introduction to the canback global income distribution database (c

INTRODUCTION TO THE CANBACK GLOBAL
INCOME DISTRIBUTION DATABASE (C-GIDD)
May 2016
MANAGEMENT
CONSULTING
THROUGH
SCIENCE
EIU CANBACK
Boston, Massachusetts
www.canback.com
+1-617-399-1300
Agenda
Introduction to EIU Canback
C-GIDD Classic
C-GIDD extensions
Leveraging C-GIDD in consulting work
Appendix: C-GIDD geographic coverage
2
EIU Canback is an elite management consulting firm
anchored in science, predictive analytics, and consumer
market knowledge.
We serve clients through five practices: Strategy, M&A Due
Diligence, Growth, Operations, and Organizational
Performance.
We operate globally with the world’s largest companies as
clients. This has taken us to 77 countries since our
founding in 2004.
We also offer analytic services with the Canback Global
Income Distribution Database (C-GIDD) as our flagship
product.
EIU Canback is a subsidiary of The Economist Group since
2015.
3
Canback is the leader in scientific and quantitative management consulting, and in particular the
use of predictive analytics, which bring better results to organizations
MANAGEMENT CONSULTING INDUSTRY S-CURVE
A new approach
with higher
performance
Performance
Scientific and
quantitative
management
consulting
Few, if any, breakthroughs since the
early 1990s
Traditional
management
consulting
1900
1960
1990
2016
Canback is the best-known firm in management consulting
based on science
4
Canback is often cited in the press, research reports, annual reports, and investor presentations by
some of the largest companies and organizations in the world
Quarterly divisional seminar: Africa (2015)
Quarterly divisional seminar: South Africa (2014)
Quarterly divisional seminar: Asia-Pacific (2013)
Mapping the Path to Future Prosperity:
Emerging Markets Growth Index (2014)
Chinese politics: A crisis of faith (2016)
Hot spots: Benchmarking Global City
Competitiveness (2012)
E-Trade: Opening the Wallets of 2.8
Billion People (2015)
Abuja +12: Shaping the Future of Health
in Africa (2013)
2014 New York Analyst Day (2014)
Contextualising the Mass Market
Banking Opportunity (2011)
Consolidated Annual Report (2012)
The Shifting Urban Economic Landscape:
What Does it Mean for Cities? (2013)
The Future of Retailer Brands (2010)
Annual Results Presentation (2013)
Amfiteatru Economic: Income Distribution
Determinants and Inequality (2014)
Constructing Official Inequality Poverty Lines for
Countries in Transition (2014)
5
Canback’s focus is management consulting, but we also offer related services. Each service line
has predictive analytics based on the scientific method at its core
Strategy
development
40%
Management
consulting
75%
M&A due diligence
35%
Canback
Predictive
modeling
10%
Research
5%
Data
10%
We pioneered, and are still the
world’s only provider of GDP and
income data at the subdivision
and city level: C-GIDD
6
Canback has offices in twelve key markets. From these offices we have worked on the ground in
58 countries. The core offices have full-time Canback employees
CANBACK OFFICES
Core office
Satellite office
Tokyo
Jakarta
Sao Paulo
Mexico City
Singapore
Shanghai
Dubai
Chicago
Johannesburg
Beijing
London
Boston
OFFICE CAPABILITIES
Management
consulting
Predictive
analytics
C-GIDD
Research
7
Canback has worked on the ground in 77 countries and done in-country projects in 58 of those,
helping clients draw reliable, fact-based conclusions through data-driven analyses
GLOBAL FOOTPRINT
Global projects: 14%
Europe: 7%
United States: 7%
Mid America: 11%
Asia: 8%
Africa: 24%
South America: 30%
Core office
Satellite office
Country projects
Consultants work travel
8
Agenda
Introduction to EIU Canback
C-GIDD Classic
C-GIDD extensions
Leveraging C-GIDD in consulting work
Appendix: C-GIDD geographic coverage
9
Data from C-GIDD have been purchased by companies from a wide range of industry areas
since the database launched in 2008. Here we highlight some of our repeat customers
10
The Canback Global Income Distribution Database (C-GIDD) is used to quantify market size and
demand drivers. C-GIDD is the only commercial database of its kind in the world
C-GIDD COVERAGE
EXAMPLES OF C-GIDD USES
• The world's only database with complete
subnational data series
• Quantify number of households at
specific income or socioeconomic levels
• GDP, household income, size of income
brackets, size of socioeconomic classes,
population
• Compare consumer market sizes across
geographies in a uniform way
• 213 countries, 696 subdivisions and 997 cities
• Merge with category or sales data to spot
new or under-developed opportunities
• Subnational: 2001-2026
National: 1970-2036
EXPLANATORY POWER OF C-GIDD
Demand variance explained by income above
category-specific thresholds
C-GIDD MODULES
Televison sets
C-GIDD
income
distribution
data
Available as a
commercial
service at
cgidd.com
Oil consumption
Cellphone subscribers
C-GIDD
economic,
demographic,
social and
psychographic
data
C-GIDD
benchmark
products and
services data
Internal to
Canback
Internal to
Canback
Internet users
Personal computers
McDonald's restaurants
Milk consumption
Cash machines (ATMs)
Insurance premiums
Bank deposits
Electricity consumption
Airline passengers
0.00
0.50
1.00
R2
11
C-GIDD draws on more than 1,600 data sources which are harmonized and econometrically
analyzed to extract the most information as possible at the city or subdivision level
FROM DISCRETE AND INCOMPLETE SOURCES
THROUGH PROPRIETARY
HARMONIZATION AND PROJECTION
TECHNIQUES
TO UP-TO-DATE, HARMONIZED AND
COMPREHENSIVE DATABASE WITH A
SIMPLE AND INTUITIVE INTERFACE
UN and national household
economic surveys
• Population data
• GDP
• Household income data
Sophisticated
econometric models to
find true income at city
level
IMF
• Short and medium term economic
projections
UN and US Census Bureau
• Population projections
Proprietary purchasing
power and cost-of-living
adjustments
C-GIDD
WIDER and national surveys
• Income distributions
National statistics offices
Proprietary income
distribution algorithms
• City and other subdivision data
UN, Eurostat, CityPopulation
and national censuses
• City data
International Comparison
Program (ICP)
Robust income
projection algorithms
• PPP data
12
C-GIDD contains detailed income distribution data at varying geographic levels, including 1,000
cities. It allows the user to analyze populations and households in specific cities and at certain
income levels – today, in the past, and in the future
C-GIDD’s data includes values in US
dollars, local currency, and PPP*
Total GDP in PPP$ trillions
Millions of households with income higher than PPP$ 20,000
2005 constant values
2005 constant values
2014
Shanghai
2019
EU
14.0
US
13.8
China
Japan
4.1
16.1
India
4.4
2.8
3.0
2.1
17.6
4.3
4.0
5.1
15.3
11.7
Mumbai
1.6
1.1
0.7
2004 2009 2014 2019
2004 2009 2014 2019
6.0
Millions of middle-class households by location in 2014
Income per household in Egypt in 2014
Socioeconomic levels A, B, C+ and C
Egyptian Pounds, 2014 current values
Major Cities
Other Urban
Brazil
5.5
Mexico
5.6
2.5
Argentina
Colombia
Chile
1.2
0.5
1.1
0.2
0.8 0.5 0.1
* Purchasing power parity dollars
3.1
1.8
0.1
121,382
Cairo
Rural
0.6
0.7
99,097
Alexandria
88,767
Suez
79,855
Port Said
69,209
Other Urban
Rural
49,913
13
C-GIDD also contains socioeconomic level population data, used to conduct powerful growth
projections of unique consumption classes
Socioeconomic
Levels (SEL)
We use an international definition developed by AMAI to define socioeconomic levels (SEL) and apply it consistently to all countries
(regardless of a country’s own SEL definition). This allows for comparability between countries, subdivisions and cities. The
international definition is the most well defined scheme and is independent of climate and culture.
BRAZILIAN POPULATION BY SOCIOECONOMIC LEVEL
HEALTHCARE CONSUMING CLASS
Millions, 1974 - 2034
Millions of people, 2014-2024
110
+64.6%
100
55.0
90
80
70
33.4
Marginalized
60
50
Lower middle
40
Lower
Upper middle
30
Middle
20
10
Upper
forecast
0
1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035
Source: C-GIDD; Canback analysis
2014
2024
Healthcare consuming class is statistically
demonstrated to comprise middle class and
above
14
In many emerging countries the E class (marginalized) is >90% of the population. For more
nuanced analysis, we can break down the E class into five unique economic classes
TANZANIAN SEL DISTRIBUTION BY REGION
TANZANIAN POPULATION DISTRIBUTION BY SEL
ABC+C
<1%
2.1%
5.5%
2.4
%
Highest
economic
level
2.0%
4.3%
11.3%
1.6%
5.2%
D+
4.2%
E1
8.6%
E2
17.2%
E3
35.6%
E4
26.6%
E5
D
22.6%
33.1%
67.4%
45.9%
Lowest
economic
level
2003
Source: C-GIDD; Canback analysis
2013
2023
Dar Es Salaam
Mwanza
Mbeya
Kagera
Tabora
Morogoro
Kigoma
Dodoma
Tanga
Mara
Geita
Arusha
Kilimanjaro
Simiyu
Shinyanga
Manyara
Ruvuma
Singida
Zanzibar
Mtwara
Pwani
Rukwa
Iringa
Lindi
Njombe
Katavi
ABC+C
D+
D
E1
E2
E3
E4
E5
15
C-GIDD can be used to examine macroeconomic and demographic trends beyond numerical
indicators, allowing users to gain both broad and in-depth understanding of economies
COUNTRY DECKS
Completed and available for purchase
• Angola
• Algeria
• Brazil
• Cuba
• Ethiopia
• Ghana
• Iran
• Mexico
• Myanmar
• Nigeria
• Pakistan
• Tanzania
In progress
• Egypt
• Indonesia
• Kenya
• Saudi Arabia
Other country decks readily created on-demand
16
Agenda
Introduction to EIU Canback
C-GIDD Classic
C-GIDD extensions
Leveraging C-GIDD in consulting work
Appendix: C-GIDD geographic coverage
17
The first type of C-GIDD extension are customized web portals where we adapt C-GIDD to the needs
to large corporate customers. This may mean adding category data, age brackets, and adding
organizational cuts to the dataset
CUSTOMIZED WEB PORTALS FOR ENTERPRISES
We work closely with enterprises, including some of the world’s largest corporations, to create customized web portals with seamless access
to C-GIDD/customer data. We provide a dedicated support team to meet their needs. Such customers include:
Procter & Gamble – C-GIDD includes the traditional variables
provided in the public site, plus P&G specific data on
consumer profiles and category spending with a 5-year
outlook. The site matches P&G’s organizational structure and
aggregates cities and countries thereafter. (pg.cgidd.com)
Mondelez - C-GIDD site covers the public variables plus
food consumption data and demographic data relevant to
Mondelez. The site has a 5 year horizon.
(mondelez.cgidd.com)
CORPORATE ACCOUNT HOLDERS
We provide subscription-based C-GIDD access and full support to
companies of various sizes to meet their needs on an ongoing
basis. Corporate account customers include:
INDIVIDUAL CUSTOMERS
In addition to providing data to large corporations on a subscription
basis, we also work with smaller entities who have occasional data
needs.
We have over 300 active customers who have purchased C-GIDD
in the last 2 years. Such purchases are made by credit card over
the web.
18
The second type of extension is to build more detailed datasets. Our sub-Saharan Africa
database (sold separately) illustrates this
SUB-SAHARAN AFRICA (SSA) DATABASE
Sub-Saharan Africa (SSA) is one of the
fastest growing and most attractive regions
in the world:
“Across Sub-Saharan Africa,
consumer demand is fueling the
continent’s economies in new ways…
‘The future is about that lower middle
class that’s expanding quickly,’ said
Staffan Canback”
-New York Times, July 2014
Given Sub-Saharan Africa’s rapid growth,
large corporations are shifting their focus
and devoting more resources to the region.
This includes the need to prioritize
investment among countries and even
cities. These needs led EIU Canback to
develop the SSA database.
ADVANTAGES OF THE SSA DATABASE
1
With a dataset that includes 393 cities, we offer a
wider and more in-depth view of Sub-Saharan African
cities. This in turn allows for more accurate as-is
evaluations and better-informed to-be projections:
• Gross domestic product
• Household spending
• Income distribution
• Socioeconomic levels
• Population
2
Data on specific business categories, ranging from
number of ATMs to international hotels in each city,
allows for more precise strategies and clearer
awareness of the playing field
19
The third type of extension is to use C-GIDD together with customer category data from various
syndicated sources to model the size of markets today and into the future
ORAL CARE DATABASE
In 2005, we were commissioned by a client to analyze the manual and
rechargeable toothbrush market. Forecasting models, a specialized C-GIDD
dataset, and analysis of market dynamics formed the basis for our
recommendations
Using the oral care database, we were able to estimate demand,
measured by disposable income per capita, price, and population.
This in turn was used to explain growth with a high degree of
accuracy
BUILDING THE ORAL CARE DATABASE
PREDICTED VERSUS ACTUAL UNITS SOLD
Market research data from
Nielsen and Euromonitor
2004 - log-log scale
14
R2=0.97
Predicted
Client shipment data for 27
countries
12
C-GIDD
Economic, demographic, and
social indicators provided by
the UN, IMF, and World Bank
Insights, adjustments, and
additional information provided
by regional teams
10
8
8
10
Actual
12
14
20
Agenda
Introduction to EIU Canback
C-GIDD Classic
C-GIDD extensions
Leveraging C-GIDD in consulting work
Appendix: C-GIDD geographic coverage
21
EIU Canback leverages a variety of statistical methods to model demand growth, calculate
elasticities and analyze commercial opportunities
Using C-GIDD in combination with other data (from client, local statistics agency, etc.) enables powerful analysis. Our analysts regularly create
advanced statistical models in our consulting services, and C-GIDD provides the foundation for many of these predictive analytics
COMMONLY USED STATISTICAL MODELS
POOLED CROSS-SECTIONAL
TIME SERIES ANALYSIS
PRAIS-WINSTEN REGRESSION
META ANALYSIS
What is it?
What is it?
What is it?
The pooled cross-sectional time series is the
hybrid of two traditional methods of
comparative research; time series analysis
and cross-sectional analysis. A pooled crosssectional time series is a dataset which has
observations of multiple cross-sectional units
such as countries (X) over time (T)
Classic regression study with standard
correction for autoregressive or lagged time
variable errors. The Prais-Winsten approach is
most often the choice for explanatory time
series analysis
Collect and compare results from different
analyses. Meta analysis constitutes an
important scientific approach to elasticity
calculation. By analyzing results, and not only
data, a broader understanding of market
movements is achieved
ARMAX
CONJOINT
CLASSIC TIME SERIES
What is it?
What is it?
What is it?
A combination of regression and time series.
Armax works best for predictions, but the
inclusion of time series methods distorts the
elasticities. No autoregressive problems
Predicts the future based on the past behavior
of the dependent variable. Time series do not
work on explanatory models since they have
no independent variables
A choice model to determine which attributes
are most influential on respondent choices.
Conjoint analysis models trade-offs that are
only loosely linked to elasticities
22
In one project, Canback leveraged C-GIDD and our management consulting practice for a
market sizing and product launch effort in healthcare
OBJECTIVE
A large US company seeks to quantify the market potential of parasitic worm
prevention/treatment and to understand how it can best capture the opportunity
TARGET COUNTRIES
DRIVERS OF REDUCED INTESTINAL
PARASITE PREVALENCE
China
Brazil
Mexico Philippines
C-GIDD database was
complemented with data
from WHO, UNESCO,
and similar databases
PRIMARY DRIVERS
PARASITIC WORM
PREVALENCE
DISPOSABLE
INCOME
13,364
MATERNAL
EDUCATION
17%
17,700
23%
22,508
12,188
23%
Disposable income per
Household-equivalent in
2005 PPP$
32%
% of women with tertiary
education
SECONDARY DRIVERS
87%
96%
98%
ACCESS TO HEALTH
CARE
79%
% of children getting
DPT3 vaccination
75%
SANITATION
CONDITIONS
44%
QUALITY
OF HOUSING
36%
79%
72%
% of population with
sustained access to
improved sanitation
55%
65%
41%
% of population living
with durable floors, walls,
and roofs; water, and
electricity
23
Canback identified three clear stages of parasite prevention and visited four countries for
consumer insights, health perspectives, and to understand distribution capabilities.
STAGES OF PARASITE PREVENTION
High prevalence
Low socioeconomic readiness
High to moderate prevalence
High socioeconomic readiness
Malaysia
Panama
Philippines
Peru
Honduras
Interest in
prevention
of parasitic
infections
South Africa
Thailand
El Salvador
Paraguay Colombia
Indonesia
Viet Nam
Bangladesh Cambodia
Cameroon
Guyana
Laos
Ghana
Nepal
Guinea
China
Uganda
Nigeria
India
Kenya
Madagascar
Ethiopia Burkina Faso
Morocco
Pakistan
BurundiMali
Tanzania
Algeria
Mongolia Mauritania
Yemen
Low prevalence
High socioeconomic readiness
Current state of 4
countries under review
Argentina
Namibia
State of 4 countries
under review in 10
years time
Dominican Republic
Oman
Botswana
Costa Rica
Brazil
Iran
Jordan
Mexico
Uruguay
Saudi Arabia
Statistically fitted
trendline
South Korea
•
•
•
•
Largest infested population in the world;
prevalence declined due to socioeconomic
development, but no concerted effort to
reduce levels of infection
About 60% of survey respondents
expressed high-level concern about
parasites
Prevention has higher appeal than
treatment
Relative ignorance regarding sources and
symptoms of infection
Interest in preventing parasites peaks
when there is a high level of
socioeconomic readiness and a
moderate level of prevalence
Three preconditions determine
whether a branded anthelmintic food
product is viable:
(1) Socioeconomic readiness to
prevent parasitic worms
(2) Branded food products
consumption
(3) Maternal perception of infection
risk
None of the four countries will reach a
stage where prevention is unnecessary
for at least another generation
Income
COUNTRY PROFILE
INTERPRETATION
FINDINGS FROM CONSUMER ENGAGEMENT
Low penetration of powdered beverages and negative brand image impacts
the new product perception
Believability of the product is a concern
Milk has wide appeal as a substitute carrier product
Respondents are willing to pay a premium for a new product that fights
parasite infection
24
Finally, Canback delivered specific recommendations for a distribution and marketing strategy as
well as provided “to-be” market projections for each country
WHERE TO SELL OR DISTRIBUTE
PROJECTED GROWTH OF FOOD RETAIL
Mean score on a scale of 1 (strongly disagree) to 5 (strongly agree)
Billion CNY
Large supermarkets
3.98
1800
1,615
1600
Given at schools for free
3.91
Primarily shelved with “health food”
3.74
cagr: 9%
1400
1200
1,063
1000
Primarily shelved with “regular food”
3.73
Doctors’ clinics and hospitals
77%
400
2.94
Pharmacy
Traditional stores
Traditional
cagr: 26%
44%
200
0
2.37
56%
800
600
3.08
cagr: 2%
Modern
23%
2006
2011
RECOMMENDATION
Product
A: Extension of preexisting product
B: Milk-centric product
Small pack sizes for
affordability and large
pack sizes to give lower
unit cost with sustained
use
Distribution
•
Skewed to modern
trade
•
Initial focus on
greater Shanghai
area where modern
trade is welldeveloped
•
Marketing
•
Social networkdriven: Word-ofmouth
•
Address believability
issues
Possible
Outcome
Price
20-30% premium above
current product price
•
$100M in retail
revenue 4-6 years
after launch
•
Contribution to brand
image + distribution
footprint
Shelved with regular
food
25
Agenda
Introduction to EIU Canback
C-GIDD Classic
C-GIDD extensions
Leveraging C-GIDD in consulting work
Appendix: C-GIDD geographic coverage
26
Appendix A
C-GIDD countries
Updated February 2016
Afghanistan
Albania
Algeria
Andorra
Angola
Anguilla
Antigua and Barbuda
Argentina
Armenia
Aruba
Australia
Austria
Azerbaijan
Bahamas
Bahrain
Bangladesh
Barbados
Belarus
Belgium
Belize
Benin
Bermuda
Bhutan
Bolivia
Bosnia and Herzegovina
Botswana
Brazil
Brunei
Bulgaria
Burkina Faso
Burundi
Cambodia
Cameroon
Canada
Cape Verde
Cayman Islands
Central African Republic
Chad
Chile
China
Colombia
Comoros
Congo-Brazzaville
Congo-Kinshasa
Cook Islands
Costa Rica
Cote d'Ivoire
Croatia
Cuba
Curacao
Cyprus
Czech Republic
Denmark
Djibouti
Dominica
Dominican Republic
Ecuador
Egypt
El Salvador
Equatorial Guinea
Eritrea
Estonia
Ethiopia
Fiji
Finland
France
French Polynesia
Gabon
Gambia
Georgia
Germany
Ghana
Note: Countries in green have subdivisions, see next page
Greece
Greenland
Grenada
Guatemala
Guinea
Guinea-Bissau
Guyana
Haiti
Honduras
Hong Kong
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Jamaica
Japan
Jordan
Kazakhstan
Kenya
Kiribati
Korea, North
Korea, South
Kosovo
Kuwait
Kyrgyzstan
Laos
Latvia
Lebanon
Lesotho
Liberia
Libya
Liechtenstein
Lithuania
Luxembourg
Macao
Macedonia
Madagascar
Malawi
Malaysia
Maldives
Mali
Malta
Marshall Islands
Mauritania
Mauritius
Mexico
Micronesia
Moldova
Monaco
Mongolia
Montenegro
Montserrat
Morocco
Mozambique
Myanmar
Namibia
Nauru
Nepal
Netherlands
New Caledonia
New Zealand
Nicaragua
Niger
Nigeria
Norway
Oman
Pakistan
Palau
Palestine
Panama
Papua New Guinea
Paraguay
Peru
Philippines
Poland
Portugal
Puerto Rico
Qatar
Romania
Russia
Rwanda
Saint Kitts and Nevis
Saint Lucia
Saint Vincent and the Grenadines
Samoa
San Marino
Sao Tome and Principe
Saudi Arabia
Senegal
Serbia
Seychelles
Sierra Leone
Singapore
Sint Maarten
Slovakia
Slovenia
Solomon Islands
Somalia
South Africa
South Sudan
Spain
Sri Lanka
Sudan
Suriname
Swaziland
Sweden
Switzerland
Syria
Taiwan
Tajikistan
Tanzania
Thailand
Timor-Leste
Togo
Tonga
Trinidad and Tobago
Tunisia
Turkey
Turkmenistan
Turks and Caicos Islands
Tuvalu
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Vanuatu
Venezuela
Viet Nam
Virgin Islands, British
Western Sahara
Yemen
Zambia
Zimbabwe
27
Appendix B
C-GIDD subdivisions
Updated October 2015
Argentina
Catamarca
Chaco
Chubut
Ciudad Autonoma de Buenos Aires
Cordoba
Corrientes
Entre Rios
Formosa
Jujuy
La Pampa
La Rioja
Mendoza
Misiones
Neuquen
Provincia de Buenos Aires
Rio Negro
Salta
San Juan
San Luis
Santa Cruz
Santa Fe
Santiago del Estero
Tierra del Fuego
Tucuman
Australia
Australian Capital Territory
New South Wales
Northern Territory
Queensland
South Australia
Tasmania
Victoria
Western Australia
Austria
Eastern Austria
Southern Austria
Western Austria
Bangladesh
Barisal
Chittagong
Dhaka
Khulna
Rajshahi
Rangpur
Sylhet
Belgium
Brussels-Capital Region
Flemish Region
Walloon Region
Brazil
Acre
Alagoas
Amapa
Amazonas
Bahia
Ceara
Distrito Federal
Espirito Santo
Goias
Maranhao
Mato Grosso
Mato Grosso do Sul
Minas Gerais
Para
Paraiba
Brazil
Parana
Pernambuco
Piaui
Rio de Janeiro
Rio Grande do Norte
Rio Grande do Sul
Rondonia
Roraima
Santa Catarina
Sao Paulo
Sergipe
Tocantins
Bulgaria
North Bulgaria
South Bulgaria
Canada
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland and Labrador
Northwest Territories
Nova Scotia
Nunavut
Ontario
Prince Edward Island
Quebec
Saskatchewan
Yukon Territory
China
Anhui
Beijing
Chongqing
Fujian
Gansu
Guangdong
Guangxi
Guizhou
Hainan
Hebei
Heilongjiang
Henan
Hubei
Hunan
Inner Mongolia
Jiangsu
Jiangxi
Jilin
Liaoning
Ningxia
Qinghai
Shaanxi
Shandong
Shanghai
Shanxi
Sichuan
Tianjin
Tibet
Xinjiang
Yunnan
Zhejiang
Colombia
Amazonia
Andina Norte
Andina Sur
Atlantica
Bogota
Orinoquia
Pacifica
Finland
Aland
Mainland Finland
France
Bassin Parisien
Center-East
East
Ile de France
Mediterranee
Nord-Pas-de-Calais
Overseas departments
South-West
West
Germany
Baden-Wurttemberg
Bavaria
Berlin
Brandenburg
Bremen
Hamburg
Hesse
Lower Saxony
Mecklenburg-Vorpommern
North Rhine-Westphalia
28
C-GIDD subdivisions, continued
Germany
Rhineland-Palatinate
Saarland
Saxony
Saxony-Anhalt
Schleswig-Holstein
Thuringia
Greece
Aegean Islands and Crete
Attica
Central Greece
Northern Greece
Hungary
Central Hungary
Great Plain and North
Transdanubia
India
Andaman and Nicobar Islands
Andhra Pradesh
Arunachal Pradesh
Assam
Bihar
Chandigarh
Chhattisgarh
Dadra and Nagar Haveli
Daman and Diu
Delhi
Goa
Gujarat
Haryana
Himachal Pradesh
Jammu and Kashmir
India
Jharkhand
Karnataka
Kerala
Lakshadweep
Madhya Pradesh
Maharashtra
Manipur
Meghalaya
Mizoram
Nagaland
Orissa
Puducherry
Punjab
Rajasthan
Sikkim
Tamil Nadu
Telangana
Tripura
Uttar Pradesh
Uttarakhand
West Bengal
Indonesia
Aceh
Bali
Bangka Belitung Islands
Banten
Bengkulu
Central Jawa
Central Kalimantan
Central Sulawesi
East Jawa
East Kalimantan
East Nusa Tenggara
Indonesia
Gorontalo
Jakarta Raya
Jambi
Lampung
Maluku
North Maluku
North Sulawesi
North Sumatera
Papua
Riau
Riau Islands
South Kalimantan
South Sulawesi
South Sumatera
Southeast Sulawesi
West Jawa
West Kalimantan
West Nusa Tenggara
West Papua
West Sulawesi
West Sumatera
Yogyakarta
Italy
Center
Islands
North-East
North-West
South
Japan
Aichi
Akita
Aomori
Japan
Chiba
Ehime
Fukui
Fukuoka
Fukushima
Gifu
Gunma
Hiroshima
Hokkaido
Hyogo
Ibaraki
Ishikawa
Iwate
Kagawa
Kagoshima
Kanagawa
Kochi
Kumamoto
Kyoto
Mie
Miyagi
Miyazaki
Nagano
Nagasaki
Nara
Niigata
Oita
Okayama
Okinawa
Osaka
Saga
Saitama
Shiga
Shimane
Japan
Shizuoka
Tochigi
Tokushima
Tokyo
Tottori
Toyama
Wakayama
Yamagata
Yamaguchi
Yamanashi
Korea, South
Busan
Chungcheongbugdo
Chungcheongnamdo
Daegu
Daejeon
Gang'weondo
Gwangju
Gyeonggido
Gyeongsangbugdo
Gyeongsangnamdo
Incheon
Jejudo
Jeonrabugdo
Jeonranamdo
Seoul
Ulsan
Mexico
Aguascalientes
Baja California
Baja California Sur
Campeche
29
C-GIDD subdivisions, continued
Mexico
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Mexico
Michoacan
Morelos
Nayarit
Nuevo Leon
Oaxaca
Puebla
Queretaro
Quintana Roo
San Luis Potosi
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Zacatecas
Netherlands
Eastern Netherlands
Northern Netherlands
Southern Netherlands
Western Netherlands
Nigeria
Abia
Adamawa
Akwa Ibom
Anambra
Bauchi
Bayelsa
Benue
Borno
Cross River
Delta
Ebonyi
Edo
Ekiti
Enugu
Federal Capital Territory
Gombe
Imo
Jigawa
Kaduna
Kano
Katsina
Kebbi
Kogi
Kwara
Lagos
Nassarawa
Niger
Ogun
Ondo
Osun
Oyo
Plateau
Rivers
Sokoto
Nigeria
Taraba
Yobe
Zamfara
Pakistan
Azad Kashmir
Balochistan
Federally Administered Tribal Areas
Gilgit-Baltistan
Islamabad
Khyber Pakhtunkhwa
Punjab
Sindh
Philippines
ARMM
Bicol
Cagayan Valley
CALABARZON
Caraga
Central Luzon
Central Visayas
Cordillera
Davao
Eastern Visayas
Ilocos
MIMAROPA
National Capital Region
Northern Mindanao
SOCCSKSARGEN
Western Visayas
Zamboanga Peninsula
Poland
Central
East
North
North-West
South
South-West
Portugal
Azores
Continental Portugal
Madeira
Romania
Macroregion 1
Macroregion 2
Macroregion 3
Macroregion 4
Russia
Central
Far East
North Caucasus
Northwest
Siberia
South
Ural
Volga
South Africa
Eastern Cape
Free State
Gauteng
KwaZulu-Natal
Limpopo
South Africa
Mpumalanga
Northern Cape
North-West
Western Cape
Spain
Canary Islands
Center
East
Madrid
Northeast
Northwest
South
Sweden
Eastern
Northern
Southern
Taiwan
Central
Eastern
Northern
Southern
Thailand
Bangkok and Vicinities
Central
Eastern
Northeastern
Northern
Southern
Western
30
C-GIDD subdivisions, continued
Turkey
Aegean
Central Anatolia
Eastern Black Sea
Eastern Marmara
Istanbul
Mediterranean
Mideastern Anatolia
Northeastern Anatolia
Southeastern Anatolia
Western Anatolia
Western Black Sea
Western Marmara
United Kingdom
East Midlands
East of England
London
North East
North West
Northern Ireland
Scotland
South East
South West
Wales
West Midlands
Yorkshire and the Humber
United States
Alabama
Alaska
Arizona
Arkansas
California
Colorado
United States
Connecticut
Delaware
District of Columbia
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
United States
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
31
Appendix C
C-GIDD cities
Updated October 2015
Afghanistan
Kabul
Australia
Sydney
Albania
Tirana
Austria
Vienna
Algeria
Algiers
Constantine
Oran
Azerbaijan
Baku
Angola
Huambo
Luanda
Argentina
Buenos Aires
La Plata
Mar del Plata
Mendoza
Rosario
Salta
San Miguel de Tucuman
Santa Fe
Armenia
Yerevan
Australia
Adelaide
Brisbane
Gold Coast
Melbourne
Newcastle
Perth
Bangladesh
Chittagong
Dhaka
Khulna
Rajshahi
Sylhet
Belarus
Minsk
Belgium
Antwerp
Brussels
Gent
Liege
Benin
Abomey-Calavi
Cotonou
Bolivia
Cochabamba
La Paz
Santa Cruz
Brazil
Aracaju
Baixada Santista
Belem
Belo Horizonte
Blumenau
Brasilia
Campinas
Campo Grande
Cuiaba
Curitiba
Feira de Santana
Florianopolis
Fortaleza
Goiania
Joao Pessoa
Joinville
Juiz de Fora
Jundiai
Londrina
Maceio
Manaus
Maringa
Natal
Porto Alegre
Recife
Ribeirao Preto
Rio de Janeiro
Salvador
Sao Jose dos Campos
Sao Luis
Sao Paulo
Sorocaba
Teresina
Uberlandia
Brazil
Vale do Aco
Vitoria
Bulgaria
Plovdiv
Sofia
Burkina Faso
Bobo Dioulasso
Ouagadougou
Burundi
Bujumbura
Cambodia
Phnom Penh
Cameroon
Douala
Yaounde
Canada
Calgary
Edmonton
Hamilton
Montreal
Ottawa
Quebec
Toronto
Vancouver
Winnipeg
Central African Republic
Bangui
Chad
N'Djamena
Chile
Concepcion
Santiago de Chile
Valparaiso
China
Anqing
Anshan
Anyang
Baoding
Baoji
Baotou
Beijing
Bengbu
Benxi
Binzhou
Changchun
Changde
Changsha
Changshu
Changzhi
Changzhou
Chaozhou
Chengde
Chengdu
Chenzhou
Chifeng
Chongqing
Cixi
China
Dalian
Dandong
Daqing
Datong
Deyang
Dezhou
Dongguan
Dongying
Ezhou
Foshan
Fuling
Fushun
Fuxin
Fuyang
Fuzhou
Ganzhou
Guangzhou
Guigang
Guilin
Guiyang
Haicheng
Haikou
Handan
Hangzhou
Harbin
Hefei
Hegang
Hengyang
Heze
Hohhot
Huai'an
Huaibei
Huainan
Huangshi
32
C-GIDD cities, continued
China
Huizhou
Huludao
Huzhou
Jiamusi
Jiangyin
Jiaozuo
Jiaxing
Jieyang
Jilin
Jimo
Jinan
Jingzhou
Jinhua
Jining
Jinzhou
Jiujiang
Jixi
Kaifeng
Kunming
Laiwu
Langfang
Lanzhou
Leshan
Lianyungang
Liaocheng
Liaoyang
Linfen
Linyi
Liu'an
Liupanshui
Liuyang
Liuzhou
Lufeng
Luohe
China
Luoyang
Luzhou
Ma'anshan
Maoming
Mianyang
Mudanjiang
Nan'an
Nanchang
Nanchong
Nanjing
Nanning
Nantong
Nanyang
Neijiang
Ningbo
Panjin
Panzhihua
Pingdingshan
Pingxiang
Pizhou
Puning
Putian
Qingdao
Qingyuan
Qinhuangdao
Qiqihar
Qitaihe
Quanzhou
Rizhao
Rugao
Rui'an
Shanghai
Shangqiu
Shantou
China
Shaoguan
Shaoxing
Shaoyang
Shenyang
Shenzhen
Shijiazhuang
Shiyan
Siping
Suining
Suqian
Suzhou
Suzhou
Taian
Taixing
Taiyuan
Taizhou
Taizhou
Tangshan
Tengzhou
Tianjin
Tianmen
Tianshui
Tongliao
Urumqi
Wanzhou
Weifang
Weihai
Wenling
Wenzhou
Wuhan
Wuhu
Wuxi
Wuzhou
Xiamen
China
Xi'an
Xiangtan
Xiangyang
Xiantao
Xianyang
Xiaogan
Xinghua
Xingtai
Xining
Xintai
Xinxiang
Xinyang
Xinyu
Xuzhou
Yancheng
Yangquan
Yangzhou
Yantai
Yibin
Yichang
Yichun
Yinchuan
Yingkou
Yiwu
Yongzhou
Yueqing
Yueyang
Yulin
Yuyao
Zaozhuang
Zhangjiakou
Zhangzhou
Zhanjiang
China
Zhaoqing
Zhengzhou
Zhenjiang
Zhongshan
Zhoushan
Zhucheng
Zhuhai
Zhuji
Zhuzhou
Zibo
Zigong
Zoucheng
Zunyi
Colombia
Barranquilla
Bogota
Bucaramanga
Cali
Cartagena
Cucuta
Ibague
Medellin
Pereira
Congo-Brazzaville
Brazzaville
Pointe-Noire
Congo-Kinshasa
Bukavu
Kananga
Kinshasa
Congo-Kinshasa
Kisangani
Lubumbashi
Mbuji-Mayi
Tshikapa
Costa Rica
San Jose
Cote d'Ivoire
Abidjan
Bouake
Croatia
Zagreb
Cuba
Havana
Czech Republic
Brno
Ostrava
Prague
Denmark
Copenhagen
Dominican Republic
Santiago de los Caballeros
Santo Domingo
Ecuador
Guayaquil
Quito
33
C-GIDD cities, continued
Egypt
Alexandria
Cairo
Port Said
Suez
El Salvador
San Salvador
Eritrea
Asmara
Estonia
Tallinn
Ethiopia
Addis Ababa
Finland
Helsinki
France
Bordeaux
Grenoble
Lille
Lyon
Marseille
Montpellier
Nantes
Nice
Paris
Rennes
Rouen
Saint-Etienne
Strasbourg
France
Toulon
Toulouse
Gabon
Libreville
Georgia
Tbilisi
Germany
Wurzburg
Ghana
Accra
Kumasi
Sekondi Takoradi
Greece
Athens
Thessaloniki
Germany
Aachen
Augsburg
Guatemala
Berlin
Guatemala City
Bonn
Bremen
Guinea
Cologne
Conakry
Dresden
Dusseldorf
Haiti
Erfurt
Port-au-Prince
Frankfurt
Freiburg
Honduras
Hamburg
San Pedro Sula
Hannover
Tegucigalpa
Heidelberg
Karlsruhe
Hong Kong
Kiel
Hong Kong
Leipzig
Mannheim-Ludwigshafen Hungary
Munich
Budapest
Nuremberg
Osnabruck
India
Ruhr Area
Agra
Saarbrucken
Ahmadabad
Stuttgart
Ajmer
India
Aligarh
Allahabad
Amravati
Amritsar
Asansol
Aurangabad
Bangalore
Bareilly
Belgaum
Bhavnagar
Bhiwandi
Bhopal
Bhubaneswar
Bikaner
Bokaro Steel City
Chandigarh
Chennai
Coimbatore
Cuttack
Dehra Dun
Delhi
Dhanbad
Durgapur
Durg-Bhilai Nagar
Erode
Firozabad
Gorakhpur
Gulbarga
Guntur
Guwahati
Gwalior
Hubli-Dharwad
Hyderabad
Indore
India
Jabalpur
Jaipur
Jalandhar
Jammu
Jamnagar
Jamshedpur
Jhansi
Jodhpur
Kannur
Kanpur
Kochi
Kolhapur
Kolkata
Kota
Kozhikode
Lucknow
Ludhiana
Madurai
Malegaon
Mangalore
Meerut
Moradabad
Mumbai
Mysore
Nagpur
Nanded
Nashik
Nellore
Patna
Puducherry
Pune
Raipur
Rajkot
Ranchi
India
Raurkela
Saharanpur
Salem
Sangli
Siliguri
Solapur
Srinagar
Surat
Thiruvananthapuram
Tiruchirappalli
Tiruppur
Ujjain
Vadodara
Varanasi
Vijayawada
Visakhapatnam
Warangal
Indonesia
Balikpapan
Bandar Lampung
Bandung
Banjarmasin
Batam
Denpasar
Jakarta
Jambi
Makassar
Malang
Medan
Padang
Palembang
Pekanbaru
Pontianak
34
C-GIDD cities, continued
Indonesia
Samarinda
Semarang
Serang
Surabaya
Tasikmalaya
Iran
Ahvaz
Esfahan
Hamadan
Karaj
Kerman
Kermanshah
Mashhad
Orumiyeh
Qom
Rasht
Shiraz
Tabriz
Tehran
Zahedan
Iraq
Baghdad
Basra
Erbil
Karbala
Kirkuk
Mosul
Najaf
Sulaymaniyah
Ireland
Dublin
Israel
Be'er Sheva
Haifa
Jerusalem
Tel Aviv-Jaffa
Italy
Bari
Bologna
Catania
Florence
Genoa
Milan
Naples
Padova
Palermo
Rome
Turin
Venice
Verona
Jamaica
Kingston
Japan
Fukuoka
Hamamatsu
Himeji
Hiroshima
Kobe
Kumamoto
Kyoto
Nagoya
Niigata
Japan
Osaka
Sapporo
Sendai
Shizuoka
Tokyo
Utsunomiya
Jordan
Amman
Kazakhstan
Almaty
Astana
Shymkent
Kenya
Mombasa
Nairobi
Korea, North
Chongjin
Hamhung
Pyongyang
Korea, South
Busan
Changwon
Cheongju
Daegu
Daejeon
Gwangju
Jeonju
Seoul
Ulsan
Kuwait
Kuwait City
Kyrgyzstan
Bishkek
Laos
Vientiane
Latvia
Riga
Lebanon
Beirut
Liberia
Monrovia
Libya
Benghazi
Misratah
Tripoli
Lithuania
Vilnius
Luxembourg
Luxembourg
Macao
Macao
Malawi
Blantyre
Lilongwe
Malaysia
Ipoh
Johor Bahru
Kuala Lumpur-Klang Valley
Kuching
Penang
Mali
Bamako
Mauritania
Nouakchott
Mexico
Acapulco
Aguascalientes
Cancun
Celaya
Chihuahua
Cuernavaca
Culiacan
Durango
Guadalajara
Hermosillo
Juarez
Leon
Merida
Mexicali
Mexico
Mexico City
Monterrey
Morelia
Oaxaca
Pachuca
Poza Rica
Puebla
Queretaro
Reynosa
Saltillo
San Luis Potosi
Tampico
Tijuana
Tlaxcala
Toluca
Torreon
Tuxtla Gutierrez
Veracruz
Villahermosa
Xalapa
Moldova
Chisinau
Mongolia
Ulaanbaatar
Morocco
Agadir
Casablanca
Fes
Madagascar
Antananarivo
35
C-GIDD cities, continued
Morocco
Marrakech
Meknes
Rabat
Tangier
Mozambique
Maputo
Matola
Nampula
Myanmar
Mandalay
Nay Pyi Taw
Rangoon
Nepal
Kathmandu
Netherlands
Amsterdam
Eindhoven
Hague, The
Rotterdam
Utrecht
New Zealand
Auckland
Nicaragua
Managua
Niger
Niamey
Nigeria
Aba
Abuja
Benin City
Enugu
Ibadan
Ilorin
Jos
Kaduna
Kano
Lagos
Maiduguri
Nnewi
Onitsha
Osogbo
Owerri
Port Harcourt
Uyo
Warri
Zaria
Norway
Oslo
Oman
Muscat
Pakistan
Bahawalpur
Faisalabad
Gujranwala
Hyderabad
Islamabad
Karachi
Lahore
Pakistan
Multan
Peshawar
Quetta
Rawalpindi
Sargodha
Sialkot
Palestine
Gaza
Panama
Panama City
Paraguay
Asuncion
Peru
Arequipa
Chiclayo
Lima
Trujillo
Philippines
Antipolo
Bacolod
Cagayan de Oro
Cebu
Dasmarinas
Davao
General Santos City
Manila
Zamboanga
Poland
Bydgoszcz
Gdansk
Katowice
Krakow
Lodz
Lublin
Poznan
Warsaw
Wroclaw
Portugal
Lisbon
Porto
Puerto Rico
San Juan
Qatar
Doha
Romania
Bucharest
Russia
Astrakhan'
Barnaul
Chelyabinsk
Irkutsk
Izhevsk
Kazan
Kemerovo
Khabarovsk
Krasnodar
Krasnoyarsk
Russia
Lipetsk
Makhachkala
Moscow
Naberezhnye Chelny
Nizhny Novgorod
Novokuznetsk
Novosibirsk
Omsk
Orenburg
Penza
Perm
Rostov
Ryazan
Saint Petersburg
Samara
Saratov
Tolyatti
Tomsk
Tula
Tyumen
Ufa
Ulyanovsk
Vladivostok
Volgograd
Voronezh
Yaroslavl
Yekaterinburg
Rwanda
Kigali
Saudi Arabia
Dammam
Hufuf-Mubarraz
Saudi Arabia
Jedda
Mecca
Medina
Riyadh
Tabuk
Ta'if
Senegal
Dakar
Touba
Serbia
Belgrade
Sierra Leone
Freetown
Singapore
Singapore
Slovakia
Bratislava
Slovenia
Ljubljana
Somalia
Hargeysa
Mogadishu
South Africa
Cape Town
Durban
Emfuleni
36
C-GIDD cities, continued
South Africa
Johannesburg
Port Elizabeth
Pretoria
Spain
Barcelona
Bilbao
Cordoba
Granada
Las Palmas
Madrid
Malaga
Murcia
Palma di Mallorca
Seville
Valencia
Vigo
Zaragoza
Sri Lanka
Colombo
Sudan
Khartoum
Nyala
Sweden
Gothenburg
Malmo
Stockholm
Switzerland
Geneva
Zurich
Syria
Aleppo
Al-Raqqa
Damascus
Hamah
Homs
Latakia
Taiwan
Hsinchu
Kaohsiung
Taichung-Changhua
Tainan
Taipei-Keelung
Taoyuan-Jhongli
Tajikistan
Dushanbe
Tanzania
Dar es Salaam
Mwanza
Thailand
Bangkok
Chiang Mai
Samut Prakan
Togo
Lome
Tunisia
Safaqis
Tunis
Turkey
Adana
Ankara
Antalya
Bursa
Diyarbakir
Eskisehir
Gaziantep
Gebze
Istanbul
Izmir
Kayseri
Konya
Mersin
Turkmenistan
Ashgabat
Uganda
Kampala
Ukraine
Dnipropetrovs'k
Donetsk
Kharkov
Kiev
Krivoi Rog
Lvov
Mykolaiv
Odessa
Zaporizhzhya
United Arab Emirates
Abu Dhabi
Dubai
United Arab Emirates
Sharjah
United Kingdom
Belfast
Birmingham
Bournemouth
Bristol
Cardiff
Coventry
Edinburgh
Glasgow
Kingston-upon-Hull
Leeds-Bradford
Leicester
Liverpool
London
Manchester
Newcastle
Nottingham
Portsmouth
Sheffield
United States
Akron
Albany
Albuquerque
Allentown
Atlanta
Augusta
Austin
Bakersfield
Baltimore
Baton Rouge
Birmingham
United States
Boise City
Boston
Buffalo
Charleston
Charlotte
Chattanooga
Chicago
Cincinnati
Cleveland
Colorado Springs
Columbia
Columbus
Dallas-Fort Worth
Dayton
Deltona-Daytona Beach-Ormond Beach
Denver
Des Moines
Detroit
Durham
El Paso
Fort Myers
Fresno
Grand Rapids
Greensboro
Greenville
Harrisburg
Hartford
Honolulu
Houston
Indianapolis
Jackson
Jacksonville
Kansas City
Knoxville
37
C-GIDD cities, continued
United States
Lakeland
Lancaster
Las Vegas
Little Rock
Los Angeles
Louisville
Madison
McAllen
Memphis
Miami
Milwaukee
Minneapolis-Saint Paul
Modesto
Nashville
New Haven
New Orleans
New York
Ogden
Oklahoma City
Omaha
Orlando
Oxnard
Palm Bay
Philadelphia
Phoenix
Pittsburgh
Portland
Portland
Providence
Provo-Orem
Raleigh
United States
Uzbekistan
Richmond
Tashkent
Riverside-San Bernardino
Rochester
Venezuela
Sacramento
Barcelona-Puerto La Cruz
Saint Louis
Barquisimeto
Salt Lake City
Caracas
San Antonio
Ciudad Guayana
San Diego
Maracaibo
San Francisco
Maracay
San Jose
Valencia
Sarasota
Scranton
Viet Nam
Seattle
Bien Hoa
Spokane
Can Tho
Springfield
Da Nang
Stamford
Haiphong
Stockton
Hanoi
Syracuse
Ho Chi Minh City
Tampa
Toledo
Yemen
Tucson
Aden
Tulsa
Sana'a'
Virginia Beach
Taiz
Washington
Wichita
Zambia
Winston-Salem
Kitwe
Worcester
Lusaka
Youngstown
Zimbabwe
Uruguay
Bulawayo
Montevideo
Harare
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C-GIDD contact information
C-GIDD
Boston
EIU Canback, Inc.
210 Broadway, Suite 303
Cambridge MA 02139
+1-617-399-1300 ext. 210
Bobo Shen
[email protected]
39
Canback contact information
AMERICAS
Boston
EIU Canback, Inc.
210 Broadway, Suite 303
Cambridge MA 02139
+1-617-399-1300
Irina Blinova
[email protected]
Mexico City
Chicago
EIU Canback USA
500 N. Michigan Ave.
Suite 1925
Chicago IL 60611
+1-312-853-3716 or 3823
Tom Andrews
Sao Paulo
[email protected]
EIU Canback Europe
20 Cabot Square
London E14 4QW
+44-20-7576-8181
Chris Pearce
[email protected]
Maureen Lanigan
[email protected]
Canback Mexico
Bosque de Ciruelos 194, PH3
Bosques de las Lomas
11700 Ciudad de México, D.F.
+52-55-4164-8500
+52-155-4354-9806
Francisco Maciel Morfin
[email protected]
EIU Canback Brazil
Av. Brigadeiro Faria Lima, 3144
3º andar Jardim Paulistano
São Paulo, 01451-000
+55-11-3845 4767
Marcio Zanetti
[email protected]
EUROPE
London
Asif Chaudhary
[email protected]
MIDDLE EAST AND AFRICA
Dubai
EIU Canback MENA
Aurora Tower, 13th Floor
Office 1301A, PO Box 450056
Dubai Media City
+971-4433-4202
+971-52-269-8425
Paul Yata
[email protected]
Johannesburg
EIU Canback SA (Pty) Ltd
Inanda Greens Business Park
Building 8
54 Wierda Road West
Wierda Valley, Sandton, 2196
+27-83-786 2450
Arshad Abba
[email protected]
EIU Canback China
Unit 1711, 17/F, Block 1
Taikang Financial Tower
38 East 3rd Ring Rd. North
Chaoyang District 100026
+86-10-8571-2188
Alex van Kemenade
Singapore
EIU Canback Southeast Asia
8 Cross St, #23-01 PWC Bldg.
Singapore 048424
+65-6534-5177
Vanny Dang
[email protected]
Tokyo
Shin Ito
[email protected]
EIU Canback China
Rm 2508A, 25/F, Rui Jin Bldg
205 Mao Ming South Rd,
Shanghai 200020
+86-21-6473-7128
Seumas Graham
EIU Canback Japan
Ginza Wall Building UCF 5F
6-13-16 Ginza
Chuo-ku, Tokyo 104-0061
+81-3-6338-0002
Jakarta
EIU Canback SE Asia
Jl. Tiang Bendera 5 no. 2A
DKI Jakarta 11230
+62-812-8743 7578
Teddy Purnomo
[email protected]
ASIA
Beijing
Shanghai
[email protected]
[email protected]
40