless mesh networks to support transaction processing for its fairs and carnivals. Firetide’s HotPort mesh
network gear provides reliable, robust connectivity in a challenging environment, says John Gallant, North
American Midway’s CIO.
“For us, it’s almost impossible to use a conventional wireless network with point-to-point runs and wireless access
points,” he says. “The Firetide mesh gives us a multipoint setup. We can actually go around corners. If the
connection’s strongest point is straight in front of you, but every three minutes a huge mechanical device like a
ride goes past it for a minute, that creates a lot of delay and latency. With the Firetide gear, if one node becomes
obstructed or the network noise level gets too high, the node will automatically route the signal to the next best
possible route,” he adds.
In mesh networks, users deploy multiple mesh nodes throughout an area, but, unlike in traditional Wi-Fi, only one
node has to be connected to a wired network. When a mesh node receives a frame from a Wi-Fi client, it relays the
frame from node to node, until the frame reaches the wired node. Each node has a standard Wi-Fi interface, to
communicate with clients, and a radio-based backbone link that relays the message across the network.
Because the mesh doesn’t require wire runs to every node, Gallant can use it in the large spaces he needs to cover.
For example, North American Midway recently ran the Canadian National Exhibition in Toronto, where the
fairgrounds blanketed about one square mile. Gallant implemented a mesh comprising 42 nodes and access points.
It supported 240 users.
Mesh has its downsides, he says, but those are common to all wireless networks susceptibility to lightning,
interference from other devices, power outages. Most problematic is having to plug nodes into standard, 110-volt
household receptacles. “They have battery backups in case you lose power, but you do have to plug them in. That’s
probably the biggest challenge,” Gallant says. Still, reliability outweighs the downsides: “Mesh works great,” he
says.
-
Proprietary routing standards
A bigger downside for some users considering mesh networks is the proprietary nature of each vendor’s routing
scheme. That means once you make the decision to buy, you’re locked into that vendor. Although the IEEE is
working on a standard routing protocol, called 802.lls, it doesn’t expect to finish that work until late 2007. Even
then the standard would provide for fairly vanilla multivendor mesh implementations.
This gives some users pause. “Wireless mesh is a little bit out there,” says Elliot Zeltzer, global manager for
telecommunications
esh vs. i AX
security at General Motors
in Detroit. “We can’t afford
any
downtime.
We’re
Wireless mesh (Wi-Fl)
WiMAX
more
looking
for
standardized
established,
Bandwidth
11M or 54Mbps
70M
100Mbps
technology.”
.
.
.
.
-
to
-
Coverage
No limit
No limit
GM is in the middle of a
traditional Wi-Fi rollout
Availability
Nowt
By year-end’2OO
across its campus, primarily
because the wiring is there
and it’s a more proven technology, Zeltzer says. If he were to look at a more metropolitan-level rollout, he says
he’d favor WIMAX.
.
-
-
“Not speaking specifically to GM, I believe WiMAX has the highest value,” Zeltzer says. “It offers huge amounts of
bandwidth for fairly low cost and in the end, it could provide total local-carrier bypass,” he says. Plus, Zeltzer says,
he is leery of mesh security.
Wireless mesh users counter such arguments by saying mesh offers enough coverage, bandwidth and security for
today’s applications. “Everything’s misleading in the world of wireless, and your rate depends on a lot of factors,
like distance and interference,” Austin’s Collins says. “With W1MAX, your rate decreases the farther away you are
from the transmitter and receiver. It’s all relative. I have a consistent throughput on wireless mesh, and that’s
more important.”
As for security, Farpoint’s Mathias, as well as current users, say it’s not an issue: “Basic wireless LAN security is
really improved to the point where it’s very good,”he says. “If you can secure a wired network, you can secure a
wireless network.”
In the end, the proof is in the deployments. Several cities have committed to wireless mesh rollouts, and vendors
seem to be ticking off new users weekly. As Mathias says: “The demand. is a global phenomenon.”
.
.
Cummings is afreelance writer in North Andover, Mass. She can be reached [email protected].
All contents copyright 1995-2008 Network World, Inc. http://www.networkworld.com
Femtocells: Spectrum Efficiency Improved
An article by Manish Singh, VP Product Line Management, Continuous Computing
From the May 12, 2008 edition of Wireless Design & Development
Since wireless spectrum is at a premium, it is advantageous
for wireless carriers to use the spectrum efficiently in both
outdoor and indoor environments.
One of the most limited resources in telecom is wireless spectrum; therefore, it is not surprising
that carriers are paying premium licensing fees for spectrum acquisition. For example, the recent
700 Mhz spectrum auction in the U.S. had an aggregate bid value of $19.6 billion. Since
acquisition of wireless spectrum is limited, it is advantageous for wireless carriers to use the
spectrum efficiently in both outdoor and indoor enviromnents.
From a radio frequency (RF) propagation perspective, buildings and walls have never been
friends to a radio signal. Physical structures cause RF signal attenuation because of reflection,
diffraction, scattering, and multi-path signal fading, all resulting in poor radio signal reception in
an indoor environment. In some cases, virtual
dead spots can occur inside buildings, even
3G Fomtocoll Solution
though there is great coverage outside. Walls
can attenuate signals by 10 to 20 dB depending
•Oflloadst omost
• Providos cc coverage ndoors
on the type of construction. At the same time,
power-hungry
• Low-power and soit-contigu ng to
3G users trom the
m nm}zo bntororonco
studies have shown that an average consumer
macroco to home
• Condensed mob o network (RAN)
spends 50 to 60% of his or her time in an indoor
base so uflon
• Leverages customo broadband to
Ca ry traffic to operators network s rig
environment, and that 70% of wireless calls
ub SIP and UMA
originate and terminate indoors. All things j
considered, this poses the question: Are wireless
carriers using their spectrum efficiently in
indoor environments?
Market Drivers for Femtocells
From an engineering standpoint, wireless
system spectral efficiency is measured in
bps/Hz/cell. From a carrier standpoint, this
Macro Network
Standard
3G localized
translates into the number of simultaneous
Base Station
air Interface
3G mobile phone
subscribers that can be supported in one cell site
(i.e., network capacity). From a consumer
standpoint, this all translates into quality of
voice and video, dropped calls, and high-speed packet access (HSPA) data rates. Poor indoor RF
signal penetration has adverse effects on the link spectral efficiency, which has a direct impact
on system spectral efficiency. Simply put, carriers lose revenue as mobile minutes are lost to
landline minutes when consumers experience dropped calls, poor quality of voice, and lower
data rates when indoors. When considered in aggregate, one can easily see the underlying market
drivers for femtocells.
What is Femtocell?
A femtocell is essentially a small wireless base station that resides in the consumer’s home or
office. Femtocells transmit at very low power, yet create almost ideal indoor radio conditions.
For backhaul, femtocells use an IP broadband connection (e.g., fiberfDSL/cable). The very walls
which are a radio signal’s adversary actually become their friend as they attenuate RF signal
propagation out of the home from the femtocell, thereby minimizing radio interference with an
existing macro-cellular network or another nearby femtocell. In fact, femtocells not only provide
excellent indoor coverage, but also, by virtue of creating a small indoor cell-site, they free up
capacity in the macro-cellular network. In other words, indoor subscribers’ cell phone traffic is
parked on a femtocell as opposed to on a macrocell. Femtocells eliminate the need for dual-mode
handsets as virtually any existing wireless handset should seamlessly work with a femtocell. And
last but not least, one femtocell can support four to six simultaneous voice calls, which means
that each member of a family of four can talk simultaneously as if they had four virtual landlines
for the price of one.
Why Has it Taken so Long?
So, if femtocells enhance coverage, increase network capacity, and improve spectral efficiency,
then why have they not been widely deployed before now? In fact, the femtocell is not a new
idea. It has been around for a long time, yet the catalyst for driving a commercially viable rollout
for femtocells has only fallen into place very recently. In the earlier days, backhaul costs were a
barrier for mass deployment, but today the wide proliferation of IP broadband connections (fiber,
DSL, or cable) means that the backhaul infrastructure already exists. In the U.S. alone, more than
52% of homes now have broadband connections, and the figure is growing. Femtocells leverage
a consumer’s IP broadband connection to backhaul voice, video, SMS, and data traffic from
millions of homes into an existing wireless core network.
Furthermore, thanks to Moore’s Law
which states that silicon performance doubles every 18
we are now at the point where integrated custom silicon parts for femtocells are
months
widely available. One silicon part, integrating the required compute, digital signal processing,
encryption and various other key features for a small wireless base station, is key to drive the bill
of materials (BOM) cost down for a commercially viable femtocell deployment. Lastly, with
more than 2.5 billion wireless subscribers worldwide, the economy of scale to justify femtocell
deployment is finally in place.
—
—
Femtocell in Enterprise
The business case for femtocell rollout is straightforward and can be summarized in three key
parts. First, consumers today are paying for landline connections. These landline minutes and
Average Revenue Per User (ARPU) are up for grabs due to competition, but only if wireless
carriers can provide reliable indoor coverage. In the U.S., the number of cell phone-only homes
exceeded the number of landline-only homes in 2007, and household cell phone spending has
exceeded landline spending. With femtocells, carriers can provide a robust wireless alternative to
landlines and accelerate this social phenomenon of consumers replacing their landlines.
Second, the demand for mobile broadband is on the rise, as fueled by the YouTubes and
Facebooks of the world. In the first half of 2007, data revenue in the U.S. alone was 15.5% of all
wireless revenue. For AT&T, data ARPU now constitutes 18.4% of their total ARPU, and
Vodafone’s data revenue grew 49% over the past year. Femtocells add network capacity and
make it possible to deliver 7.2 Mb/s and 14.4 Mb/s HSDPA data rates to consumers in indoor
thereby fulfilling market demand for wireless broadband access.
environments
—
Thirdly, femtocells deliver capital and operational expenditure savings. Adding a new macro
base station costs roughly $600,000, depending on site geography, technology, supplier cost
model, etc. Add to this approximately $15,000 per month for operation costs, such as leased
lines, electricity, and cooling, etc. For the cost of one macrocell site, a network operator could
potentially cover 6,000 homes, assuming a cost of $150 femtocell price per unit and operator
subsidies of $100 per unit. For $600,000, assuming 7.2 Mb/s HSDPA rate, one macrocell site
would add an aggregated 7.2 Mb/s bandwidth capacity, as opposed to 43 Gb/s with 6,000
especially if revenue is accumulated on a usage basis.
femtocells. This is a huge difference
—
Carrier Benefits
The carriers that roll out femtocells first will benefit from reduced churn as subscribers will not
struggle with dropped calls. The quality of the consumer’s experience will improve significantly
as clear voice and HSPA data rates are delivered. Most importantly, the carriers that initiate the
charge will benefit from “reverse-churn” as femtocells enable home-zone “family tariff plans”
which will entice all family members to switch to one carrier in order to take advantage of
packaged bulk service benefits.
Second, the demand for mobile broadband is on the rise, as fueled by the YouTubes and
Facebooks of the world. In the first half of 2007, data revenue in the U.S. alone was 15.5% of all
wireless revenue. For AT&T, data ARPU now constitutes 18.4% of their total ARPU, and
Vodafone’s data revenue grew 49% over the past year. Femtocells add network capacity and
make it possible to deliver 7.2 Mb/s and 14.4 Mb/s HSDPA data rates to consumers in indoor
thereby fulfilling market demand for wireless broadband access.
environments
—
Challenges of Femtocell Rollout
While the economics for femtocells are compelling, there are many technical challenges that
need to be addressed. Utilizing femtocell means that a wireless base station essentially moves
into the consumer’s home, and along with that comes the challenge of integrating millions of
femtocells with an existing 3G wireless core infrastructure. Many different architecture options,
like Tunneled lub, Tunneled hi, and SIP/IMS are under consideration, and much more work is
needed in order to reduce these choices to only one or two.
Femtocells also bring up the challenge of managing RF interference. RF interference between
femto-femto and femto-macro can create virtual dead spots as well as the potential of degrading
the performance of an existing carrier’s macro network. Traditional RF planning tools used to
plan macro cellular networks will not work for femtocell deployments. Instead, femtocells will
need the ability to scan the dynamically changing RF environment and configure themselves
with frequency bands, scrambling codes and transmit power levels.
Femtocells take security challenges to another level. Since the traffic from femtocells can be
carried over a public IP network, the traffic needs to be encrypted to avoid eavesdropping.
Potential solutions include establishing IPSec tunnels, SRTP, or TLS for securing the traffic.
Carriers also need to secure their existing core network infrastructure from any Denial of Service
OS) attacks
hence the need for a Security Gateway between femtocells and the core
network.
—
Quality of Service (QoS) is another challenge that needs to be addressed. The best effort of an IP
network is just not good enough to carry real-time voice which might be vying for bandwidth on
a shared IP link with peer-to-peer (P2P) and other data traffic. In certain deployment scenarios,
the DSL uplink bandwidth can be as low as 200 Kb/s and pack four simultaneous voice calls. In
this environment, not losing a consumer’s VPN connection on his or her PC will be difficult. As
a result, classifying, marking, and prioritizing [P packets based on class of service becomes a key
requirement. Potential QoS solutions include static Diffserv-based solutions as well as Signaled
QoS solutions based on RSVP or SIP.
TR-069 Standard
Management of millions of femtocells requires unique solutions. Traditional Element
Management Systems (EMS) that are used to manage NodeBs and Radio Network Controllers
(RNCs) in today’s 3G networks simply do not scale for femtocells. The DSL Forum already has
developed the TR-069 standard for remote customer premise equipment (CPE) device
management. This standard needs to be further extended to support femtocells’ data models and
deployment models. With TR-069, carriers can re-use their existing CPE device management
infrastructure by just extending it to include femtocells. Likewise, to support E9 11 regulations,
carriers will need the exact location information of femtocells to effectively route emergency
calls to the nearest public safety answering point (PSAP). Femtocell location information could
potentially be obtained using global positioning system (GPS) technology; however, GPS itself
does not function very well in indoor environments. Another alternative could be mapping a
static IP address to a femtocell’s physical location. All of these challenges will need to be
addressed before widespread femtocell deployment becomes a reality.
What Lies Ahead?
Looking further into the future, femtocells will be more than just access points. In 2008, the
market will see more converged CPE devices with femtocell functionality embedded into a
residential gateway
an IPTV set top box or a cable/DSL modem. For example, Netgear has
already announced the availability of a Residential Gateway incorporating femtocell technology.
These converged CPE devices will enable carriers to deploy true quad-play services
voice,
—
—
all out of one box. And let’s not forget that 30 Long Term
video, data, and mobility
Evolution (LTE), or “4G,” standardization work is already being influenced architecturally as
eNodeBs are also expected to be deployed as home base stations, i.e., Home eNodeBs (HeNB).
Carriers that have already secured CPE real estate in consumers’ homes will continue to have an
advantage long into the next decade.
—
Conclusion
Carriers and consumers will both benefit by femtocell rollouts. Carriers will accelerate return on
investment (ROl) on spectrum acquisition by efficiently using this scarce and costly resource in
indoor environments, while at the same time monetizing mobile minutes substituting for landline
minutes; thereby, creating pull for new customer acquisitions through family tariff plans and
aggressively growing the data ARPU. Consumers will benefit as they jettison their landlines and
become accustomed to their existing cell phones working seamlessly with femtocells while
enjoying better coverage, HSPA data rates, zero dropped calls and multiple virtual connections.
And this is all just the beginning. In the future, femtocells are poised to play a key role in
delivering converged services via IP Multimedia Subsystem (IMS)
a topic for another day and
another article.
—
About The Author
Manish Singh is vice president, product line management at Continuous Computing. Previously
he served as vice president of field engineering and vice president of engineering. Mr. Singh is
an experienced engineering leader who brings 14 years of experience in telecommunications
product design and development. Prior to Continuous Computing, Mr. Singh held various
engineering management and architect positions at Intel Corporation, Trillium Digital Systems,
and C-DOT (Center for Development of Telematics). Mr. Singh holds the patent as a sole
inventor of “Configurable Cache” memory system. Apart from broad telecom domain
knowledge, Mr. Singh brings specialized expertise in the wireless and VoIP telecom technology
areas. In 1998, he successfully led the development of 20 MSC at C-DOT and since has led
various VoIP and 3G/IMS wireless product development. Mr. Singh received a B.S. degree in
electronics and telecommunication from Shri GSlnstitute of Technology & Science, Indore and a
M.S. degree in computer science from India Institute of Science, Bangalore.
RCRWf l-ss News
Report: AT&T Mobility to sell $100 femtocells
Carrier Inked contract with femto vendor lp.access
By Mike Dano
Story posted: April 24, 2008 1:21 pm EDT
-
According to a report from research and banking firm ThinkPanmure, AT&T Mobility plans to sell up to 7 million
femtocells from ip.access Ltd., a picocell and femtocell infrastructure vendor based in Cambridge, United Kingdom.
According to ThinkPanmure, AT&T signed a contract with the firm for up to $500 million in femtocells over the course
of five years, and will sell the devices for as little as $100 each.
A spokeswoman for AT&T did not comment on the report specifically; however, she said the nation’s largest carrier is
examining the potential benefits of femtocells through lab tests, and plans to conduct a femtocell trial “later this year.”
Representatives from ip.access were not immediately available to comment on ThinkPanmure’s report.
Femtocell technology has caused a notable stir in the wireless industry. FemtoceUs essentially are tiny base stations
that can be sold to individual phone users. Femtocells can be installed in homes or offices, and transmit cellphone
traffic through a high-speed Internet connection. Femtocells work much like VV1-Fi hotspots, except they power
transmissions over a wireless carrier’s licensed spectrum.
Thus, femtocells raise a number of potentially troublesome issues for users and carriers, including the management
of radio interference between a cell tower and a femtocell; radio interference between different femtocells, such as in
an apartment building; and roaming between femtocells.
Nonetheless, femtocells could solve one of the biggest headaches wireless carriers face: indoor coverage. The
installation of a femtocell in a home or office would eliminate the need for a carrier to cover that same space, and
offloads the cost of the equipment onto the user.
And a number of carriers have embraced the technology. Sprint Nextel Corp. was the first out of the femtocell gate in
the United States; the carrier in September introduced its Airave femtocell from Samsung Electronics Co. Ltd. for $50
along with a monthly fee. The product allows users to make unlimited calls over their femtocell connection.
When the Airave launched, it was only available in Denver and Indianapolis. The carrier expanded distribution to
Nashville in October.
T-Mobile USA Inc., though, is taking a slightly different tack. The carrier last year introduced a dual-mode calling
service that allows users with GSMNV1-Fi phones to place calls over their Wi-Fi network for free.
Although AT&T would not comment on its UMA plans, Current Analysis analyst Peter Jarich said that if the carrier
placed UMA software on its iPhone “they’d probably see a great uptake and they could eventually leverage the core
network kit to support femtocell network integrations as well.”
ThinkPanmure said GSM operators will roll out femtocells on a broad scale by next year.
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s issinfo.ch
July 10, 2006
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12:42 PM
Mobile phone airship to conquer stratosphere
Airships like this one may one day fill the stratosphere (Stratxx)
A zeppelin will replace all the terrestrial mobile phone antennas in Switzerland
inventor has his way.
-
if a Swiss
Should Kamal Alavi’s project for the high-tech airship take off, the worlds of mobile telephony and
data transmission would be turned on their heads.
Not only would the technology, called High Altitude Platform Systems (Haps), make the current 1,000
earth-bound antennas redundant, it would drastically reduce radiation.
A Swiss of Iranian extraction, Alavi is a former aerospace engineer turned entrepreneur who heads his
own firm, Stratxx. Together with a team of 50 scientists, he is preparing a 2007 test run of the
airship, which he has named the “X station”.
Thanks to a GPS steering system developed by the Swiss Federal Institute of Technology, the 60meter long helium-filled balloon will remain stationary at 21 kilometres above the earth.
A small-unmanned aircraft outfitted with a mobile phone antenna and other devices for transmitting
digital data will be attached to the zeppelin. The X station has been equipped with giant propellers to
help counter the almost constant buffeting from the wind.
Solar panels will supply the energy to propel the airplane and antenna. Underneath will be a platform
containing technical equipment, conceived by Ruag, the large Swiss aerospace concern.
Radiation
“Transmitting on earth causes lots of radiation, because you have to penetrate countless buildings,”
Alavi says, arguing that phone connections are more reliable when transmitted from above because
the signals are unobstructed by manmade or natural objects.
And “spot beam” antennas developed at Lausanne will allow radiation to be adjusted according to
usage, regions with little activity receiving relatively less.
But Switzerland’s largest mobile telephone operator, Swisscom believes not all of the technological
hurdles have been overcome.
“This project cannot replace the present mobile telephone system,” spokesman Sepp Huber told
swissinfo.
The X station would not be limited to forwarding mobile telephone signals, but would also be capable
of handling the radio, television and internet needs of entire nations.
Alavi believes that his project is also economical. He estimates that a Haps airship will cost no more
than SFr4O million ($32 million).
In comparison, a single mobile phone antenna costs about SFr300,000 while a communications
satellite starts at SFr600 million.
Alavi says the X stations are conceived to be low maintenance. In the event of a defect, the aircraft
will be decoupled from the airship and returned to earth, much like a mini-space shuttle.
The project is now in a key phase. Solar cells are being tested at an altitude of 30 kilometres, and final
preparations are underway for the launch of the first airship into the stratosphere. The entire system
should be ready for testing a year from now.
The potential is enormous if Stratxx manages to be the first to fly with this new technology. About 20
Haps would be required to cover Europe alone while Africa would need twice as many.
swissinfo, Etienne Strebel
CONTEXT
The X station will go to an altitude of 21 kilometres nine more than civilian aircraft are permitted. This
height is needed to place the antenna stations above the jet stream where winds are moderate.
—
Satellites are stationed from 500 to 36,000 kilometres above earth.
An X station can service an area of about 1,000 kilometres in diameter. X stations can also exchange data
between themselves.
In addition to the Swiss Federal Institutes of Technology at Zurich and Lausanne and Ruag, participants in
the project include Neuchâtel University.
http://www.stratxx.com/)
URL of this story:http ://www.swissinfo.ch/eng/swissinfo. html?siteSect= 105&sid =6873540
Changes in Government Regulation
The Federal Communications Commission has the strategic goal for, “All Americans to have
affordable access to robust and reliable broadband services.” The support of the FCC in the
deployment of broadband services through WiMax, as well as other telecommunication services
that are coming into the industry, will bring competition to the signals that are transceived from
wireless facilities. Broadband services allow for the convergence of voice, video, and data
services into a single network. Not only does it allow for a single network, but it can be carried
further over distances and it is cheaper to deploy. Currently, multi-mode phones are being
rd
th
generation technologies, such as VOIP and Internet, which will require
equipped with 3
and 4
additional bandwidth.
The FCC’s support of these services will quickly bring these
marketplace.
technologies to the
The strategic goal goes on to state that, “Regulatory policies
must promote technological neutrality, competition, investment, and innovation to ensure that
broadband service providers have sufficient incentive to develop and offer such products and
services.”
Mobile satellite systems and other new technologies may compete with land-based wireless
communications systems, thereby reducing the demand for tower space and other services we provide.
The FCC has granted license applications for several low-earth orbiting satellite systems that are
intended to provide mobile voice or data services. The growth in delivery of video services by direct
broadcast satellites may also adversely affect demand for our antenna space.
Source: RCR Wireless News, January 26, 2004
Order Code RS20993
Updated May 27, 2004
CRS Report for Congress
Received through the CRS Web
Wireless Technology and Spectrum Demand:
Third Generation (3G) and Beyond
Linda K. Moore
Analyst in Telecommunications and Technology Policy
Resources, Science, and Industry Division
Summary
Advances in wireless telecommunications technology are converging with Internet
technology to foster new generations of applications and services. Presently, the United
States and other countries are moving to a third generation (3G) of mobile telephony.
The defining feature of3G technology is that transmission speeds are significantly faster
than prevailing technology.
A related trend is the growth in use of Wi-Fi (wireless fidelity); these are localized
wireless networks providing high-speed access to the Internet. Whereas 3G could be
described as bringing Internet capabilities to wireless mobile phones, Wi-Fi provides
wireless Internet access for portable computers and handheld devices, such as Personal
Digital Assistants. The two technologies are seen by some as competing for customers
and by others as complementary
providing a broader base and greater choice of
devices for wireless communications and networking.
From the perspective of
spectrum management, a significant difference between the two technologies is that 3G
services operate on designated frequencies licensed by the Federal Communications
Commission (FCC), while Wi-Fi shares unlicenced spectrum with other technologies.
Providers ofthe two technologies share in common the concern that there is insufficient
spectrum available for their services to be developed to full market potential.
—
Industry experts have noted that more efficient uses ofspectrum must be developed
to meet future demand. The U.S. Congress and federal government departments and
agencies are examining the impact that new technology will have on bandwidth demand
and spectrum allocation, prompting Congress to review the policies and laws that guide
spectrum management. Legislation, supported by the Administration, has been
introduced that would make it easier for government agencies to relinquish spectrum to
private wireless carriers for use in providing 3G and other services (H.R. 1320,
Representative Upton and S. 865, Senator McCain).
This report will be updated.
Congressional Research Service + The Library of Congress
CRS-2
Wireless Technology: Development and Demand
In order to deploy third-generation (3G) and other advanced wireless technologies,
telecommunications carriers and their suppliers are seeking effective strategies to move
to new standards, upgrade infrastructure, and develop software for new services. This
migration path includes decisions about using spectrum.
Radio frequency (RF) spectrum is used for all wireless communications. It is
managed by the Federal Communications Commission (FCC) for commercial and other
non-federal uses and by the National Telecommunications and Information
Administration (NTIA) for federal government use. International use is facilitated by
numerous bilateral and multilateral agreements covering many aspects ofusage, including
mobile telephony. Spectrum is segmented into bands of radio frequencies and typically
measured in cycles per second, or hertz.’
Spectrum bandwidth is a finite resource that is infinitely re-usable. Commercial
wireless communications currently rely on bandwidth within a narrow range.
2 American
competitiveness in advanced wireless technology may be constrained by the limited
amount of exploitable bandwidth that is available. This constraint is both specific, in the
inherent finiteness of useful spectrum, and relative, in comparison to the amount of
spectrum available for commercial use in other countries. Developments in technology
have in the past facilitated the more efficient use ofbandwidth within a given portion of
the spectrum. New technologies, such as Software-Defined Radio (SDR) and “smart”
antennae for terrestrial wireless, are being explored and implemented to increase the
efficiency of spectrum and to expand its usable range.
Technology Development. Mobile communications became generally available
to businesses and consumers in the 1980s. This “first generation” technology, still in use,
is analog, the prevailing telecommunications technology of the time. Second generation
(2G) wireless devices are characterized by digitized delivery systems that provide
qualitatively better delivery of voice and small amounts of data, such as caller ID. The
next major advance in mobile technology is referred to as the third generation —3G—
because it represents significant advances over the analog and digital services that
characterize current cellular phone technology. A dramatic increase in communications
speed is the most important technical feature of 3G.
3
Wireless communications services have grown significantly worldwide, and
explosively in some countries. Consumer demand for wireless telephony in the United
States has soared in recent years, totaling over 164 million mobile phone subscribers in
‘One million hertz = 1 megahertz (MHZ); 1 billion hertz = 1 gigahertz (GHz).
2
The FCC limits consideration of bandwidth available for 3G to frequencies below 3 GHz.
The Federal Communications Commission (FCC) identifies key service attributes and
capabilities of3G as the following: capability to support circuit and packet data at high bit rates;
interoperability and roaming; common billing and user profiles; capability to determine and
report geographic position of mobiles; support of multimedia services; and capabilities such as
“bandwidth on demand.” 3G speeds are: 144 kilobits per second at vehicular traffic speeds; 384
kilobits for pedestrian traffic; 2 megabits or higher for indoor traffic, [http:I/wvv.fcc.govI3G].
(Visited May 27, 2004.)
CRS-3
May 2O04. In approximately the same time frame, use of the Internet expanded
dramatically from an arcane tool for specialized research to a popularized, user-friendly
service providing near instant access to information and entertairuuent. Wireless Internet
is widely expected to redefine how computers are used in the future. 3G technologies
bring the wireless Internet revolution to cell phones. Business and consumer demand for
new, advanced wireless services
including 3G and Local Area Networks (LANS),
such as those using Wi-Fi (wireless fidelity)
is considered by many to be an engine
for future growth in American and global economies.
—
—
Third-generation and future developments in wireless technology will be able to
support many services for business and consumer markets, such as: enhanced Internet
links, mobile intranetlextranet, mobile commerce (m-commerce)—including the ability
to make payments—”always on” capabilities, high-quality streaming video and location
identification. In the United States, location-fmder technology for existing cellular phones
is being introduced through the nationwide wireless enhanced 911 (E911) program.
5
Public Policy and 3G
International Agreements on 3G. International agreements that coordinate and
enable global telecommunications are negotiated under the aegis of the International
Telecommunication Union (1TU), a specialized agency of the United Nations. Delegates
to the ITU World Radio Conference in 2000 (WRC-2000) agreed that harmonized
worldwide bands for advanced commercial wireless services were desirable in order to
achieve global roaming and economies ofscale. Resolutions voted by delegates ofWRC
2000 encouraged nations to make available some part of one or more of the three
spectrum bands identified in committee (806-960 MHZ, 1710-1885 MHZ, and 2500-2690
MHZ) for use as harmonized spectrum. In the United States, most of the frequencies
within these bands had been allocated for other uses, requiring reassignment and
relocation in order to provide harmonized spectrum to meet WRC accords.
Harmonized Spectrum. The applications of wireless technology are tied to
spectrum. Infrastructure, such as towers, relay stations, and handsets, must be able to
provide communications along pre-designated frequencies. A benefit of harmonization
is to provide common bands of spectrum dedicated to 3G technology worldwide. This
makes it easier for carriers to cover large geographical areas and for the
telecommunications industry to develop 3G hardware and software. Many industry
observers, however, believe that WRC-2000 did not evaluate the practical considerations
of achieving global roaming capabilities and economies of scale through harmonization.
They argue that countries like China and Brazil are using spectrum to develop 3G
technology in bandwidths not covered by the WRC-2000 resolution, and that global
roaming exists today without the benefit of harmonized spectrum.
Policy Decisions in the United States. Following WRC-2000, President
Clinton directed the Secretary of Commerce to work with the FCC, in coordination with
the NTIA, to prepare studies on allocating bandwidth for harmonized spectrum. In
Statistic updated regularly at [http://www.ctia.org].
CRS Report RS2 1028, Emergency Communications: Wireless Enhanced9l 1 (E911) Issues
Update.
CRS-4
response, the NTIA and the FCC issued reports, respectively, on 17 10-1850 MHZ and
2500-2690 MHZ use.
6
FCC Actions. The report provided by the FCC covered spectrum used primarily
by Fixed Service operators for Multipoint Distribution Service (MDS), Multichannel
Multipoint Distribution Services (MMDS) and Instructional TV Fixed Service (ITFS).
As part of the effort to provide additional spectrum for 3G and other new wireless
technology, the FCC subsequently adopted a First Report and Order and Memorandum
Opinion and Order
7 adding a mobile allocation to the 2500-2690 MHZ range. In March
2003, the FCC announced a Notice of Proposed Rulemaking that will probe alternative
uses for underutilized portions of this spectrum. One of the announced objectives of the
8
proposal is to promote broadband wireless.
In line with the actions of the 3G planning group, the FCC allocated new spectrum
for advanced wireless services, a category that includes but is not limited to 3G.
9 The
spectrum bands are two blocks of 45 MHz each of contiguous spectrum at 1710-1755
MHz and 2110-2155 MHz. The 1700 M}{z band spectrum is used primarily by federal
agencies, including the DOD. Plans are for a rapid relocation of federal agencies other
than the DOD from the 1710-1755 MHz band, with a slower relocation plan for
frequencies used by the DOD. The speed and efficacy of this relocation will be impacted
primarily by the ability to fund the costs of relocation. As part of its plan for relocation
within the 2100 MHz band, the FCC is also looking at other bandwidths that might be
0
freed for advanced wireless servjces.’
NTIA Actions and the Department of Defense. In its report, the NTIA
divided the band into two segments: the 17 10-1755 MHz band, already scheduled to be
made available for commercial use,
’ and the 1755-1850 MHZ band occupied by the
1
Department of Defense (DOD) and 13 other government agencies. In particular, the
report addressed the issue ofreallocating spectrum now used by the DOD. The DOD also
issued a report on the subject with different conclusions than those of the NTIA.
12 The
6
“The Potential for Accommodating Third-generation Mobile Systems in the 1710-1850 MHz
Band,” Final Report, March 2001, U.S. Department of Commerce, NTIA
[http://www.ntia.doc.gov/ntiahome/threegI33001/3g3300 1 .pdf]; and “Spectrum Study of the
2500-2690 MHz Band,” Final Report, March 30, 2001, FCC, [http://www.fcc.gov/3G].
FCC 01-256, September 6, 2001, September 24, 2001.
by the FCC on March 13, 2002, by Notice of Proposed Rulemaking and Memorandum
Opinion and Order (FCCO3-56), FCC News Release, “FCC Initiates Proceeding to Facilitate
Wireless Broadband in the 2500-2690 MHz Bands,” March 13, 2003 [http://www.fcc.govJ.
FCC, Second Report and Order, ET Docket No. 00-258 (2002).
9
‘°FCC, Third Report and Order, ThirdNotice ofProposedRulemaking andSecondMemorandum
Opinion and Order, ET Docket No. 00-258 (2003).
The Omnibus Budget Reconciliation Act of 1993 (47 U.S.C. 927) directed the FCC to
allocate frequencies from the 1710-1755 MHz band on a “mixed-use” basis.
12
“Investigation of the Feasibility of Accommodating the International Mobile
Telecommunications (IMT) 2000 Within the 1755-1850 MHz Band,” 9 February 2000, DOD.
CRS-5
NTIA, DOD and others continue to study and debate Defense’s use of spectrum and
possible plans for migration from the 1755 1850 M}{z band to other spectrum ranges.
-
Spectrum Relocation.’
3 In October 2001 the NTIA announced that a new plan
for the selection of 3G spectrum would be prepared with the FCC, the DOD and other
Executive Branch agencies.’
4 After receiving this and other interagency assessments,
the FCC announced the allocation ofadditional spectrum for advanced wireless services.’
5
In mid-2002, the Department of Commerce circulated draft legislation that proposed the
creation ofa Spectrum Relocation Fund. This would make it possible for federal agencies
to recover relocation costs when they are required to vacate spectrum slated for
commercial auction. Previously, the Strom Thurmond National Defense Authorization
Act of 1999 (P.L. 105-261) authorized agencies to accept compensation payments when
they relocate or modify frequency use in order to accommodate non-federal users. It
authorized the NTIA and FCC to develop procedures for this. The NTIA subsequently
ruled that agencies must submit detailed estimates ofcosts. The FCC suggested that these
estimates be included in the auction process for the relevant spectrum; in effect,
commercial bidders would be covering the costs ofrelocation. The Communications Act
of 1934 would need to be modified to permit the agencies access to auction funds, even
ifpart of the proceeds have been earmarked for their use. A bill (H.R. 1320, Commercial
Spectrum Enhancement Act) introduced in the House on March 18, 2003 called for the
creation of a Spectrum Relocation Fund. It was approved by the House Committee of
Energy and Commerce on April 30 with an amendment to clarify that federal spectrum
could be transferred for non-commercial uses, such as public safety, and for uses where
spectrum is not now auctioned, such as unlicenced spectrum. The bill was passed by the
House on June 11, 2003. The bill was passed, with an amendment, in mark up by the
Senate Committee on Commerce, Science and Transportation on June 26. The addition
of a controversial amendment that could benefit Northpoint Communications reportedly
could harm the bill’s chances for passage by the Senate.’
6 Reportedly, the Acting Director
of the NTIA, Michael Gallagher, has written to Vice President Richard B. Cheney
suggesting that the passage of the Commercial Spectrum Enhancement Act would spur
the development of 3G. He is quoted as saying in the letter that the NTIA “would not
support such an action until identification of alternative frequencies for the affected
federal systems has been completed.”
7
‘
See also CRS Report RS21508 Spectrum Management: Special Funds.
An lntra-Government 3G Planning Group (103 GPG) was created, comprising the NTIA, the
4
‘
FCC, DOD, the Office ofManagement and Budget, the Office ofScience and Technology Policy,
and the Department of State.
‘ FCC News Release, “FCC Allocates Spectrum for Advanced Wireless Service and Proposes
Licensing and Service Rules,” November 7, 2002 [http://www.fcc.gov].
Natio1 Journal’s CongressDaily (AM Edition), “Administration Disapproves of Northpoint
16
Funding Language,” November 11, 2003.
‘‘
“Gallagher Recommends Govt Actions to Forward 3G Deployment,” TELECOM A.M.,
(Today’s News), April 23, 2004.
CRS-6
Wi-Fi
Wireless Local Area Networks (W-LANs) operate on unlicenced spectrum, using
radio frequencies in the free 2.4 GHz and 5.4 GHz spectrum bands. A group of standards
for frequency use in these bands is known as the 802.11 family. The 802.llb standard
is currently the most widely used and is commonly referred to as Wi-Fi, for wireless
fidelity. Wi-Fi provides high-speed Internet access for personal computers and Personal
Digital Assistants (PDAs) and is also widely used by businesses to link computer-based
communications within a small area. The current operating radius for Wi-Fi is 300-350
feet. Links are connected to a high-speed wireline (landline) either at a business location
or through HotSpots. HotSpots are typically located in homes or convenient public
locations, including many airports and café environments such as Starbucks. Another
standard for wireless Internet is Bluetooth, which has a shorter range than Wi-Fi but
works well in cell phones. Bluetooth handles both voice and data; Wi-Fi is mostly data
only, with some use of Voice over Internet Protocols (VoIP). Many industry experts
predict that Wi-Fi and its successor technologies will be the primary link for wireless
Internet, while 3G mobile phones and Bluetooth-enabled PDAs will provide other
th
8 Legislation was introduced in the 108
services.’
Congress (S. 159) that would require
the FCC to allocate “not less than an additional 255 megahertz of contiguous spectrum”
in the 5 GHz band. In response, the FCC has provided 255 MHz of spectrum between
5.47-5.725 GHz, adjacent to one of the frequency bands now used by Wi-Fi.’
9
Conclusion
The continued growth in demand for bandwidth for private and public sector use has
prompted Congress to review the policies and laws that guide the management of this
Some future legislative initiatives regarding spectrum policy might be
resource.
influenced by the formation of a Spectrum Policy Initiative by President George W.
° Among the issues are consideration ofthe law, policies and rulings for spectrum
2
Bush.
allocation that will best meet the sometimes conflicting objectives of protecting
consumers, fostering new technology, encouraging efficiency, bolstering international
competitiveness, and promoting competition, fairness, and access in domestic markets.
18
Financial Times, “Wi-Fi and 3G; cheaper, faster and actually here,” March 12, 2003.
19
FCC, “Revision.. of Rules to Permit Unlicenced.
No. 03-122, released November 18, 2003.
.
20
.
.
Devices in the 5 GHz Band,” Docket
By Executive Memorandum, June 5, 2003 [http://www.whitehouse.gov/news/releases/
2003/06/20030605-5.html]. (Viewed May 27, 2004.)
Government Computer News
The battle for spectrum
030707
By Bob Brewin
Growing demand and a fmite supply of radio frequencies could force
and compromise
confrontation
between the U.S. government and
competing global interests
—
—
Radio frequency spectrum isn’t something you can see, touch or feel, but like other commodities
in short supply, the Earth’s radio frequencies are increasingly valuable as economic and strategic
resources.
The organization that decides how spectrum should be allocated for different purposes is the
International Telecommunication Union (ITU), a United Nations agency. It will host the World
Radiocommunication Conference this fall to allocate global radio frequencies among competing
interests
a highly competitive event that insiders refer to as the Wireless Olympics.
—
Spectrum issues include the demands of an emerging fixed-wireless broadband industry, the
performance of ship and airborne military radar, and the desire of shortwave broadcasters to
operate in a frequency that the U.S. federal government wants to use for data communications
for military and homeland security purposes.
Spectrum is the raw material of mobile and cellular networks that have transformed the way
people communicate. It has liberated the phone from its wired tether and made anywhere,
anytime communication possible for teenagers and millions of people in China, the world’s
largest mobile phone market.
That finite resource has spawned armies of BlackBerry-toting executives and road warrior
students tapping Wi-Fi hot spots in airports and coffee shops to check e-mail and browse the
Web. Remote-sensing satellites use a slice of the spectrum to monitor the weather. Massive
arrays of satellite dishes dedicated to radio astronomy rely on radio spectrum to probe the
mysteries of the cosmos at the beginning of time.
But spectrum remains a limited resource, and authorities must allocate it to meet the
requirements of emerging communications technologies and, at the same time, protect the radio
frequencies that older forms of defense and public-safety communications require.
World radio conference Every three to four years the ITU hosts the World
Radiocommunication Conference for delegations from its 191 member states and 600 sector
members. The sector delegates represent telecommunications companies, such as AT&T, and
digital technology companies, such as Intel. The conference is the venue in which the ITU sets
policies for allocating radio frequency spectrum.
The ITU held its last world conference in 2003. At that time, it established global allocations for
Wi-Fi spectrum in the 2.4 Ghz and 5 GHz bands, a decision that transformed Wi-Fi into a global
phenomenon and enriched numerous companies, including Intel, the Linksys division of Cisco
Systems and Wi-Fi chipset manufacturers Atheros and Broadcom.
The world conference this fall in Geneva is one that Richard Russell, associate director of the
White House Office of Science and Technology Policy, calls the Wireless Olympics because of
the many competing spectrum demands that its participants must resolve. Russell will lead the
U.S. delegation as its ambassador.
The 2007 World Radiocommunication Conference will make spectrum allocations that are
critical for new and emerging technologies of economic importance to the U.S. high-tech
industry. “This is our opportunity to move the ball forward on new services [backed] by U.S.
companies, which will be good for the economy,” Russell said.
In his role as leader of the U.S. delegation, Russell said he must balance U.S. industry interests in
spectrum’s economic value against national security and other public needs. The National
Telecommunications and Information Administration, which defines those public requirements,
has raised questions about new services and technologies that impinge on spectrum that DOD
says it needs for strategic and tactical command-and-control systems. The process The Federal
Communications Commission is responsible for developing initial industry positions for the U.S.
delegation to the conference. For that decision-making, the FCC relies on the World
Radiocommunication Conference 2007 Advisory Committee and five informal working groups
to assess spectrum needs. Those groups held their first meetings in February 2004.
During that preconference period, the working groups approve drafts and present them to the
conference advisory committee. The advisory committee forwards the drafts that it approves to
the FCC, which publishes them for public comment. The consensus reached after the public
comment period will inform the positions that the United States takes at the world conference.
With the conference eight months away, the United States is far from reaching consensus on
many contested issues. Russell said a hot question will be who gets to operate in the 698 MHz to
806 MHz radio frequency band.
That question appeared to be settled after participants at the 1992 and 2000 world conferences
set aside those spectrum bands for broadband wireless mobile or cellular services. Since then,
however, an emerging fixed-wireless broadband industry
with backing from Intel
has
decided it needs to operate in those same frequencies. It wants to offer the public a high-speed
wireless alternative to high-speed Internet service that cable and phone companies now provide.
—
—
The FCC is the present battleground on which Intel and its allies are fighting existing wireless
carriers
AT&T, Verizon, Sprint Nextel and others
to influence the U.S. position on use of
—
—
that high-speed radio frequency band. Nancy Victory, a partner at the Washington, D.C., law
firm Wiley Rein and chairwoman of the FCC advisory committee, said the two industry sides
appear to be so far apart that the U.S. delegation might go to the world conference with two
opposing views on the use of the 698 MHz to 806 MHz band. Russell, however, said he is
confident that the United States will end up with a unified position on the contested spectrum
that will satisf’ all industry segments before he heads to Geneva.
While that question is debated in the months preceding the conference, DOD is concerned about
how the ITU will rule on frequencies that the department uses for navigation and mobile
communications. The ITU must decide whether to let industry use those spectrum bands for new
broadband mobile services. Badri Younes, DOD’s director of spectrum management, said
allowing broadband mobile services to operate in those frequencies could degrade the
performance of ship and airborne radars and mobile communications systems.
The frequencies in which DOD has a stake are the 410 MHz to 430 MHz band that fixed and
older mobile communications systems use, the 2700 MHz to 2900 MHz band on which pilots
rely for radio navigation, and the 3400 MHz to 3650 MHz radio frequency band that ship and
airborne radars use.
DOD also has an interest in whether the ITU decides to protect high-frequency (HF) spectrum
from encroachment by shortwave broadcasters worldwide. All three military services rely on HF
for long-range terrestrial communications. Fighting to retain control of the HF bands might seem
like a last-ditch stand to keep horse-drawn buggies, some spectrum experts say. Broadcasters,
such as the BBC, have moved from HF and now rely on satellite and Internet feeds.
But the development of high-quality digital radio broadcasting technology has changed the
picture and made HF suddenly more appealing. Shortwave broadcasters worldwide want the ITU
to allocate to them as much as 800 KHz of additional spectrum in the HF band from 4 MHz to 10
MHz. A new golden age Analog shortwave broadcasts are typically interrupted by hisses and
pops. But the new technology, Digital Radio Mondiale (DRM), will enable shortwave
broadcasters to transmit programs thousands of miles with the signal quality and audio clarity of
FM radio, said Nigel Holmes, transmission manager at Radio Australia.
DRM could lead to a golden age for shortwave broadcasting, Holmes said.
Broadcasters worldwide
the BBC, Deutsche Welle in Germany, Radio France, Radio Sweden,
Radio Canada and Radio New Zealand
have embraced it. The National Association of
Shortwave Broadcasters in the United States, most of whose members are religious broadcasters,
supports DRM, and it has urged the FCC to push for allocating additional HF spectrum for
broadcasting.
—
—
But Eric Johnson, professor of engineering at New Mexico State University and a member of the
AFCEA International HF Industry Association, said HF is equally well-positioned to support a
golden age of data communications. Thanks to new standards, some of which Johnson helped
develop, HF can support data rates of 9,600 bits/sec in a 3 KI-{z channel and 64 bits/sec in a 12
KHz channel.
In an era in which users can access the Internet at speeds measured in megabytes of data, 64
bits/sec does seem like horse-drawn buggy speed, but it exceeds the data rate of satellite
communication systems on some of the Navy’s smallest ships, Johnson said. The Air Force
already relies on HF in its High Frequency Global Communications System to transmit e-mail
messages to airlifters the Air Mobility Command operates.
The Homeland Security Department’s Customs and Border Protection organization operates a
nationwide HF network to communicate with its boats, planes, helicopters and vehicular assets,
Johnson said. Australia and the United Kingdom recently installed new HF networks. Those
DHS and overseas networks could be undermined if shortwave broadcasters receive expanded
HF spectrum allocations, Johnson said.
Younes said HF spectrum is critical to DOD’s combat operations in Afghanistan and Iraq and
relief operations such as those DOD conducted in late 2004 and early 2005 after a tsunami hit
many Asian and Indian Ocean countries. DOD must protect HF spectrum from broadcasters’
incursions as it develops new Internet-based applications for HF, he said. HF is essential for
communications with partner countries in multinational coalitions, many of whom use it as their
sole means of communications, he added.
The FCC has deliberated but has not reached a decision about whether to back the shortwave
broadcasters or the government’s tactical and mobile users of HF spectrum. Johnson said the
FCC needs to side with DOD and other federal stakeholders and do so well ahead of the
conference to protect HF spectrum that DOD and other federal agencies use. Many countries are
waiting to learn the U.S. policy position before they solidify their own, and an early signal from
the United States could slow the broadcasters’ momentum in seeking additional HF spectrum, he
said.
Remote-sensing applications Another contested frequency is the 36 0Hz to 37 GHz band. The
National Academy of Sciences, for example, wants the United States to push for mandatory
power limits on communications satellites operating in that band to protect satellite-sensing
systems in the Earth Exploration Satellite Service. U.S. government and nongovernmental
entities operate that service.
The academy informed the FCC that scientists rely on that band for passive sensing of the
Earth’s surface and atmospheric conditions. Scientists say they have little flexibility in choosing
frequencies to conduct their remote-sensing observations because the specific frequencies of
observed elements, such as the absorption and emission of passive microwave radiation, are
established by the laws of physics and chemistry.
But the Satellite Industry Association, which represents satellite operators, service providers and
manufacturers, has told the FCC that it opposes mandatory power limits on communications
satellites. Any such limits would harm the development of new services and technologies that the
satellite industry wants to offer, it said.
The competing demands don’t end there. The airline industry and the Federal Aviation
Administration have put in their bid for additional spectrum for flight test telemetry. Boeing says
it needs access to additional radio frequencies to support a near-doubling of the test data that the
FAA now requires before certifying commercial aircraft.
Boeing says it monitored 64,000 test points in 1995 to certify its 777 airliner. It expects to
monitor 100,000 test points for its new fuel-efficient 787 Dreamliner series aircraft that will
carry 250 to 330 passengers. Younes agreed that a failure to gain additional spectrum for flight
testing would inevitably cause schedule delays and cost increases for Boeing and other airplane
manufacturers.
Russell said his goal in representing the U.S. is to be competitive in that and other high-profile
spectrum contests at the Wireless Olympics, where going for the gold will mean more to the
United States than winning a coveted medal.
© 1996-2008 1105 Media, Inc. All Rights Reserved.
LO5to,, ni
he oston 1obc
Big wireless carriers get set to free the phone
By Carolyn Y. Johnson, Globe Staff
I March 28, 2008
It is a scenario rarely seen in today’s technology market: Cellphone customers wander into any store, pick
any device from a shelf, and connect it to any wireless network one as open as the Internet.
-
But spurred by growing demand and a federal airwaves auction that closed last week, the major wireless
carriers are stepping away from a model in which each cellphone is controlled by a single company that
sells customers a device locked to their network, demands a lengthy contract, and limits the phone’s
features.
‘We call it a 180-degree about-face to open access, and it really is a fundamental shift in business
models if we can get there,” said Linda Barrabee, senior analyst at Yankee Group, a technol ogy
research firm, and author of a recent report, “Open Access is the New Black.”
-
Just a year ago, open celiphones were largely the province of hackers or frequent international travelers.
But the newest website educating people about how to connect outside devices to a network is no hacker
forum: It is run by AT&T, the nation’s largest wireless carrier. Verizon Wireless, the number two provider,
held a two-day conference this month to tell independent developers how they could get their devices
certified to work on its network. And Google, the Internet giant that lobbied for open access and last year
unveiled an open mobile platform called Android, this week detailed a proposal to use portions of the
airwaves between television channels for open Internet access.
Suddenly, open access is fashionable.
The pivotal moment occurred in the run-up to this year’s federal auction of valuable broadcast spectrum,
which can also be used to carry telephone calls and data. Because of federal requirements that TV
channels broadcast digital signals by February 2009, some airwaves now being used for TV will be
available for other uses. As the auction of what is often called the last beachfront property in the wireless
world approached, politicians, consumer advocates, and Google launched a discussion about the future
of telecommunications in the United States.
The Federal Communications Commission attached rules to a slice of the spectrum, requiring that the
winner of that portion leave the network open to outside devices and applications.
Meanwhile, more capable phones and networks meant people began to expect the devices to function
more like computers, and public awareness of restrictive carrier policies increased.
When the high-profile iPhone was launched exclusively on the AT&T network last summer, it increased
public awareness that devices were locked, meaning they were only compatible with one carrier. People
who paid full price for an iPhone could not use it through another carrier, even if the carrier T-Mobile, for
instance used compatible technology.
-
-
When the iPhone was unlocked last summer to allow use with other carriers, what would have seemed to
be an insider-geeky event drew widespread attention and national news stories.
Last fall, SDrint agreed to provide codes to unlock its phones as part of a class-action settlement. And all
four major carriers have said that when a customer ends a contract early, termination fees will be
prorated.
Driven by a combination of regulation and public awareness, the zeitgeist for “open” was born. Earlier this
month, Apple began allowing outside software developers to create their own programs, such as games.
Not long ago, carriers bristled at the notion that the nation’s wireless system stifled innovation. Verizon
Wireless fought the FCC’s decision to attach open access requirements to the spectrum.
“Imposing any such requirements in the competitive wireless market would reduce the revenue the
government will receive from the spectrum auction and limit the introduction of new and innovative
wireless services,” the company said in a statement in July, as the rules were being debated.
But Verizon Wireless eventually accepted the rules, and earlier this month it won the coveted block of
spectrum subject to the open-access conditions. Also, AT&T and other companies won other portions of
the spectrum, and the auction raised $19.1 billion. At its conference for developers last week in New
York, Verizon emphasized that new partnerships were essential for innovation.
‘We believe that as the two great megatrends of mobility and the Internet come together, the next wave of
growth will come from a whole new generation of devices, applications, and services,” said Ivan
Seidenberg, chief executive of Verizon Communications Inc., which owns 55 percent of Verizon Wireless.
“No single company whether you’re a carrier, a manufacturer, a software company, or anybody else
will be able to envision all these uses or meet all the needs on their own.”
-
-
Not to be outdone, AT&T launched a website the day before the conference, emphasizing its open
network.
“This is not new business for us,” said Mark Collins, vice president of Consumer Data Products for AT&T.
The company uses GSM, the predominant wireless technology and “the most open standard on the
planet,” he said.
Still, Collins said AT&T phones would be sold locked -and unlocked only upon customer request. T
Mobile has a similar policy. Sprint and Verizon Wireless use different technology. Sprint and T-Mobile
also moved to embrace openness as members of the “Open Handset Alliance.” To some extent, the
technology for open systems has been available all along, but wireless carriers have created a different
model in the United States than in Europe or Asia, where consumers can easily swap a phone between
providers.
But by the end of this year, Verizon will allow approved devices that aren’t offered by the company to
connect to its network. People can already buy phones and add T-Mobile or AT&T service. Also, Sprint is
beginning to roll out its Xohm mobile broadband WiMAX service, touted as part of its “open Internet
vision.”
Ultimately, loosening the relationship between the wireless provider and devices could spur innovation
devices that phone companies may never have developed. Sprint, for instance, powers the wireless
connection for the Amazon Kindle, an e-book reader.
-
Openness comes at a pivotal point for the industry. Companies are struggling to prevent what happened
online, when people moved away from proprietary “walled gardens” like AOL and Prodigy and onto the
wider Web.
As the cellphone market becomes saturated, providers will have to find ways to grow other than selling
people their first phone, and as data services become more common, “their whole business model is
called into question,” said Paul DeBeasi, senior analyst with the Burton Group. “If instead of paying for
minutes people pay for Skype that’s what happened to the old AT&T. People stopped paying for long
distance; it became a commodity.”
-
But even as companies try various approaches to openness, their definition of “open” remains unclear.
Are they paying lip service to a popular idea or will they open a new frontier in phones and computing?
-
According to Barrabee, it will be years before the mobile ecosystem really changes and technological
hurdles are overcome so people can really walk into stores and buy any device and pick any network.
And consumers may continue to prefer the current US model, where it is clear whom to call for customer
support and people are used to cheap phones and long contracts.
“The concept of open access is a bit intoxicating, but we really need to see the details and action need
to see an ecosystem emerge and then see distribution channels for these devices and services, before
we see the impact,” said Barrabee. “And then it is really a question how much does anybody want?”
-
-
Carol n Y. Johnson can be reached at c ohnson
© CoDvriaht 2008 The New York Times Company
lobe, corn..
RCR fie1ess News
WiMAX to snag 47M subscribers by 2013
Story posted: May 9, 2008 8:18 pm EDT
-
A new report from Juniper Research predicts WiMAX growth will begin to take off in the period between 2009 and
2011, growing to more than 47 million subscribers worldwide by 2013.
The report predicts W1MAX will find a strong foothold as a substitute for DSL technology.
“We determined that the vast majority of the W1MAX 802.16e trials and network contracts which are being announced
almost daily will begin by providing fixed broadband,” said Howard Wilcox, author or the report.
“WiMAX can deliver broadband not only to uriwired areas, but can also improve speeds for subscribers who are on
the fringe of DSL coverage in metropolitan areas.
“We anticipate that mobile usage will develop after initial demand for fixed and portable services
is a flexible platform that can operate in all three modes of usage,” said Wilcox.
—
WiMAX 802.16e
The report predicts global revenues for WiMAX service as a DSL replacement technology will exceed $20 billion a
year by 2013 arid that 12% of the DSL subscriber base at that time Will be replaced by WiMAX technology. The Far
East, North America, Western Europe and Africa/Middle East will be the largest markets for WIMAX as a DSL
substitute, predicts the report.
The report cautions that uptake could be slowed by a lack of suitable devices and timely network construction.
PRINTED FROM: http:/Iwww.rcmews.comlappslpbcs.dIIIa,ticle?AID=/20080509/SUB/94007759211008/newsletterl 6&template=pnntart
Entire contents © 2008 Cram Communications, Inc.
Google to bid for U.S. mobile airwaves
Fri Nov 30, 2007 4:22pm EST
By Eric Auchard and Peter Kaplan
SAN FRANCISCO/WASHINGTON (Reuters) Google Inc said on Friday that the company would bid on
coveted airwaves to launch a U.S. wireless network, pitting it against established telecommunications
players AT&T and Verizon.
-
The Internet leader said in a statement that it was ready to go it alone rather than rely on partners in
bidding in the Federal Communications Commission-run auction of 700-megahertz wireless spectrum
due to begin on January 24.
The Silicon Valley-based company said it would make its filing ahead of the FCC deadline on Monday
for companies to declare their interest in joining the airwaves bidding. “We believe it’s important to
put our money where our principles are,” Chief Executive Eric Schmidt said. “Consumers deserve more
competition and innovation than they have in today’s wireless world.”
Wall Street investors have reacted cautiously to Google’s latest move to expand beyond its core Web
search and online advertising franchises, worried the potential upfront costs and eventual network
build-out could exceed $10 billion.
But some analysts have speculated that Google was more interested in ensuring certain requirements
for network openness and that it was bidding just to preserve those rules.
“The real question here is whether Google’s intent is to bid up to the reserve price and assure that the
openness condition stays in place,” Stifel Nicolaus analyst Blair Levin wrote to investors. “Or is the real
purpose to actually win?”
And despite the excitement surrounding a Google bid, Stifel Nicolaus said in a research note that it
suspects Verizon will probably end up winning the auction for the C block spectrum. Google shares
closed down $4.00 at $693.00 on Nasdaq.
Bidding separately instead of assembling a coalition does not rule out Google later signing up partners
if it wins the bidding, said a source familiar with the company’s strategy. But the FCC has “anticollusion” rules that prevent deal-making between potential bidders during the auction period.
The source said Google was eyeing the biggest chunk of spectrum up for auction
the “C block”
considering
bidding
but also was
on separate spectrum reserved for public safety agencies but which
will allow some commercial uses. A Google spokesman declined to comment on the company’s
bidding strategy.
--
--
LAST CHANCE FOR NEW PLAYER
The auction is expected to take several weeks, or even months, of daily, back-and-forth bidding, with
the identities of the bidders kept secret. Big spectrum bidders typically draw up elaborate strategies,
often with input from game-theory experts.
Expected bidders include AT&T Inc and Verizon Wireless, the No. 1 and No 2. U.S. wireless network
operators. Verizon Wireless is a joint venture of Verizon Communications Inc and Vodafone Group Plc.
Less certain are the strategies of satellite broadcasters DirectTV and EchoStar Communications and
cable networks Comcast Corp and Time Warner Inc as well as other wireless players Sprint, T-Mobile
and Clearwire, according to Leviri.
AT&T is in merger talks with EchoStar that could lead them to join forces in the bidding, but with the
deadline looming the time to strike such a deal is short, the Stifel Nicolaus analyst said.
These radio waves are being returned by broadcasters as they move from analog to digital signals
early in 2009. The signals can go long distances and penetrate thick walls. The auction is seen as a
last chance for a new wireless player.
Goole and other Silicon Valley leaders see the wireless spectrum as a way to create more open
cornpetition for mobile services and devices than existing networks
putting the industry on a footing
similar to the free-wheeling Internet.
--
The company won some changes in rules governing use of the spectrum several months ago, but was
denied other requests, including a rule that would have required winning bidders to resell access to
their spectrum on an open wholesale basis.
The winning bidder must provide open access to any device consumers choose to use on the network
if the reserve price of $4.6 billion for the “C Block” is met at auction, Google said. If the reserve price
is not met, the auction would be rerun without the so-called “open-platform” conditions.
On Tuesday, Verizon Wireless announced it had acceded to Google’s open-platform demands and
would open its network to any phone or software application by the end of 2008. But Levin said
Google may still want to bid high enough to lock in a government-enforced open-platform condition on
the 700-megahertz spectrum.
If its bid proves successful, Google could operate a wireless network itself or seek partners to help it
build out the network and to potentially resell wireless services.
Google’s announcement was greeted as good news at the FCC, said a source at the agency. “It means
that they’re willing to go a little bit further into the water,” the source said. “They’re not just dipping
their toe anymore.” FCC officials hope the company’s participation will mean a possible new player in
the wireless business and boost the amount of money the government can bring in from the auction.
“We know we’re going to have somebody in the mix who has a lot of money and who is showing signs
in being interested in winning,” said the source.
Supporting Reference for Monetization
To Fund Investment Opportunities
Many cities and municipal agencies purchase government bonds due to their low risk. As the information
provided in this package has shown, cell site leases or cell sites options are the opposite, high risk. This is
due to the technological and economic factors that are affecting the telecommunications industry today.
Below we have shown an example of the situation that we are advising our clients to take, cash in on the
certain net present value of your site lease options and purchase government bonds. This situation will
eliminate your risk of the termination and bring in slightly more income.
ATS Communications
Initial Rent
EscalatIon
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170000
1,75100
1,803 53
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To Fund Capital Improvements
Receiving a lump sum of the net present value of the monthly rent/income eliminates the risk of lease
termination, which can take place within 30 days. In actuality, the Communication Site Lease Agreement
that you are holding is nothing more than a 30 day option, granting the “Lessee the authority to determine
if the Premise is not appropriate for its operations for economic, environmental or technological reasons.”
Many times the revenue generated from this lease agreement or option is used to fund necessary capital
improvements within parks, city streets, and city buildings. But with the 30 day termination clause
embedded in the lease or option there is a high probability that the payout of 30 years will never come due
to the economic and technological changes previously explained. Along with the risk of waiting for this
stream of income to come through on a monthly basis, there is inflation and the rising cost of materials to
account for, which exponentially increases the cost of capital improvement projects as time goes on.
I
I
THE ASSOCIATED GENERAL CONTRACTORS OF AMERICA
2300 Wilson Blvd., Suite 400 •Arllngton, VA 22201
Title: RISING COSTS, UNCERTAIN DEMAND SQUEEZE NONRESIDENTIAL CONSTRUCTION, AGC SAYS
Date: March 18, 2008
Washington, D.C. — “Construction costs continued to outpace other inflation measures in February, while
demand softened for some project types,” Ken Simonson, Chief Economist for The Associated General
Contractors of America (AGC), said today. Simorison was commenting on two new economic releases for
February: producer price indexes (PPIs) from the Bureau of Labor Statistics (BLS) and housing permits from
the Census Bureau.
“The PPI for inputs to construction industries—materials used in all types of construction plus items
consumed by contractors, such as diesel fuel—climbed 0.6 percent in February, compared to 0.2 percent for
the PPI for finished goods and 0.3 percent for the consumer price index (CPI), before seasonal adjustment,”
Simonson observed. “That continues a trend since steel prices first jumped at the end of 2003. From
December 2003 through February 2008, prices for these construction inputs have soared 31 percent, vs. 15
percent for the CPI.
“That huge gao is especially troublesome for contractors on public projects.” Simonson asserted. “Public
agencies often rely on the CPI to proiect future costs but they are coming up short of the dollars needed to
award contracts. The roblem is most acute with highway orolects. where the huae run—ups in diesel.
asphalt, concrete and steel costs have pushed up the PPI by 50 percent since December 2003
“In February, there were outsized increases in the PPIs for copper and brass mill shapes (5.8 percent); hot—
rolled bars, plates and structural shapes for rebar and structural steel (3.5 percent) and diesel fuel (2.2
percent),” Simonson noted. “Still worse, all of these materials have risen even more since the PPI data was
collected in mid—February. Yesterday, the Energy Information Administration reported that on—highway
diesel costs $3.97 a gallon nationally, up 69 cents in the five weeks since the PPI reporting date and up
$1.29 or 48 percent from a year ago.
“Meanwhile, demand is falling for multi—unit residential projects,” Simonson added. “Census reported today
that multi—unit permits plunged 11% from January and 23% from February 2007. Demand for office, hotel
and retail construction is reportedly weakening as well.
“Nevertheless, I do expect continued strength for hospital, university, power, energy and communication
construction,” Simonson concluded. “There is ongoing demand for these facilities, and their financing is
generally more secure than for projects that depend on short—term rents.”
NOTE: A chart comparing the increase in the PPI for construction inputs and the CPI is at
www.agc.org/febppi. For a more detailed discussion of trends in construction activity, materials costs, and
labor, see AGC’s Construction Inflation Alert at www.agc.org/cia.
The Associated General Contractors of America (AGC) is the largest and oldest national construction trade
association in the United States. AGC represents 33,000 firms, including 7,500 of America’s leading general
contractors and 12,500 specialty—contracting firms. More than 13,000 service providers and suppliers are
associated with AGC through a nationwide network of chapters. Visit the AGC Web site at www.agc.org. AGC
members are “Building Your Quality of Life.”
be uork imc5
nyt mes
corn http://www.riytimes.com/
January 26,2008
Building Costs Deal Blow to Local Budgets
YARDLEY
By
SEATTLE
—
State and local governments in many parts of the country are struggling to pay for roads, bridges
and other building projects because of rising construction costs, adding another burden to budgets already
stressed by the troubled housing market.
The problems have come as many governments pursue ambitious projects to improve roads and airports,
build schools and upgrade long-neglected water and sewer systems. Many of the projects were conceived
when money from property, sales and income taxes was steady and interest rates low, but officials say the
ground has shifted beneath their feet.
“Everybody’s scared,” said Uche Udemezue, director of engineering and transportation for San Leandro,
Calif., which will soon put out a request for construction bids on a retiree center and a parking garage. “You
don’t know what you’re going to find when you go out to bid.”
Costs have jumped for projects as varied as levee construction in New Orleans, Everglades restoration in
Florida and huge sewer system upgrades in Atlanta. The reconstruction of the Interstate 35W bridge in
Minneapolis, a $234 million project, has been fast-tracked for completion by December, and state officials
say it is too soon to know whether it will come in on budget.
The impact has been felt in different regions at different times, and not every project has been high-profile.
In Oregon, high costs have forced the State Department of Transportation to slow the rate at which it
upgrades roads and bridges. In Seattle, school building projects were put on a fast track this fall because of
fears of cost overruns.
“We escalated our project schedule to get ahead,” said Fred Stephens, director of facilities and construction
for Seattle Public Schools.
Nationwide, increasing costs first became a problem for some projects more than two years ago, and in some
regions the rate of increase has dropped in the past year. But some regions are tighter than ever, and the
pressure from the high costs can be more acute in the context of general revenue declines.
The list of culprits for the increases often depends on the rate of growth and construction in a particular
region, with labor costs playing a role along with the rising prices of materials like steel and concrete, and
asphalt, fuel and other petroleum-based products.
Experts say high costs are linked to competition from a global development boom, particularly in China and
India; the housing boom in the United States; and the rush to rebuild after Hurricane Katrina in 2005 and
other recent hurricanes that struck Florida and the Southeast. In the Northwest, public projects have
competed with downtown construction surges in Seattle and Portland. Just across the Canadian border,
hotels and highways are being built to prepare for the 2010 Winter Olympics in Vancouver.
The costs have added to what has become an increasingly bleak economic forecast for many states and local
governments. At least 25 states expect to have budget deficits in 2009, according to the Center on Budget
and Policy Priorities, which estimates the combined budget shortfall for 17 of the states at $31 billion or
more. Many cities, too, see difficult times ahead as revenues wane and costs increase for wages, pensions
and health care.
“We’re talking about all levels of government being in some revenue constraints at a time when the service
costs aren’t going down,” said Chris Hoene, the director of policy and research for the National League of
Cities.
In some places, the news is not all bad. Recent declines in residential construction are beginning to force
contractors to be more competitive when they bid for government work. Yet some government officials see
that as a dubious silver lining.
In Oregon, low bids for recent bridge projects came in at $18 million, about 10 percent below what the state
had projected. That was unimaginable a year ago, but the relief is relative, said Tom Lauer, the major projects
manager for the Transportation Department.
“We’ve been getting hit so hard that we’ve been pumping them up the last couple of years,” Mr. Lauer said
of the state’s internal cost projections.
“I didn’t get a price break,” he said of the recent bid. “I may just have more predictable pricing. I still can’t
afford to do other stuff.”
In Newcastle, a growing Seattle suburb, the situation is emblematic of the struggles confronting towns and
school districts across the country. Two main goals prompted the improvements now under way on a main
thoroughfare, Coal Creek Parkway. Widening a bottleneck on the road would help relieve congestion on
nearby Interstate 405. And doing it with style
installing landscaped medians between lanes
—
—
using steel on a bridge to evoke an old train trestle and
would send the signal that Newcastle is ready to do business.
Then the bids came back. “Slack-jawed,” said John Starbard, the city manager, when asked his reaction to the
bids.
Mr. Starbard said even the project’s engineering consultant, CH2M Hill, was stunned when what they
believed was a very conservative $38 million estimate in March 2007 was met with a low bid of more than
$44 million for a mile’s worth of road and bridge improvements.
But waiting to build was not an option. The city had already received help from Senator Patty Murray,
Democrat of Washington, and state lawmakers, as well as the State Transportation Improvement Board. It
went back to the board and received $2 million more.
“It was a shared sticker shock, but they had seen this with other projects so they were not as surprised,” Mr.
Starbard said of the board.
In Newton, Mass., a Boston suburb with a population of more than 80,000, the estimate for the new Newton
North High School was $104 million in 2004. Four years later, the foundation is about to be poured and the
estimate is now at least $186 million, said Jeremy Solomon, a city spokesman. Mr. Solomon said about $25
million of the increase involved changes to the original plan, for asbestos abatement, adjustments to the
heating and air-conditioning system and other factors. Otherwise, he said, the increase resulted from rising
building costs.
“We kind of got caught in a period where construction costs grew rapidly,” said Mr. Solomon, citing steel and
fuel costs, among others.
The need for public improvements only grows greater. Costs are rising even as engineers across the country
say infrastructure is rapidly decaying.
In San Leandro, a city of 78,000 in the San Francisco Bay Area, Mr. Udemezue said the city could not afford to
delay work on the parking garage and retiree center.
“We can’t wait,” he said, “because we don’t know if the prices are going to come down or go up.”
In the grading guide known as the Pavement Condition Index, zero is not far from a dirt strip and 100 is a
fresh new roadway. When Mr. Udemezue began working for San Leandro 16 years ago, the average road
ranking in the city was nearly 70. Now it is closer to 60, despite what Mr. Udemezue said were the city’s
efforts to keep up maintenance.
Years ago, there was more money in the city’s general revenue stream that could be diverted to help with
basic maintenance, which Mr. Udemezue said required about $5 million a year.
That general revenue now goes to other needs, like public safety, and the roads go wanting, with flat revenue
from gas taxes and other declines leaving about $1.2 million to maintain roads each year. The $13 million
retiree center and the $8 million parking garage have been affected, too, with the city dropping plans to build
commercial space beneath the garage and reducing the space for social programs in the center.
Mr. Udemezue and others say they have heard that things may be stabilizing, but they cannot be sure.
Even in places where the rise of costs has slowed, said Ken Simonson, chief economist with the Associated
General Contractors of America, “it’s dormant at best.”
Cost overru
From Wikipedia, the free encyclopedia
• Learn more about using Wikipedia for research•
Cost overrun is defined as excess of actual cost over budget. Cost overrun is also sometimes
called “cost escalation,” “cost increase,” or “budget overrun.” However, cost escalation and
increases do not necessarily result in cost overruns if cost escalation is included in the budget.
Cost overrun is common in infrastructure, building, and technology projects. One of the most
comprehensive studies [1] of cost overrun that exists found that 9 out of 10 projects had
overrun, overruns of 50 to 100 percent were common, overrun was found in each of 20 nations
and five continents covered by the study, and overrun had been constant for the 70 years for
which data were available. For IT projects, an industry study by the Standish Group (2004)
found that average cost overrun was 43 percent, 71 percent of projects were over budget, over
time, and under scope, and total waste was estimated at US$55 billion per year in the US alone.
Spectacular examples of cost overrun are the Sydney Opera House with 1,400 percent, and the
Concorde supersonic aeroplane with 1,100 percent. The cost overrun of Boston’s Big Dig was
275 percent, or US$1 I billion. The cost overrun for the Channel tunnel between the UK and
France was 80 percent for construction costs and 140 percent for financing costs.
Three types of explanation of cost overrun exist: technical, psychological, and politicaleconomic. Technical explanations account for cost overrun in terms of imperfect forecasting
techniques, inadequate data, etc. Psychological explanations account for overrun in terms of
optimism bias with forecasters. Finally, political-economic explanations see overrun as the result
of strategic misrepresentation of scope and/or budgets.
All of the explanations above can be considered a form of risk. A project’s budgeted costs
should always include cost contingency funds to cover risks (other than scope changes imposed
on the project). As has been shown in cost engineering research [1], poor risk analysis and
contingency estimating practices account for many project cost overruns. Numerous studies
have found that the greatest cause of cost growth was poorly defined scope at the time that the
budget was established. The cost growth (overrun of budget before cost contingency is added)
can be predicted by rating the extent of scope definition, even on complex projects with new
technology.
Cost overrun is typically calculated in one of two ways. Either as a percentage, namely actual
cost minus budgeted cost, in percent of budgeted cost. Or as a ratio, viz, actual cost divided by
budgeted cost. For example, if the budget for building a new bridge was $100 million and the
actual cost was $150 million then the cost overrun may be expressed as 50 percent or by the
ratio 1.5.
COMMODITY PRICE DATA
Commodity
Energy
Coal, Australia
Crudeoil,avg,spot
Crude oil, Brent
Crude oil, Dubai
Crudeoil,WestTexaslnt.
Natural gas Index
Natural gas, Europe
Natural gas, US
Natural gas LNG, Japan
Unit
Annual averages
Jan-Dec Jan-Dec Jan-Apr
2006
2007
2008
Quarterly averages
Jan-Mar Apr-Jun Jul-Sep Oct-Dec Jan.Mar
2007
2007
2007
2007
2008
Monthly averages
Feb
Mar
Apr
2008
2008
2008
j S/mmbtu
$/mmbtu
S/mmbtu
49.09
64.29
65.39
61.43
66.04
181.6
8.47
6.72
7.08
65.73
71.12
72.70
68.37
72.28
186.5
8.56
6.98
7.68
116.25
98.67
100.05
94.35
101.61
243.4
11.19
9.02
10.55
53.19
57.23
58.07
55.58
58.03
187.9
8.51
7.23
6.95
57.91
66.13
68.73
64.71
64.96
186.1
8.00
7.50
7.14
68.37
73.50
75.04
69.97
75.48
174.4
8.34
6.17
7.68
83.47
87.61
88.95
83.21
90.67
197.7
9.37
7.03
8.96
114.00
95.31
96.67
91.30
97.94
235.0
10.86
8.65
10.30
132.00
93.39
94.82
89.96
95.38
233.9
10.84
8.55
10.46
118.25
101.84
103.28
96.78
105.47
246.3
11.04
9.40
10.50
123.00
108.76
110.19
103.47
112.62
268.5
12.19
10.13
11.30
j c/kg
c/kg
c/kg
jc/kg
Jc/kg
L c/kg
c/kg
159.2
252.2
148.9
187.2
191.0
175.4
195.2
195.2
272.4
190.9
203.6
252.2
192.1
166.5
251.0
323.9
246.8
237.0
301.8
187.8
221.2
181.3
267.2
172.8
178.0
226.4
141.5
166.0
200.0
255.1
188.3
199.9
231.1
208.7
159.8
199.9
271.1
200.4
211.0
254.7
211.3
167.1
199.7
296.1
202.1
225.6
296.7
207.1
173.0
247.7
328.5
247.3
234.6
305.2
176.6
221.8
250.4
346.8
254.5
239.7
304.3
173.1
241.7
272.6
330.5
268.8
226.3
306.1
163.2
209.5
260.8
310.2
245.4
244.2
291.6
221.4
219.5
1 S/mt
S/mt
b/S/mt
$Imt
S/mt
S/mt
L$Imt
b/ 5/mt
607
403
970
478
581
209
599
269
919
607
1,352
780
888
307
881
384
1,395
926
2,056
1,161
1.388
450
1,394
562
754
499
1,170
609
678
256
710
318
900
599
1,190
762
876
260
794
338
923
607
1,397
822
917
309
917
396
1,098
724
1,651
928
1,084
402
1,105
485
1,379
914
2.007
1,156
1,375
443
1,384
563
1.382
921
1,958
1,160
1,386
453
1,400
572
1,471
972
2.203
1,249
1,462
443
1,476
575
1,443
963
2.200
1,174
1,428
470
1,425
558
Grains
Barley
$/mt
Maize
5/mt
Rice, Thailand, 5%
L S/mt
Rice, Thailand, 25%
$Imt
Rice, Thailand, 35%
S/mt
*
Rice,Thai, A1.Special / Super S/mt
Sorghum
S/mt
Wheat, Canada
S/mt
Wheat, US, HRW
1 S/mt
WheatUSSRW
S/mt
116.6
121.9
304.9
277.1
272.0
219.5
122.9
216.8
192.0
159.0
172.4
163.7
326.4
306.5
300.1
272.3
162.7
300.4
255.2
238.6
222.1
226.9
585.3
na.
n.a.
522.8
224.1
600.5
399.4
375.1
153.4
170.9
315.6
292.6
285.8
254.5
175.2
232.4
198.4
173.7
167.8
159.4
319.1
297.4
288.8
257.0
151.4
244.7
205.7
187.0
173.8
152.5
327.1
306.5
298.0
265.7
150.7
309.0
274.9
267.5
194.6
171.9
344.0
329.5
327.7
312.0
173.4
415.3
341.9
326.2
216.8
220.4
478.1
na.
n.a.
522.8
218.7
621.7
411.8
384.1
216.4
220.1
464.8
n.a.
na.
432.8
218.5
732.4
425.0
388.7
228.6
234.4
594.0
n.a.
n.a.
537.6
224.9
618.8
439.7
419.6
237.8
246.6
907.0
n.a.
na.
762.7
240.3
537.1
362.2
348.2
Other Food
Bananas EU
Bananas US
Fishmeal
Meat, beef
Meat, chicken
Meat, sheep
Oranges
Shrimp, Mexico
SugarEU domestic
SugarUSdomestic
Sugar, world
897
677
1,166
254.7
138.8
403.6
829
1,024
64.56
48.76
32.59
1,037
676
1,177
260.3
156.7
412.0
957
1,010
68.09
45.77
22.22
1,426
869
1,137
287.1
160.2
462.5
1,136
1,106
75.44
44.93
28.27
1,036
647
1,251
261.2
147.9
394.2
817
988
65.10
45.17
23.49
1,045
705
1,260
259.9
159.3
399.3
893
1,003
66.98
46.47
20.90
999
699
1,123
260.3
163.0
416.5
1,135
1.003
68.28
46.98
21.86
1.068
652
1,075
259.8
156.7
437.9
982
1,045
72.00
44.48
22.61
1.421
836
1,126
282.1
158.8
453.6
1,103
1,103
74.51
44.85
28.42
1,451
792
1,114
283.6
158.7
451.9
1,049
1,105
73.27
44.40
29.78
1,643
1,027
1,161
294.0
162.8
479.4
1,231
1,113
77.14
45.53
29.10
1,440
967
1,168
302.3
164.5
489.3
1,234
1,113
78.22
45.16
27.82
318.5
239.4
595.6
623
749.3
698.6
381.3
268.0
640.7
760
806.3
767.0
537.8
293.0
641.9
1,032
880.5
851.4
371.3
264.8
629.5
720
794.4
727.4
372.8
262.0
639.6
725
807.4
751.3
371.6
269.6
646.7
756
820.9
769.8
409.6
275.5
647.0
838
802.5
819.4
530.8
293.4
640.4
1,036
860.3
850.2
545.7
288.4
639.2
1,083
855.8
849.4
562.8
304.9
640.9
1,069
912.5
856.0
558.9
291.8
646.6
1,021
941.0
855.0
126.7
133.5
231.3
210.8
139.5
142.9
248.0
229.0
167.5
174.3
294.5
277.9
128.8
135.9
241.6
223.3
127.4
130.0
251.6
233.9
148.9
150.3
234.2
213.8
153.0
155.5
264.8
245.1
167.9
174.3
292.6
275.5
165.5
170.0
297.4
281.3
176.8
187.3
298.5
280.9
166.3
174.3
300.3
285.3
Non Energy Commodities
Agriculture
Beverages
Cocoa
Coffee, Arabica
Coffee, robusta
Tea, auctions (3), average
Tea, Colombo auctions
Tea, Kolkata auctions
Tea, Mombasa auctions
Food
Fats and Oils
Coconut oil
Copra
Groundnutoil
Palm oil
Palmkemel oil
Soybean meal
Soybean oil
Soybeans
Raw Materials
Timber
Logs, Cameroon
Logs, Malaysia
Plywood
Sawnwood, Cameroon
Sawnwood, Malaysia
Woodpulp
Other Raw Materials
Cotton A Index
Cotton Memphis
Rubber, US
Rubber, Singapore
S/mt
LS!bbl
$/bbl
a/ $/bbl
1S/bbI
t2ooo,1oo
S/mt
j S/mt
S/mt
L c/kg
j c/kg
c/kg
L S/mt
c/kg
jc/kg
dkg
1c/kg
$/cum
i 5/cum
c/sheets
$/cum
j $/cum
S/mt
t
c/kg
c/kg
c/kg
c/kg
COMMODITY PRICE DATA
Commodity
UnIt
Fertilizers
DAP
Phosphate rock
Potassium chloride
TSP
Urea, E. Europe, bulk
j$/mt
L S/mt
j S/mt
J$/mt
.j S/mt
Metals and Minerals
Aluminum
1 S/mt
Copper
S/mt
$/toz
Gold
c/dmtu
Iron ore
c/kg
Lead
J$/mt
Nickel
c/toz
Silver
**Steel products index Japan j2o00=100
Steelcrcoilsheet.Japan,Reinsj$/mt
Steel hr coilsheet, Japan, Reintj S/mt
Steel,rebar,Japan,ReinstatedS!mt
Steel wire rod, Japan, Reinstatrj S/mt
c/kg
Tin
j c/kg
Zinc
Annual averages
Jan-Dec Jan-Dec Jan-Apr
2006
2007
2008
Quarterly averages
Jan-Mar Apr-Jun Jul-Sep Oct-Dec Jan-Mar
2007
2007
2007
2007
2008
260
44.2
174.5
202
222.9
433
70.9
200.2
339
309.4
267.7
395.2
793
386.0
344
45.5
175.6
226
297.4
2,570
6,722
604.3
77.4
129.0
24,254
1,157
177.6
693.8
600.0
443.8
581.3
878
327.5
2,638
7,118
696.7
84.7
258.0
37,230
1,341
178.1
650.0
550.0
521.5
533.3
1,454
324.2
2,797
8,018
922.5
140.6
288.0
28,908
1.761
226.6
771.9
712.5
677.1
785.5
1,875
238.8
2,801
5,933
650.3
84.7
178.7
41,440
1,332
173.8
650.0
550.0
484.2
500.0
1,273
345.6
945
NEW World Bank commodity price Indices for low and middle
220.9
244.8
Energy
192.1
224.8
Non Energy Commodities
150.4
Agriculture
180.5
145.4
Beverages
169.9
147.0
184.7
Food
137.9
FatsandOils
208.8
149.8
189.0
Grains
156.4
149.0
Other Food
161.4
175.8
RawMaterials
126.0
Timber
136.8
200.0
Other Raw Materials
218.5
168.6
Fertilizers
240.1
280.3
Metals and Minerals
314.0
431
59.9
331
291.3
433
80.0
209.4
375
283.6
522
98.3
230.8
425
365.4
860
234.4
367.7
715
357.6
828
190.0
385.0
729
325.3
1,045
323.1
445.0
876
377.8
1,201
367.5
477.6
1,029
471.3
2.761
7,641
667.4
84.7
217.6
48,055
1,336
175.6
650.0
550.0
540.8
530.0
1,410
366.4
2,546
7,712
681.1
84.7
314.3
30.205
1,273
176.2
650.0
550.0
504.2
550.0
1,498
322.7
2,444
7,188
788.0
84.7
321.5
29,219
1,424
186.7
650.0
550.0
556.8
553.3
1,634
262.3
2.743
7,796
926.8
140.6
289.9
28,957
1,765
221.7
762.5
700.0
639.4
754.0
1,778
243.0
2,777
7,888
922.3
140.6
308.0
27,955
1,767
226.6
800.0
750.0
598.5
725.0
1,721
243.8
3,005
8,439
968.4
140.6
300.9
31,225
1,922
239.6
800.0
750.0
745.0
857.0
1,980
251.1
2,959
8,685
909.7
140.6
282.3
28,763
1,751
241.1
800.0
750.0
790.0
880.0
2,166
226.4
251.1
228.8
183.3
173.3
189.7
216.2
188.3
156.1
172.8
138.9
209.8
240.2
320.8
298.6
237.3
200.9
179.4
212.9
259.1
215.6
149.7
182.8
137.2
232.7
292.0
305.7
331.1
281.4
236.6
210.7
257.2
310.2
274.6
171.9
199.6
146.8
257.3
409.4
358.7
328.4
282.2
238.3
216.4
258.3
313.4
275.3
170.5
200.6
145.7
260.7
384.2
360.8
352.6
301.0
251.8
222.8
276.5
325.5
305.0
186.2
206.4
155.0
262.6
489.9
380.5
376.6
306.3
254.7
213.3
282.5
317.8
340.7
183.5
208.0
157.2
263.6
574.7
381.7
184.8
Income countrles( 2000 =100)
342.4
201.1
228.5
287.6
206.6
226.7
241.1
164.8
173.0
211.3
158.9
167.9
263.5
163.4
172.6
312.1
168.8
191.1
291.1
177.2
174.7
174.8
143.8
146.5
201.7
171.4
176.4
149.4
134.9
136.2
258.9
211.3
220.3
450.7
203.5
224.6
364.4
292.6
337.1
a! Included in the energy index (2000=100)
S
US dollar
mt metric ton
=
0
Monthly averages
Feb
Mar
Apr
2008
2008
2008
b/ Included in the non-energy index (2000=100)
Cl Steel not included in the non-energy index
US cent bbl = barrel cum = cubic meter dmtu = Dry Metric Ton Unit kg = kilogram mmbtu = million British thermal units
toz troy oz n.a. = not available n.q. = no quotation
=
Description of
Price Series
Coal (Australian), thermal, fob. p.ers, Newcastle!Pott Kembla, 6,300 kcalikg (11340 btuflb). less than 0.8%, sulfur 13% ash beginring January 2002;
previously 6.667 kcaVkg (12,000 btuflb). less than 1.0% sulfur, 14% ash
Crude ot (spot), average spot price of Brent, Dubai and West Texas Intermediate, equally weighed
Crude ot (spot), U.K. Brent 38’ API, fob. U.K ports
Crude oti (spot). Dubai Fetch 32’ API, fob Dubai
Crude ci (spot), West Texas Intermediate (Wl’l) 40’ API. f.o.b. k5dland Texas
Natural Gas Index, composite index weighted by coraurnption volumes for Europe, US and Japan Iquefled natural gas (LNG).
Natural Gas (Europe), average Import border price including U.K. for 1991 May, 2000; from June 2000 onwards European Import price excluding U.K
Natural Gas (U.S.), spot price at Henry Hub, Louisiana
Natural gas LNG (Japan). Import price, at, recent two months’ averages are estimates.
-
Cocoa (ICCO), International Cocoa Organation daily price, average of the first three positions on the terminal markets of New York and London,
nearest three future trading months.
Coffee (ICO). International Coffee Organization indicatur price, other mid Arabicas, average New York and BremerVHambLrg markets, ex-dock
Coffee (ICO), International Coffee Orgardzation Indicator price, Robustas, average New York and Le HavrelMarseiies markets, ex-dock
Tea average three auctions, arittrnetic average of quotations at Kolkata, Cotornto and Mornbasalhiairobi.
Tea (Colombo auctions), Sri Laran origIn, at tea, arithmetic average of weekly quotes.
Tea (Kolkata auctions), leaf, include excise duty, arithmetic average of weekly quotes.
Tea (Mombasa,’Nairobl auctions), African origin, al tea, arithmetic average of weekly quotes.
,
Coconut ol (Philippines/Indonesian), bulk, c.I.f. Rotterdam
Copra (PhilippInes/Indonesian), bulk, c.i.f. N.W. Europe
Groundrsit oil (any origin), c.i.f. Rotterdam
Palm oil (Malaysian), 5% bu&, c.l.f. N. W. Europe
Palmkernel Di (Malaysian), c.l.f. Rotterdam
Soybean meal (any origin), Argentine 45/46% exlraction, cit. Rotterdam; prior to 1990. US 44%
Soybean oil (Dutch), crude, f.o.b. ex-mill
Soybeans (US), eLf. Rotterdam
2-
COMMODITY PRICE DATA
Annual averages
Quarterly averages
Jan-Dec Jan-Dec Jan-Apr
Jan-Mar Apr-Jun Jul-Sep Oct-Dec Jan-Mar
Unit
2006
2007
2008
Commodity
2007
2007
2007
2007
2008
Barley (Canadian), feed, Western No. 1, Winnipeg Commodity Exchange, spot, wholesale farmers’ price
Maize (US), no.2, yetow, f.o.b. US Gulf ports
Rice (Thai), 5% broken, white rice (WR), milled, indicative price based on weekly surveys of export transactions, government standard, fob. Bangkok
Rice (ThaI), 25% broken, WR, milled Indicative survey price, government standard, Lob. Bangkok
Rice (Thai), 35% broken, Wit, mlled, indicative survey price, govemment standard, f.o.b. Bangkok
Rice (ThaI), 100% broken, A.l Super from 2006 onwards, broken kernel obtained from the miltng of WR 15%, 20%, and 25%, government standard,
f.o.b. Bangkok; prior to 2006, Al Special also refers to 100% broken rice similar to Al Super, but slightly lower in grade than Al Super.
Sorghum (US), no.2 mile yetow, f.o.b. Gulf ports
Wheat (Canadian), no.1, Western Red Spring (CWRS), in store, St. Lawrence, export price
Wheat (US). no.1, hard red winter, ordinary protein, export price delivered at the Gulf port for prompt or 30 days shipment
Wheat (US). no.2, soft red winter, export price delivered at the Gulf port for prompt or 30 days shipment
Monthly averages
Feb
Mar
Apr
2008
2008
2008
Banaras (Central & South American). major brands, c.i.f. Hamburg
Banares (Central & South American), major brands, US Import price, free on truck (f.o.t.) US Gulf ports
F’ehmeal (any origin), 64-65%, up to December 2003 c&f Hamburg, nis; from January 2004 onwards Breman
Meat, beef (Australian/New ZealandX up to October 2002, cow forequarters, frozen boneinas, 85% chemical lean, c.i.f. U.S. port (East Coast), ex-docic from November,
2002 onwards chucks and cow forequarters
Meat chicken (US), broiler/fryer, whole bIrds, 2-1/2 to 3 pounds. USDA grade A, ice-pecked, Georgia Dock preliminary weighted average, wtrolesale
Meat, sheep (New Zealend frozen whole carcasses Prune Meditsn (PM) beginning January 2006, wholesale, Smithfield, London; prior to January 2006 Prime Light (PL)
Oranges (Mediterranean exporters) navel, EEC indicative unport price, c.i.f. Paris
Shrimp, (Mexican), west coast frozen, white, No.1, shell-on, headtera, 26 to 30 cor,rt per poled, wholesale price at New York
Sugar (EU), European Union negotiated import price for raw unpaciraged sugar from African, Caribbean and Pacific (ACP) under Lome Conventons,
c.l.f. European ports
Sugar (US), import price, nearest future, c.i.f. NewYork
Sugar (world), International Sugar Agreement (ISA) deity price, raw, Lob. end stowed at greater Caribbean ports
Logs (West African), sepele. high quatty (loyal and marchand LM), fob. Douals, Cameroon begtrsiing January 1996, LM 80 centimeter or more
Logs (Malaysian), merenti, Ssrswak, eale price charged by importers, Tokyo; prior to February 1993, average of Ssbsh and Ssrawsk weighted by Japanese
import vokrmes
Plywood (African end Southeest Asian), Leusrt 3-ply, adre, 91 cmx 182cm x4 mm, wtmlesale price, spot Tokyo
Sawrwood (Cemeroonlan), sapele. width 6 inches or more, terrgth 6 feet or more, f.a.a. Cemeroonlan ports
Sswnwood (Malaysian), dark red sereys/meranti. select and better quality, average 7 to 8 inches; length average 12 to 14 inches; thickness 1 to 2 inctr(es);
kiln dry, c. & L UK ports, with 5% agents commission; beginning Jermery 200 indudes premium ($20 to $30) for products of certified sustsfrreble forest
Woodpdp (Swedish), softwood, sulphate, bleached, sir-dry weight c.i.f. North Sea ports
—
Cotton (Cotton Outlook Cottooks, ‘mdcxl, midding 1-3/32 ‘md traded in Far East C/F starting 2006; for
years Northern Europe, c.i.f.
Cotton (US), Memphin/Eeslem, mIddling 1-3/32 inch, c.i.f. Northem Europe. one of the 15 styles based on which the Codook A Index in computed
Rubber (any origin), Ribbed Smoked Sheet (RSS) no. 1 • in bales, Rubber Traders Association (RTA), spot New York
Rubber (Asian), RSS no. 1, in bales, Rubber Association of Singapore Commodity Exchange (RASCE)/ Singapore Commodity Exchange, midday buyers’
asking price for prompt or 30 days delivery prior to June 1992, spot Singapore
DAt’ (diammonkrm phosphate), standard size, bulk, spot fob. US Gui
Phosphate rock (Moroccan), 70% BPL, contract f.a.a. Casablanca
Potassium chloride (muriate of potash), standard grade, spot f.o.b. Vancouver
TSP (triple supemphosphate), upto September 2006 bulk, spot f.o.b. US Gull from October2006 onwerds Tunisian, grenuler, f.o.b.
Urea, (Black See), bulk, spot for 1965-91 (June) fob. Eestem Europe; 1991 (July) onwards f.o.b. Black Sea (primarily Yuzhnw)
Aluminum (LME) London Metal Exchange, unalloyed primary ingota, high grade, minimum 99.7% purity, cash until December 2004; thereafter settlement price
Copper (LME). grade A, minimum 99.9935% purity, cathodes and wire bar shapes, settlement price
Gold (UK). 99.5% fine, London afternoon fixing, average of deity rates
Iron ore (Brezitan), Companhia Vale do Rio Doce (CVRD) Csrejss sinter feed, for years 2005-08, 67.50% Fe (iron) content (dry weight) ores, moisture content 8.0%;
for year 2004, 67.40% Fe; 2000-03, 67.55% Fe, moisture 7.6 8.0 %; contract price to Europe, f.o.b. Ponts da Madeira. Unit dry metric ton unit (dmtu) stands for
mt 1% Fe-unit. To convert price in cants/dmtu to $/dmt SSF (dry ore), multiply by percent Fe content.
Lead (LME), refined, 99.97% purity, settlement price
Nickel (LME), cathodes, minimum 99.8% purity, official morning session, weekly average bid/asked cash until December 2004; thereafter settlement price
Silver (Handy& Harman), 99.9% grade refined, New York
DROPPED due to update difficuttles: Steel products (Belgium), composite price index for eight selected steel products, export, f.o.b., ordinary commercial quality.
REINSTATED Sleet products price index, 2000=100, (Japanese), composite price index for eight selected sleet products besed on quotstiore f.o.b. Japan excluding
shipments to the United States, including China after 2002. weighted by product shares of apparent combined consunpiton (volume of deliveries) at Germany,
Japan and the United Stales. The eight products are as follow. rebar (concrete reinforcing bare). march bar (merchant bars), wire rod, section (H-shape),
plate (medium), hot roted coil/sheet, cold roted cot/sheet and galvanized iron sheet
‘tin (LME), refined, 99.85% purity, settlement price
Zinc (LME). epaulet high grade, minimum 99.995% purity, weekly average bid/asked price, official morning session; prior to April 1990, high grade, minimum 99.95%
ptsity, settlement price
-
* *
Development Prospects Group
Development Economics Vice Presidency
Worid Bank
May 6,2008
1818 H Street, NW. • MSN MC 2-200
Washington, D.C. 20433 U.S.A.
Tel. (202) 473 3862
Emsfl GCMworidbank.org
-
This article presents results from the
first statistically significant study of
cost escalation in transportation in
frastructure projects. Based on a sam
ple of 258 transportation infrastruc
ture projects worth US$90 billion and
representing different project types.
geographical regions, and historical
periods, it is found with overwhelming
statistical significance that the cost es
timates used to decide whether such
projects should be built are highly and
systematically misleadIng. Underesti
mation cannot be explained by error
and is best explained by strategic mis
representation, that is, lying. The pol
icy implications are clear: legislators,
administrators, investors, media rep
resentatives, and members of the pub
lic who value honest numbers should
not trust cost estimates and cost-ben
efIt analyses produced by project pro
moters and their analysts.
Flyvbjerg is a professor of planning with
the Department of Development and Plan
ning. Aalborg University, Denmark. He is
founder and director of the university’s re
search program on transportation infra
structure planning and was twice a Visiting
Fulbright Scholar to the U.S. His latest
books are Rationality and Power (University
of Chicago Press, 1998) and Making Social
Science Matter (Cambridge University Press.
2001). He is currently working on a book
about megaprojects and risk (Cambridge
University Press). Hoim is an assistant pro
fessor of planning with the Department of
Development and Planning. Aalborg Uni
versity, and a research associate with the
university’s research program on transpor
tation infrastructure planning, Her main In
terest is economic appraisal of projects.
Buhi is an associate professor with the De
partment of Mathematics, Aalborg Univer
sity, and an associate statistician with the
university’s research program on transpor
tation infrastructure planning.
Underestimating
Costs in Public
Works Projects
Error or Lie?
Bent Flyvbjerg, Mette Skamris Hoim, and Søren Buhi
C
omparative studies of actual and estimated costs in transportation
infrastructure development are few. Where such studies exist, they are
typically single-case studies or they cover a sample of projects too
small to allow systematic, statistical analyses (Bruzelius et al., 1998; Fouracre
etal., 1990; Hall, 1980; Nijkamp & Ubbels, 1999; Pickrell, 1990; Skamris &
Flyvbjerg, 1997; Szyliowicz & Goetz, 1995; Walmsley & Pickett, 1992). To
our knowledge, only one study exists that, with a sample of 66 transporta
tion projects, approaches a large-sample study and takes a first step toward
valid statistical analysis (Merewitz, 1 973a, 1 973b) ,1 Despite their many mer
its in other respects, these studies have not produced statistically valid an
swers regarding the question of whether one can trust the cost estimates
used by decision makers and investors in deciding whether or not to build
new transportation infrastructure. Because of the small and uneven sam
ples used in existing studies, different studies even point in opposite direc
tions, and researchers consequently disagree regarding the credibility of cost
estimates. Pickrell (1990), for instance, concludes that cost estimates are
highly inaccurate, with actual costs being typically much higher than esti
mated costs, while Nijkamp and Ubbels (1999) claim that cost estimates are
rather correct. Below we will see who is right.
The objective of the study reported here was to answer the following
questions in a statistically valid manner: How common and how large are
differences between actual and estimated costs in transportation infra
structure projects? Are the differences significant? Are they simply random
errors? Or is there a statistical pattern to the differences that suggests other
explanations? What are the implications for policy and decision making re
garding transportation infrastructure development?
lournal of the American Planning Association,
Vol. 68, No.3, Summer 2002. C) American
Planning Association, Chicago, IL,
APA Journal • Surnxner 2002 • Vol. 68, No. 3 279
BENT FLYVBJERG. METE SKAMRIS HOLM. AND SØREN BURL
Four Steps to Understanding
Deceptive Cost Estimation
We see four steps in the evolution of a body of schol
arly research aimed at understanding practices of cost
underestimation and deception in decision making for
transportation infrastructure. The first step was taken
by Pickrell (1990) and Fouracre, A]lport, and Thomson
(1990), who provided sound evidence for a small number
of urban rail projects that substantial cost underestima
tion is a problem, and who implied that such underesti
mation may be caused by deception on the part of pro
ject promoters and forecasters. The second step was
taken by Wachs (1990), who established—again for a
small sample of urban rail projects—that lying, under
stood as intentional deception, is, in fact, an important
cause of cost underestimation. Wachs began the diffi
cult task of charting who does the lying, why it occurs,
what the ethical implications are. etc.
The problem with the research in the first two steps
is that it is based on too few cases to be statistically sig
nificant; the pattern found maybe due to random prop
erties of the small samples involved. This problem is
solved in the third step, taken with the work reported in
this article. Based on a large sample of transportation in
frastructure projects, we show that (1) the pattern of cost
underestimation uncovered by Pickrell and others is of
general import and is statistically significant, and (2) the
pattern holds for different project types, different geo
graphical regions, and different historical periods. We
also show that the large-sample pattern of cost underes
timation uncovered by us lends statistical support to the
conclusions about lying and cost underestimation ar
rived at by Wachs for his small sample.
The fourth and final step in understanding cost un
derestimation and deception would be to do for a large
sample of different transportation infrastructure pro
jects what Wachs did for his small sample of urban rail
projects: establish whether systematic deception actu
ally takes place, who does the deception. why it occurs,
etc. This may be done by having a large number of fore
casters and project promoters, representing a large num
ber of projects, directly express, in interviews or surveys,
their intentions with and reasons for underestimating
costs, This is a key topic for further research.
In sum, then, we do not claim with this article to
have provided final proof that lying is the main cause of
cost underestimation in transportation infrastructure
projects. We claim, however, to have taken one signifi
cant step in a cumulative research process for testing
whether this is the case by establishing the best and
largest set of data about cost underestimation in trans
portation infrastructure planning so far seen, by carry-
280 APA Journal • Summer 2002 • Vol. 68, No. 3
ing out the first statistically significant study of the is
sues involved, and by establishing that our data support
and give statistical significance to theses about lying de
veloped in other research for smaller, statistically non
significant samples.
As part of further developing our understanding of
cost underestimation, it would also be interesting to
study the differences between projects that are approved
on a competitive basis, by voters at an election, and those
that are funded through formula-based allocations. One
may speculate that there is an obvious incentive to make
a project look better, and hence to underestimate costs,
in the campaign leading up to an election. A good sin
gle-case study of this is Kain’s (1990) article about a rail
transit project in Dallas. Votes are cast more often for
large rail, bridge, and tunnel projects than for road pro
jects. For example, most U.S. highway funds are distrib
uted to states based on a formula (i.e., there is no com
petitive process). A state department of transportation
(DOT) is likely to have a fixed annual budget for con
struction. The DOT leadership would presumably want
fairly accurate cost estimates before allocating the bud
get. One may speculate that large cost underestimation
is less likely in this situation. There are exceptions to this
scenario. Sometimes DOT officials want to persuade
state legislators to increase their budget. And states oc
casionally submit bond issue proposals to voters. In Eu
rope, the situation is similar on important points, al
though differences also exist. This may explain the result
found below, that cost underestimation is substantially
lower for roads than for rail, bridges, and tunnels, and
that this is the case both in the U.S. and Europe. Need
less to say, more research is necessary to substantiate this
observation.
Finally, we want to emphasize that although the
project sample used in this study is the largest of its kind,
it is still too small to allow more than a few subdivisions,
if comparative statistical analyses must still be possible.
Therefore, in further work on understanding cost un
derestimation, the sample should be enlarged to better
represent different types of projects and different geo
graphical locations. As to project types, data for more
private projects would be particularly useful in allowing
statistically valid comparisons between public and pri
vate sector projects. Such comparisons do not exist
today, and nobody knows whether private projects per
form better or worse than public ones regarding cost un
derestimation. The sample should also be enlarged to
contain data for more fixed-link and rail projects. Such
data would allow a better (i.e., a statistically corrobo
rated) comparative understanding of cost underestima
tion for more specific subtypes of projects such as
bridges, tunnels, high-speed rail, urban rail, and conven
UNDERESTIMATING COSTS IN PUBLIC WORKS PROJECTS
tional rail. Such an understanding is nonexistent today.
As to geography, immediate rewards would be gained
from data for projects outside Europe and North Amer
ica, especially for fixed links and roads. But even for Eu
rope and North America, data on more projects are
needed to allow better comparative analysis.
Measuring Cost Inaccuracy
The methods used in our study are described in the
Appendix. All costs are construction costs. We follow in
ternational convention and measure the inaccuracy of
cost estimates as so-called “cost escalation” (often also
called “cost overrun”: i.e., actual costs minus estimated
costs in percent of estimated costs). Actual costs are de
fined as real, accounted construction costs determined
at the time of project completion. Estimated costs are de
fined as budgeted, or forecasted, construction costs at the
time of decision to build. Although the project planning
process varies with project type, country, and time, it is
typically possible for any given project to identify a spe
cific point in the process as the time of decision to build.
Usually a cost estimate was available at this point in time
for the decision makers, If not, then the closest available
estimate was used, typically a later estimate resulting in a
conservative bias in our measure for inaccuracy (see the
Appendix).All costs are calculated in fixed prices in Euros
by using the appropriate historical, sectoral, and geo
graphical indices for discounting and the appropriate ex
change rates for conversion between currencies.
Project promoters and their analysts sometimes ob
ject to this way of measuring cost inaccuracy (Flyvbjerg
et al., in press). Various cost estimates are made at dif
ferent stages of the process: project planning, decision
to build, tendering, contracting, and later renegotia
tions. Cost estimates at each successive stage typically
progress toward a smaller number of options, greater de
tail of designs, greater accuracy of quantities, and better
information about unit price. Thus, cost estimates be
come more accurate over time, and the cost estimate at
the time of making the decision to build is far from final.
It is only to be expected, therefore, that such an early es
timate would be highly inaccurate. And this estimate
would be unfair as the basis for assessing the accuracy
of cost forecasting, or so the objection against using the
time-of-decision-to-build estimate goes (Simon, 1991).
We defend this method, however, because when the
focus is on decision making, and hence on the accuracy
of the information available to decision makers, then it
is exactly the cost estimate at the time of making the de
cision to build that is of primary interest. Otherwise it
would be impossible to evaluate whether decisions are
informed or not. Estimates made after the decision to
build are by definition irrelevant to this decision. What
ever the reasons are for cost increases after decision mak
ers give the go-ahead to build a project, or however large
such Increases are, legislators and citizens—or private in
vestors in the case of privately funded projects—are enti
tled to know the uncertainty of budgets. Otherwise
transparency and accountability suffer. We furthermore
observe that if the inaccuracy of early cost estimates were
simply a matter of incomplete information and inher
ent difficulties in predicting a distant future, as project
promoters often say it is, then we would expect inaccu
racies to be random or close to random. Inaccuracies,
however, have a striking and highly interesting bias, as
we will see below.
Another objection to using cost at the time of deci
sion to build as a basis of comparison is that this sup
posedly would entail the classical error of comparing ap
ples and oranges. Projects change over the planning and
implementation process. When, for instance, the physi
cal configuration of the original Los Angeles Blue Line
Light Rail project was altered at substantial cost to com
prise grade-crossing improvements, upgrading of adja
cent streets, better sidewalks, new fences, etc., the pro
ject was no longer the same. It was, instead, a new and
safer project, and comparing the costs of this project
with the costs of the older, less safe one would suppos
edly entail the apples-and-oranges error. A problem with
this argument is that existing research indicates that
project promoters routinely ignore, hide, or otherwise
leave out important project costs and risks in order to
make total costs appear low (Flyvbjerg et al., in press:
Wachs, 1989, 1990). For instance, environmental and
safety concerns may initially be ignored, even though
they will have to be taken into account later in the pro
ject cycle if the project lives on, and the project is more
likely to live on if environmental and safety concerns are
initially ignored. Similarly, ignoring or underplaying
geological risks may be helpful in getting projects ap
proved, and no other risk is more likely to boomerang
back and haunt projects during construction. “Salami
tactics” is the popular name used to describe the prac
tice of introducing project components and risks one
slice at a time in order to make costs appear low as long
as possible. If such tactics are indeed a main mechanism
in cost underestimation, as existing research indicates,
then, clearly, comparing actual project costs with esti
mated costs at the time of decision to build does not en
tail the error of comparing apples and oranges but is
simply a way of tracking how what was said to be a small,
inexpensive apple turned out to actually be a big, expen
sive one,
Finally, we observe that if we were to follow the ob
jections against using the cost estimate at the time of de
APA Journal • Summer 2002 • Vol. 68, No. 3 281
BENT FLYVBJERG. METrE SKAMRIS HOLM, AND SØREN BUHL
cision to build as the basis of tracking cost escalation, it
would be impossible to make meaningful comparisons
of costs because no common standard of comparison
would be available. We also observe that this method Is
the international standard for measuring inaccuracy of
cost estimates (Fouracre et al., 1990; Leavitt et al., 1993;
National Audit Office & Department of Transport,
1992; Nijkamp & Ubbels, 1999; Pickrell, 1990; Walms
ley & Pickett, 1992; World Bank, 1994). This standard
conveniently allows meaningful and consistent com
parisons within individual projects and across projects,
project types, and geographical areas. This standard,
then, is employed below to measure the inaccuracy of
cost estimates in 258 transportation infrastructure pro
jects worth US$90 billion.
Inaccuracy of Cost Estimates
Figure 1 shows a histogram with the distribution of
inaccuracies of cost estimates. If errors in estimating
costs were small, the histogram would be narrowly con
centrated around zero. If errors in overestimating costs
were of the same size and frequency as errors in under
estimating costs, the histogram would be symmetrically
distributed around zero. Neither is the case. We make
the following observations regarding the distribution of
inaccuracies of construction cost estimates:
• Costs are underestimated in almost 9 out of 10
projects. For a randomly selected project, the like
lihood of actual costs being larger than estimated
costs is 86%. The likelihood of actual costs being
lower than or equal to estimated costs is 14%.
• Actual costs are on average 28% higher than
estimated costs (sd=39).
• We reject with overwhelming significance the
thesis that the error of overestimating costs is as
common as the error of underestimating costs
(p.cO.OO1; two-sided test, using the binomial
distribution). Estimated costs are biased, and the
bias is caused by systematic underestimation.
• We reject with overwhelming significance the
thesis that the numerical size of the error of
underestimating costs is the same as the
numerical size of the error of overestimating costs
(p<O.OOl; nonparametric Mann-Whitney test).
Costs are not only underestimated much more
often than they are overestimated or correct, costs
that have been underestimated are also wrong by a
substantially larger margin than costs that have
been overestimated.
We conclude that the error of underestimating costs is
significantly much more common and much larger than
282 APA Journal • Summer 2002 • Vol. 68, No. 3
the error of overestimating costs. Underestimation of
costs at the time of decision to build is the rule rather
than the exception for transportation infrastructure pro
jects. Frequent and substantial cost escalation is the
result.
Cost Underestimation by Project
Type
In this section, we discuss whether different types of
projects perform differently with respect to cost under
estimation. Figure 2 shows histograms with inaccura
cies of cost estimates for each of the following project
types: (1) rail (high-speed; urban: and conventional,
inter-city rail), (2) fixed link (bridges and tunnels), and
(3) road (highways and freeways). Table 1 shows the ex
pected (average) inaccuracy and standard deviation for
each type of project.
Statistical analyses of the data in Table 1 show both
means and standard deviations to be different with a
high level of significance. Rail projects incur the highest
difference between actual and estimated costs, with an
average of no less than 44.7%, followed by fixed-link proj
ects averaging 33.8% and roads at 20.4%. An F-test falsi
fies the null hypothesis at a very high level of statistical
significance that type of project has no effect on per
centage cost escalation (p<O.OO 1). Project type matters.
The substantial and significant differences among proj
ect types indicate that pooling the three types of projects
in statistical analyses, as we did above, is strictly not ap
propriate. Therefore, in the analyses that follow, each
type of project will be considered separately.
Based on the available evidence, we conclude that
rail promoters appear to be particularly prone to cost
underestimation, followed by promoters of fixed-link
projects. Promoters of road projects appear to be rela
tively less inclined to underestimate costs, although ac
tual costs are higher than estimated costs much more
often than not for road projects as well.
Further subdivisions of the sample indicate that
high-speed rail tops the list of cost underestimation, fol
lowed by urban and conventional rail, in that order. Sim
ilarly, cost underestimation appears to be larger for tun
nels than for bridges. These results suggest that the
complexities of technology and geology might have an
effect on cost underestimation. These results are not sta
tistically significant, however. Even if the sample is the
largest of its kind, it is too small to allow repeated sub
divisions and still produce significant results. This prob
lem can be solved only by further data collection from
more projects.
We conclude that the question of whether there are
significant differences in the practice of cost underesti
UNDERESTIMATING COSTS IN PUBLIC WORKS PROJECTS
40
-
TRANSPORTATION INFRASTRUCTURE
PROJECTS (N=255)
U
C
II,
-
I
aI
40
I
I
-40
P
P
I
0
I
40
I
I
I
80
I
I
120
I
160
I
I
I
200
I
I
240
2O
Cost escalation (%)
FIGURE 1. Inaccuracy of cost estimates in 258 transportation infrastructure projects (fixed prices).
TABLE 1. Inaccuracy of transportation project cost estimates by type of project
(fixed prices).
Project type
Number of
cases (N)
Average cost
escalation (%)
Standard
deviation
Level of
significance (p)
Rail
Fixed-link
Road
All projects
58
33
167
258
44.7
33.8
20.4
27.6
38.4
62,4
29.9
38.7
<0.001
<0.004
<0.001
<0.001
APA Journal • Summer 2002 • Vol. 68, No. 3
283
BENT FLYVBJERG, METE SKAMRIS HOLM, AND SØREN BURL
4n-
RAIL PROJECTS (N =58)
cJ
1
;
LL
10
,•
ci’
0.
.
i4( 4
c
cv
‘
&
I1,
0
40
Cnst e
80
1
1ihori
(%)
‘40
2B0
40.
:cj.
FIXED-LINK PROJECTS (N=33)
il9i
LL
-ac
I
-4
I
I
0
eo
120
I
I
I
200
150
240
280
Co5t esckition (%)
50
[lF.
ROAD PROJECTS (N=167)
40
1.-
CI.
0
40
.
80
120
1’0
•
200
Cmt esc&Uon (%)
FIGURE 2. Inaccuracy of cost estimates in rail, fixed-link, and road projects (fixed prices).
284 APA Journal • Summer 2002 • Vol. 68, No. 3
240
20
UNDERESTIMATING COSTS IN PUBLIC WORKS PROJECTS
mation among rail, fixed-link, and road projects must be
answered in the affirmative. The average difference be
tween actual and estimated costs for rail projects is sub
stantially and significantly higher than that for roads,
with fixed-link projects in a statistically nonsignificant
middle position. The average inaccuracy for rail projects
is more than twice that for roads, resulting in average
cost escalations for rail more than double that for roads.
For all three project types, the evidence shows that it is
sound advice for policy and decision makers as well as
investors, bankers, media, and the public to take any
estimate of construction costs with a grain of salt, espe
cially for rail and fixed-link projects.
Cost Underestimation by
Geographical Location
In addition to testing whether cost underestimation
differs for different kinds of projects, we also tested
whether it varies with geographical location among Eu
rope, North America, and “other geographical areas” (a
group of 10 developing nations plus Japan). Table 2
shows the differences between actual and estimated
costs in these three areas for rail, fixed-link, and road pro
jects. There is no indication of statistical interaction be
tween geographical area and type of project. We there
fore consider the effects from these variables on cost
underestimation separately. For all projects, we find that
the difference between geographical areas in terms of un
derestimation is highly significant (p’cO.OO 1). Geography
matters to cost underestimation.
If Europe and North America are compared sepa
rately, which is compulsory for fixed links and roads be
cause no observations exist for these projects in other ge
ographical areas, comparisons can be made by t-tests (as
the standard deviations are rather different, the Welch
version is used). For fixed-link projects, the average dif
ference between actual and estimated costs is 43.4% in
Europe versus 25.7% North America, but the difference
between the two geographical areas is nonsignificant
4 14). Given the limited number of observations and
(p=O.
the large standard deviations for fixed-link projects, we
would need to enlarge the sample with more fixed-link
projects in Europe and North America in order to test
whether the differences might be significant for more
observations. For rail projects, the average difference be
tween actual and estimated costs is 34.2% in Europe ver
sus 40.8% in North America. For road projects, the simi
lar numbers are 22.4% versus 8.4%. Again, the differences
between geographical areas are nonsignificant (p=O.5 10
and p=0.18
, respectively).
4
We conclude, accordingly, that the highly significant
differences we found above for geographical location
come from projects in the “other geographical areas” cat
egory. The average difference between actual and esti
mated costs in this category is a hefty 64.6%.
Have Estimates Improved Over
Time?
In the previous two sections, we saw how cost un
derestimation varies with project type and geography. In
this section, we conclude the statistical analyses by
studying how underestimation has varied over time. We
ask and answer the question of whether project promot
ers and forecasters have become more or less inclined
over time to underestimate the costs of transportation
infrastructure projects. If underestimation were unin
tentional and related to lack of experience or faulty
methods in estimating and forecasting costs, then, a pri
ori, we would expect underestimation to decrease over
time as better methods were developed and more experi
ence gained through the planning and implementation
of more infrastructure projects.
Figure 3 shows a plot of the differences between ac
tual and estimated costs against year of decision to build
TABLE 2. Inaccuracy of transportation project cost estimates by geographical location (fixed prices).
North America
Europe
Project
type
Rail
Fixed-link
Road
All projects
Average
Number
cost
of projects escalation
(N)
(%)
23
15
143
181
34.2
43.4
22.4
25.7
Standard
deviation
25.1
52.0
24.9
28.7
Average
Number
cost
of projects escalation
(N)
(%)
19
18
24
61
40.8
25.7
8.4
23.6
Other geographical areas
Standard
deviation
36.8
70.5
49.4
54.2
Average
Number
cost
of projects escalation
(N)
(%)
16
0
0
16
Standard
deviation
64.6
49.5
—
—
—
—
64.6
49.5
APA Journal • Summer 2002 • Vol. 68, No. 3 285
BENT FLYVBJERG, METrE SKAMRIS HOLM, AND SØREN BUHL
for the 111 projects in the sample for which these data
are available. The diagram does not seem to indicate an
effect from time on cost underestimation. Statistical
analyses corroborate this impression. The null hypothe
sis that year of decision has no effect on the difference
between actual and estimated costs cannot be rejected
, F-test). A test using year of completion instead
22
(p=O.
of year of decision (with data for 246 projects) gives a
similar result (p=O.
8, F-test).
2
We therefore conclude that cost underestimation
has not decreased over time. Underestimation today is
in the same order of magnitude as it was 10, 30, and 70
years ago. If techniques and skills for estimating and
forecasting costs of transportation infrastructure pro
jects have improved over time, this does not show in the
data. No learning seems to take place in this important
and highly costly sector of public and private decision
making. This seems strange and invites speculation that
the persistent existence over time, location, and project
type of significant and widespread cost underestimation
is a sign that an equilibrium has been reached: Strong
incentives and weak disincentives for underestimation
may have taught project promoters what there is to
learn, namely, that cost underestimation pays off. If this
is the case, underestimation must be expected and it
must be expected to be intentional. We examine such
speculation below. Before doing so, we compare cost un
derestimation in transportation projects with that in
other projects.
Cost Underestimation in Other
Infrastructure Projects
In addition to cost data for transportation infra
structure projects, we have reviewed cost data for several
hundred other projects including power plants, dams,
water distribution, oil and gas extraction, information
technology systems, aerospace systems, and weapons
systems (Arditi et al., 1985; Blake et al., 1976; Canaday,
1980; Department of Energy Study Group, 1975;
Dlakwa & Culpin, 1990; Fraser, 1990; Hall, 1980; Healey,
1964; Henderson, 1977; Hufschmidt & Germ, 1970;
Merewitz, 1973b; Merrow, 1988; Morris & Hough, 1987;
World Bank, 1994, n.d.). The data indicate that other
types of projects are at least as, if not more, prone to cost
underestimation as are transportation infrastructure
projects.
Among the more spectacular examples of cost un
derestimation are the Sydney Opera House, with actual
costs approximately 15 times higher than those pro
jected, and the Concorde supersonic airplane, with a cost
12 times higher than predicted (Hall, nd., p. 3). The data
also indicate that cost underestimations for other proj
286 APA Journal • Summer 2002 • Vol. 68, No. 3
ects have neither increased nor decreased historically,
and that underestimation is common in both First- and
Third-World countries. When the Suez canal was com
pleted in 1869, actual construction costs were 20 times
higher than the earliest estimated costs and 3 times
higher than the cost estimate for the year before con
struction began. The Panama Canal, which was com
pleted in 1914, had cost escalations in the range of 70 to
200% (Summers, 1967, p. 148).
In sum, the phenomena of cost underestimation
and escalation appear to be characteristic not only of
transportation projects but of other types of infrastruc
ture projects as well.
Explanations of Underestimation:
Error or Lie?
Explanations of cost underestimation come in four
types: technical, economic, psychological, and political.
In this section, we examine which explanations best fit
our data.
Tethnical Explanations
Most studies that compare actual and estimated
costs of infrastructure projects explain what they call
“forecasting errors” in technical terms, such as imperfect
techniques, inadequate data, honest mistakes, inherent
problems in predicting the future, lack of experience on
the part of forecasters, etc. (Ascher, 1978; Flyvbjerg et al.,
in press; Morris & Rough, 1987; Wachs, 1990). Few
would dispute that such factors may be important
sources of uncertainty and may result in misleading fore
casts. And for small-sample studies, which are typical of
this research field, technical explanations have gained
credence because samples have been too small to allow
tests by statistical methods. However, the data and tests
presented above, which come from the first large-sam
ple study in the field, lead us to reject technical explana
tions of forecasting errors. Such explanations simply do
not fit the data.
First, if misleading forecasts were truly caused by
technical inadequacies, simple mistakes, and inherent
problems with predicting the future, we would expect a
less biased distribution of errors in cost estimates
around zero. In fact, we have found with overwhelming
) that the distribution of
1
statistical significance (p<O.OO
such errors has a nonzero mean. Second, if imperfect
techniques, inadequate data, and lack of experience were
main explanations of the underestimations, we would
expect an improvement in forecasting accuracy over
time, since errors and their sources would be recognized
and addressed through the refinement of data collection,
forecasting methods, etc. Substantial resources have
UNDERESTIMATING COSTS IN PUBLIC WORKS PROJECTS
300
a
0
200
-
o
0
C
0
to
0
C
o
100
$
-
00
0
0
0
00
0
C-,
0
0
0
0
0
C
-1001910
1920
1930
1940
1950
1960
1970
1950
1990
2000
Year of decision Ia build
FIGURE 3. Inaccuracy of cost estimates in transportation projects over time, 1910—1998 (fixed prices, 111
projects).
been spent over several decades on improving data and
methods. Still our data show that this has had no effect
on the accuracy of forecasts. Technical factors, therefore,
do not appear to explain the data. It is not so-called fore
casting “errors” or cost “escalation” or their causes that
need explaining. It is the fact that in 9 out of 10 cases,
costs are underestimated.
We may agree with proponents of technical expla
nations that it is, for example, Impossible to predict for
the individual project exactly which geological, environ
mental, or safety problems will appear and make costs
soar. But we maintain that it is possible to predict the
risk, based on experience from other projects, thatsome
such problems will haunt a project and how this will af
fect costs. We also maintain that such risk can and
should be accounted for in forecasts of costs, but typi
cally is not. For technical explanations to be valid, they
would have to explain why forecasts are so consistent in
ignoring cost risks over time, location, and project type.
Economic Explanations
Economic explanations conceive of cost underesti
mation in terms of economic rationality. Two types of
economic explanation exist; one explains in terms of eco
APA Journal • Summer 2002 • Vol. 68, No. 3
287
BENT FLYVBJERG, METE SKAMRIS HOLM, AND SØREN BURL
nomic self-interest, the other in terms of the public in
terest. As regards self-interest, when a project goes for
ward, it creates work for engineers and construction
firms, and many stakeholders make money. If these
stakeholders are involved in or indirectly influence the
forecasting process, then this may influence outcomes
in ways that make it more likely that the project will be
built. Having costs underestimated and benefits overes
timated would be economically rational for such stakeholders because it would increase the likelihood of reve
nues and profits. Economic self-interest also exists at the
level of cities and states. Here, too, it may explain cost
underestimation. Pickrell (1990, 1992) pointed out that
transit capital investment projects in the U.S. compete
for discretionary grants from a limited federal budget
each year, This creates an incentive for cities to make
their projects look better, or else some other city may get
the money.
As regards the public interest, project promoters and
forecasters may deliberately underestimate costs in order
to provide public officials with an incentive to cut costs
and thereby to save the public’s money. According to this
type of explanation, higher cost estimates would be an
incentive for wasteful contractors to spend more of the
taxpayer’s money. Empirical studies have identified pro
moters and forecasters who say they underestimate costs
in this manner and with this purpose (i.e., to save public
money; Wachs, 1990). The argument has also been
adopted by scholars, for instance Merewitz (1 973b),who
explicitly concludes that “keeping costs low is more im
portant than estimating costs correctly” (p. 280).
Both types of economic explanation account well for
the systematic underestimation of costs found in our
data. Both depict such underestimation as deliberate,
and as economically rational. If we now define a lie in the
conventional fashion as making a statement intended to
deceive others (Bok, 1979, p. 14; Cliffe et al., 2000, p. 3),
we see that deliberate cost underestimation is lying, and
we arrive at one of the most basic explanations of lying,
and of cost underestimation, that exists: Lying pays off,
or at least economic agents believe it does. Moreover, if
such lying is done for the public good (e.g., to save tax
payers’ money), political theory would classify it in that
special category of lying called the “noble lie,” the lie mo
tivated by altruism. According to Bok (1979), this is the
“most dangerous body of deceit of all” (p. 175).
In the case of cost underestimation in public works
projects, proponents of the noble lie overlook an impor
tant fact: Their core argument—that taxpayers’ money is
saved by cost underestimation—is seriously flawed. Any
one with even the slightest trust in cost-benefit analysis
and welfare economics must reject this argument. Un
derestimating the costs of a given project leads to a
288 APA Journal • Summer 2002 • Vol. 68, No. 3
falsely high benefit-cost ratio for that project, which in
turn leads to two problems. First, the project may be
started despite the fact that it is not economically viable.
Or, second, it may be started instead of another project
that would have yielded higher returns had the actual
costs of both projects been known. Both cases result in
the inefficient use of resources and therefore in waste of
taxpayers’ money. Thus, for reasons of economic effi
ciency alone, the argument that cost underestimation
saves money must be rejected; underestimation is more
likely to result in waste of taxpayers’ money. But the ar
gument must also be rejected for ethical and legal rea
sons. In most democracies, for project promoters and
forecasters to deliberately misinform legislators, admin
istrators, bankers, the public, and the media would not
only be considered unethical but in some instances also
illegal, for instance where civil servants would misinform
cabinet members or cabinet members would misinform
the parliament. There is a formal “obligation to truth”
built into most democratic constitutions on this point.
This obligation would be violated by deliberate under
estimation of costs, whatever the reasons may be. Hence,
even though economic explanations fit the data and help
us understand important aspects of cost underestima
tion, such explanations cannot be used to justify it.
Psychological Explanations
Psychological explanations attempt to explain bi
ases in forecasts by a bias in the mental makeup of proj
ect promoters and forecasters. Politicians may have a
“monument complex,” engineers like to build things,
and local transportation officials sometimes have the
mentality of empire builders. The most common psy
chological explanation is probably “appraisal opti
mism.” According to this explanation, promoters and
forecasters are held to be overly optimistic about project
outcomes in the appraisal phase, when projects are
planned and decided (Fouracreetal., 1990, p. 10; Mackie
& Preston, 1998; Walmsley & Pickett, 1992, p. 11; World
Bank, 1994, p. 86). An optimistic cost estimate is clearly
a low one. The existence of appraisal optimism in pro
moters and forecasters would result in actual costs being
higher than estimated costs. Consequently, the existence
of appraisal optimism would be able to account, in
whole or in part, for the peculiar bias of cost estimates
found in our data, where costs are systematically under
estimated. Such optimism, and associated cost under
estimation, would not be lying, needless to say, because
the deception involved is self-deception and therefore
not deliberate. Cost underestimation would be error ac
cording to this explanation.
There is a problem with psychological explanations,
however. Appraisal optimism would be an important
UNDERESTIMATING COSTS IN PUBLIC WORKS PROJECTS
and credible explanation of underestimated costs if esti
mates were produced by inexperienced promoters and
forecasters, i.e., persons who were estimating costs for
the first or second time and who were thus unknowing
about the realities of infrastructure building and were
not drawing on the knowledge and skills of more expe
rienced colleagues. Such situations may exist and may
explain individual cases of cost underestimation. But
given the fact that the human psyche is distinguished by
a significant ability to learn from experience, it seems un
likely that promoters and forecasters would continue to
make the same mistakes decade after decade instead of
learning from their actions. It seems even more unlikely
that a whole profession of forecasters and promoters
would collectively be subject to such a bias and would
not learn over time. Learning would result in the reduc
tion, if not elimination, of appraisal optimism, which
would then result in cost estimates becoming more ac
curate over time. But our data clearly shows that this has
not happened.
The profession of forecasters would indeed have to
be an optimistic group to keep their appraisal optimism
throughout the 70-year period our study covers and not
learn that they were deceiving themselves and others by
underestimating costs. This would account for the data,
but is not a credible explanation. As observed elsewhere,
the incentive to publish andjustify optimistic estimates
is very strong, and the penalties for having been overop
timistic are generally insignificant (Davidson & Huot,
1989, p. 137; Flyvbjerg et al., in press). This is a better ex
planation of the pervasive existence of optimistic esti
mates than an inherent bias for optimism in the psyche
of promoters and forecasters. And “optimism” calcu
lated on the basis of incentives is not optimism, of
course; it is deliberate deception. Therefore, on the basis
of our data, we reject appraisal optimism as a primary
cause of cost underestimation.
Political Explanations
Political explanations construe cost underestima
tion in terms of interests and power (Flyvbjerg, 1998).
Surprisingly little work has been done that explains the
pattern of misleading forecasts in such terms (Wachs,
1990, p. 145). A key question for political explanations is
whether forecasts are intentionally biased to serve the in
terests of project promoters in getting projects started.
This question again raises the difficult issue of lying.
Questions of lying are notoriously hard to answer, be
cause in order to establish whether lying has taken place,
one must know the intentions of actors. For legal, eco
nomic, moral, and other reasons, if promoters and fore
casters have intentionally fabricated a deceptive cost
estimate for a project to get it started, they are unlikely to
tell researchers or others that this is the case (Flyvbjerg,
1996; Wachs, 1989).
When Eurotunnel, the private company that owns
the tunnel under the English Channel, went public
in 1987 to raise funds for the project, investors were
told that building the tunnel would be relatively straight
forward. Regarding risks of cost escalation, the prospec
tus read:
Whilst the undertaking of a tunneling project of
this nature necessarily involves certain construc
tion risks, the techniques to be used are well
proven.
The Directors, having consulted the
Maitre d’Oeuvre, believe that 10%. would be a
reasonable allowance for the possible impact of un
foreseen circumstances on construction costs.
2
(‘Under Water,’ 1989, p.37)
.
.
.
.
.
Two hundred banks communicated these figures for
cost and risk to investors, including a large number of
small investors. As observed by The Economist (“Under
Water,” 1989), anyone persuaded in this way to buy
shares in Eurotunnel in the belief that the cost estimate
was the mean of possible outcomes was, in effect, de
ceived. The cost estimate of the prospectus was a best
possible outcome, and the deception consisted in mak
ing investors believe in the highly unlikely assumption—
disproved in one major construction project after an
other—that everything would go according to plan, with
no delays; no changes in safety and environmental per
formance specifications; no management problems; no
problems with contractual arrangements, new tech
nologies, or geology; no major conflicts; no political
promises not kept; etc. The assumptions were, in other
words, those of an ideal world. The real risks of cost es
calation for the Channel tunnel were many times higher
than those communicated to potential investors, as evi
denced by the fact that once built, the real costs of the
project were higher by a factor of two compared with
forecasts.
Flyvbj,erg, Bruzelius, and Rothengatter (in press)
document for a large number of projects that the Every
thing-Goes-According-to-Plan type of deception used
for the Channel tunnel is common. Such deception is,
in fact, so widespread that in a report on infrastructure
and development, the World Bank (1994, pp. ii, 22)
found reason to coin a special term for it: the “EGAP
principle.” Cost estimation following the EGAP-princi
pie simply disregards the risk of cost escalation result
ing from delays, accidents, project changes, etc. This is a
major problem in project development and appraisal, ac
cording to the World Bank.
It is one thing, however, to point out that investors,
public or private, were deceived in particular cases. It is
APA Journal • Summer 2002 • Vol. 68, No. 3 289
BENT FLYVBJERG. MEUE SKAMRIS HOLM, AND SØREN BUHL
quite another to get those involved in the deceptions to
talk about this and to possibly admit that deception was
intentional, i.e., that it was lying. We are aware of only
one study that actually succeeded in getting those in
volved in underestimating costs to talk about such is
sues (Wachs, 1986, 1989, 1990). Wachs interviewed pub
lic officials, consultants, and planners who had been
involved in transit planning cases in the U.S. He found
that a pattern of highly misleading forecasts of costs and
patronage could not be explained by technical issues and
were best explained by lying. In case after case, planners,
engineers, and economists told Wachs that they had had
to ‘cook” forecasts in order to produce numbers that
would satisfy their superiors and get projects started,
whether or not the numbers could be justified on tech
nical grounds (Wachs, 1990, p. 144). One typical plan
ner admitted that he had repeatedly adjusted the cost
figures for a certain project downward and the patronage
figures upward to satisfy a local elected official who
wanted to maximize the chances of getting the project
in question started. Wachs’ work is unusually penetrat
ing for a work on forecasting. But again, it is small-sam
ple research, and Wachs acknowledges that most of his
evidence is circumstantial (Wachs, 1986, p. 28). The evi
dence does not allow conclusions regarding the project
population. Nevertheless, based on the strong pattern
of misrepresentation and lying found in his case stud
ies, Wachs goes on to hypothesize that the type of abuse
he has uncovered is “nearly universal” (1990, p. 146;
1986, p. 28) and that it takes place not only in transit
planning but also in other sectors of the economy where
forecasting routinely plays an important role in policy
debates.
Our data give support to Wachs’ claim. The pattern
of highly underestimated costs is found not only in the
small sample of projects Wachs studied; the pattern is
statistically significant and holds for the project popu
lation mean (i.e., for the majority of transportation in
frastructure projects). However, on one point, Wachs
(1986) seems to draw a conclusion somewhat stronger
than is warranted. ‘[F] orecasted costs always seem to be
lower than actual costs” (p. 24) he says (emphasis in orig
inal). Our data show that although “always” (100%) may
cover the small sample of projects Wachs chose to study,
when the sample is enlarged by a factor of 20—30 to a
more representative one, “only” in 86% of all cases are
forecasted costs lower than actual costs. Such trifles—14
percentage points—apart, the pattern identified by Wachs
is a general one, and his explanation of cost underesti
mation in terms of lying to get projects started fit our
data particularly well. Of the existing explanations of
cost development in transportation infrastructure pro
jects, we therefore opt for political and economic expla
290 APA Journal • Summer 2002 • Vol. 68, No. 3
nations. The use of deception and lying as tactics in
power struggles aimed at getting projects started and at
making a profit appear to best explain why costs are
highly and systematically underestimated in transpor
tation infrastructure projects.
Summary and Conclusions
The main findings from the study reported in this
article—all highly significant and most likely conserva
tive—are as follows:
• In 9 out of 10 transportation Infrastructure
projects, costs are underestimated.
• For rail projects, actual costs are on average 45%
higher than estimated costs (sd=38).
• For fixed-link projects (tunnels and bridges),
actual costs are on average 34% higher than
estimated costs (sd=62).
• For road projects, actual costs are on average 20%
higher than estimated costs (sd=30).
• For all project types, actual costs are on average
28% higher than estimated costs (sd=39).
• Cost underestimation exists across 20 nations
and 5 continents; it appears to be a global
phenomenon.
• Cost underestimation appears to be more
pronounced in developing nations than in
North America and Europe (data for rail projects
only).
• Cost underestimation has not decreased over the
past 70 years. No learning that would improve
cost estimate accuracy seems to take place.
• Cost underestimation cannot be explained by
error and seems to be best explained by strategic
misrepresentation, i.e., lying.
• Transportation infrastructure projects do not
appear to be more prone to cost underestimation
than are other types of large projects.
We conclude that the cost estimates used in public
debates, media coverage, and decision making for trans
portation infrastructure development are highly, sys
tematically, and significantly deceptive. So are the costbenefit analyses into which cost estimates are routinely
fed to calculate the viability and ranking of projects. The
misrepresentation of costs is likely to lead to the misal
location of scarce resources, which, in turn, will produce
losers among those financing and using infrastructure,
be they taxpayers or private investors.
We emphasize that these conclusions should not be
interpreted as an attack on public (vs. private) spending
on infrastructure, since the data are insufficient to de
cide whether private projects perform better or worse
UNDERESTIMATING COSTS IN PUBLIC WORKS PROJECTS
than public ones regarding cost underestimation. Nor
do the conclusions warrant an attack on spending on
transportation vs. spending on other projects, since
other projects appear to be as liable to cost underesti
mation and escalation as are transportation projects.
With transportation projects as an in-depth case study,
the conclusions simply establish that significant cost un
derestimation is a widespread practice in project devel
opment and implementation, and that this practice
forms a substantial barrier to the effective allocation of
scarce resources for building important infrastructure.
The key policy implication for this consequential
and highly expensive field of public policy is that those
legislators, administrators, bankers, media representa
tives, and members of the public who value honest num
bers should not trust the cost estimates presented by
infrastructure promoters and forecasters. Another im
portant implication is that institutional checks and bal
ances—including financial, professional, or even crimi
nal penalties for consistent or foreseeable estimation
errors—should be developed to ensure the production
of less deceptive cost estimates. The work of designing
such checks and balances has been begun elsewhere,
with a focus on four basic instruments of accountability:
(1) increased transparency, (2) the use of performance
specifications, (3) explicit formulation of the regulatory
regimes that apply to project development and imple
mentation, and (4) the involvement of private risk capi
tal, even in public projects (Bruzelius et al., 1998; Flyv
bjerg et al., in press).
ACKNOWLEDGMENTS
The authors wish to thank Martin Wachs, Don Pickrell, and
three anonymous JAPA referees for valuable comments on an
earlier draft of the article. Research for the article was sup
ported by the Danish Transport Council and Aalborg Univer
sity, Denmark.
NOTES
1. Merewitz’s (1 973a, 1 973b) study compared cost overrun
in urban rapid transit projects, especially the San Fran
cisco Bay Area Rapid Transit (BART) system, with over
run in other types of public works projects. Merewltz’s
aims were thus different from ours, and his sample of
transportation projects was substantially smaller: 17
rapid transit projects and 49 hIghway projects, compared
with our 58 rail projects, 167 highway projects, and 33
bridge or tunnel projects. In addition to issues of a small
sample, in our attempt to replicate Merewitz’s analysis we
found that his handling of data raises a number of other
issues. First, Merewitz did not correct his cost data for in
flation, i.e., current prices were used instead of fixed ones.
This is known to be a major source of error due to varying
inflation rates between projects and varying duration of
construction periods. Second, in statistical tests, Mere
witz compared the mean cost overrun of subgroups of
projects (e.g., rapid transit) with the grand mean of over
run for all projects, thus making the error of comparing
projects with themselves. Subgroups should be tested di
rectly against other subgroups in deciding whether they
differ at all and, if so, which ones differ. Third, Merewitz’s
two reports (1973a, 1973b) are inconsistent. One (1973a)
calculates the grand mean of cost overrun as the average
of means for subgroups: that is. the grand mean is un
weighted, where common practice is to use the weighted
mean, as appears to be the approach taken in the other
(1973b). Fourth, due to insufficient information, the p
values calculated by Merewitz are difficult to verify; most
likely they are flawed, however, and Merewitz’s one-sided
p-values are misleading. Finally, Merewitz used a debat
able assumption about symmetry, which has more impact
for the nonparametric test used than nonnormality has
for parametric methods. Despite these shortcomings, the
approach taken in Merewitz’s study was innovative for its
time and in principle pointed in the right direction re
garding how to analyze cost escalation in public works
projects. The study cannot be said to be a true large-sam
ple study for transportation infrastructure, however, and
its statistical significance is unclear.
2. The Maitre d’Oeuvre was an organization established to
monitor project planning and implementation for the
Channel tunnel. It was established in 1985. and until 1988
it represented the owners. In 1988 it was reverted to an
impartial position (Major Projects Association, 1994, pp.
151—153).
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APPENDIX
The first task of the research reported in this paper
was to establish a sample of infrastructure projects sub
stantially larger than what is common in this area of re
search, a sample large enough to allow statistical analy
ses of costs. Here a first problem was that data on actual
costs in transportation infrastructure projects are rela
tively difficult to come by. One reason is that it is quite
time consuming to produce such data. For public sector
projects, funding and accounting procedures are typi
cally unfit for keeping track of the multiple and complex
changes that occur in total project costs over time. For
large projects, the relevant time frame may cover 5, 10, or
more fiscal years from decision to build, until construc
tion starts, until the project is completed and operations
begin. Reconstructing the actual total costs of a public
project, therefore, typically entails long and difficult ar
chival work and complex accounting. For private pro
jects, even if funding and accounting practices may be
more conducive to producing data on actual total costs,
such data are often classified to keep them from the
hands of competitors. Unfortunately, this also tends to
keep data from the hands of scholars. And for both pub
lic and private projects, data on actual costs may be held
back by project owners because more often than not, ac
tual costs reveal substantial cost escalation, and cost es
calation is normally considered somewhat of an embar
rassment to promoters and owners. In sum, establishing
reliable data on actual costs for even a single transporta
tion infrastructure project is often highly time consum
ing or simply impossible.
This state of affairs explains why small-sample stud
ies dominate scholarship in this field of research. But de
spite the problems mentioned, after 4 years of data col
lection and refinement, we were able to establish a sample
of 258 transportation infrastructure projects with data
on both actual construction costs and estimated costs at
the time of decision to build. The project portfolio is
worth approximately US$90 billion (1995 prices). The
project types are bridges, tunnels, highways, freeways,
high-speed rail, urban rail, and conventional (interurban)
rail. The projects are located in 20 countries on 5 conti
nents, including both developed and developing nations.
The projects were completed between 1927 and 1998.
Older projects were included in the sample in order to
test whether the accuracy of estimated costs improved
over time. The construction costs of projects range from
US$1.5 million to US$8.5 billion (1995 prices),with the
smallest projects typically being stretches of roads in
larger road schemes, and the largest projects being rail
links, tunnels, and bridges. As far as we know, this is the
largest sample of projects with data on cost development
that has been established in this field of research.
In statistical analysis, data should be a sample from
a larger population, and the sample should represent the
population properly. These requirements are ideally sat
isfied by drawing the sample by randomized lot. Ran
domization ensures with high probability that factors
that cannot be controlled are equalized. A sample should
also be designed such that the representation of sub
groups corresponds to their occurrence and importance
in the population. In studies of human affairs, however,
where controlled laboratory experiments often cannot
be conducted, it is frequently impossible to meet these
ideal conditions. This is also the case for the current
study, and we therefore had to take a different approach
to sampling and statistical analysis.
We selected the projects for the sample on the basis
of data availability. All projects that we knew of for which
data on construction cost development were obtainable
were considered for inclusion in the sample. Cost devel
opment is defined as the difference between actual and
estimated costs in percentage of estimated costs, with all
costs measured in fixed prices. Actual costs are defined
as real, accounted costs determined at the time of com
pleting a project. Estimated costs are defined as bud
geted, or forecasted, costs at the time of decision to build.
Even if the project planning process varies with project
type. country, and time, it is typically possible to locate
for any given project a specific point in the process that
can be identified as the time of decision to build. Usually
a cost estimate was available for this point in time. If not,
the closest available estimate was used, typically a later
estimate resulting in a conservative bias in our measure
ment of cost development. Cost data were collected from
a variety of sources, including annual project accounts,
questionnaires, interviews, and other studies.
APA Journal • Summer 2002 • Vol. 68, No. 3
293
BENT FLYVBJERG, METE SKAMRIS HOLM, AND SØREN BUHL
Data on cost development were available for 343
projects. We then rejected 85 projects because of insuffi
cient data quality. For instance, for some projects we
could not obtain a clear answer regarding what was in
cluded in costs, or whether cost data were given in cur
rent or fixed prices, or which price level (year) had been
used in estimating and discounting costs. More specifi
cally, of those 85 projects, we rejected 27 because we
could not establish whether or not cost data were valid
and reliable. We rejected 12 projects because they had
been completed before 1915 and no reliable indices were
available for discounting costs to the present. Finally, we
excluded 46 projects because cost development for them
turned out to have been calculated before construction
was completed and operations begun: therefore, the ac
tual final costs for these projects may be different from
the cost estimates used to calculate cost development,
and no information was available on actual final costs. In
addition to the 85 rejected projects mentioned here, we
also rejected a number of projects to avoid double count
ing of projects. This typically involved projects from
other studies that appeared in more than one study or
where we had a strong suspicion that this might be the
case. In sum, all projects for which data were considered
valid and reliable were included in the sample. This cov
ers both projects for which we ourselves collected the
data and projects for which other researchers in other
studies did the data collection (Fouracre et al., 1990:
Hall, 1980: Leavitt et al., 1993; Lewis, 1986; Merewitz,
1973a; National Audit Office, Department of Transport,
1985, 1992: National Audit Office, Department of
Transport, Scottish Development Department, & Welsh
Office, 1988; Pickrell, 1990; Riksrevisionsverket, 1994;
Vejdirektoratet, 1995: Walmsley & Pickett, 1992). Cost
data were made comparable across projects by discount
ing prices to the 1995 level and calculating them in
Euros, using the appropriate geographical, sectoral, and
historical indices for discounting and the appropriate
exchange rates for conversion between currencies.
Our own data collection concentrated on large Eu
ropean projects because too few data existed for this type
of project to allow comparative studies. For instance, for
projects with actual construction costs larger than 500
million Euros (1995 prices: EUR1=US$ 1.29 in 1995), we
were initially able to identify from other studies only two
European projects for which data were available on both
actual and estimated costs. If we lowered the project size
and looked at projects larger than 100 million Euros, we
were able to identify such data for eight European pro
jects. We saw the lack of reliable cost data for European
projects as particularly problematic since the Commis
sion of the European Union hadjust launched its policy
for establishing the so-called trans-European transport
294 APA Journal • Summer 2002 • Vol. 68, No. 3
networks, which would involve the construction of a
large number of major transportation infrastructure
projects across Europe at an initial cost of 220 billion
Euros (Commission of the European UnIon, 1993, p.
75). As regards costs, we concluded that the knowledge
base for the Commission’s policy was less than well de
veloped, and we hoped to help remedy this situation
through our data collection. Our efforts on this point
proved successful. We collected primary data on cost for
37 projects in Denmark, France, Germany, Sweden, and
the U.K. and were thus able to greatly increase the num
ber of large European projects with reliable data for both
actual and estimated costs, allowing for the first time a
comparative study for this type of project in which sta
tistical methods could be applied.
As for any sample, a key question is whether the sam
ple is representative of the population. Here the ques
tion is whether the projects included in the sample are
representative of the population of transportation in
frastructure projects. Since the criterion for sampling
was data availability, this question translates into one of
whether projects with available data are representative.
There are four reasons why this is probably not the case.
First, it may be speculated that projects that are man
aged well with respect to data availability may also be
managed well in other respects, resulting in better than
average (i.e., nonrepresentative) performance for such
projects. Second, it has been argued that the very exis
tence of data that make the evaluation of performance
possible may contribute to improved performance when
such data are used by project management to monitor
projects (World Bank, 1994, p. 17). Again, such projects
would not be representative of the project population.
Third, we might speculate that managers of projects
with a particularly bad track record regarding cost esca
lation have an interest in not making cost data available,
which would then result in underrepresentation of such
projects in the sample. Conversely, managers of projects
with a good track record for costs might be interested in
making this public, resulting in overrepresentation of
these projects. Fourth, and finally, even where managers
have made cost data available, they may have chosen to
give out data that present their projects in as favorable a
light as possible. Often there are several estimates of
costs to choose from and several calculations of actual
costs for a given project at a given time. If researchers col
lect data by means of survey questionnaires, as is often
the case, there might be a temptation for managers to
choose the combination of actual and estimated costs
that suits them best, possibly a combination that makes
their projects look good.
The available data do not allow an exact, empirical
assessment of the magnitude of the problem of misrep
UNDERESTIMATING COSTS IN PUBLIC WORKS PROJECTS
resentation. But the few data that exist that shed light on
this problem support the thesis that data are biased.
When we compared data from the Swedish Auditor Gen
eral for a subsample of road projects, for which the prob
lems of misrepresentation did not seem to be an issue,
with data for all road projects in our sample, we found
that cost escalation in the Swedish subsample is signifi
cantly higher than for all projects (Holm, 1999, pp. 11—
15). We conclude, for the reasons given above, that most
likely the sample is biased and the bias is conservative. In
other words, the difference between actual and estimated
costs derived from the sample is likely to be lower than
the difference in the project population. This should be
kept in mind when interpreting the results from statisti
cal analyses of the sample. The sample is not perfect by
any means. Still it is the best obtainable sample given the
current state of the art in this field of research.
In the statistical analyses, percentage cost develop
ment in the sample is considered normally distributed
unless otherwise stated. Residual plots, not shown here,
indicate that normal distribution might not be com
pletely satisfied, the distributions being somewhat
skewed with larger upper tails. However, transforma
tions (e.g., the logarithmic one) do not improve this sig
nificantly. For simplicity, therefore, no transformation
has been made, unless otherwise stated.
The subdivisions of the sample implemented as part
of analyses entail methodological problems of their own.
Thus the representation of observations in different
combinations of subgroups is quite skewed for the data
considered. The analysis would be improved consider
ably if the representation were more even. Partial and
complete confounding occur; that is, if a combination
of two or more effects is significant, it is sometimes dif
ficult to decide whether one, the other, or both cause the
difference. For interactions, often not all the combina
tions are represented, or the representations can be quite
scarce. We have adapted our interpretations of the data
to these limitations, needless to say. If better data could
be gathered, sharper conclusions could be made.
The statistical models used are linear normal models
(i.e., analysis of variance and regression analysis with the
appropriate F-tests and t-tests). The tests of hypotheses
concerning mean values are known to be robust to devi
ations from normality. Also, chi-square tests for inde
pendence have been used for count data. For each test,
the p-value has been reported. This value is a measure
for rareness if identity of groups is assumed. Tradition
ally, a p-value less than 0.01 is considered highly signifi
cant and less than 0.05 significant, whereas a larger p
value means that the deviation could be due to chance.
APA Journal • Summer 2002 • Vol. 68, No. 3 295