Canback Global Income Distribution Database


Published on

C-GIDD is the world's most comprehensive and detailed database for GDP and income distribution data. The dataset covers 212 countries, 694 subdivisions (states, provinces, etc.) and 997 major cities from 2000 till 2025. Fully harmonized data are available in local currency, purchasing power parity (PPP) and US dollars in constant and current values. In addition, there is a long-term, national dataset covering each of the 212 countries.

C-GIDD is an EIU Canback product.

  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Canback Global Income Distribution Database

  2. 2. 2 Agenda Introduction to EIU Canback C-GIDD Classic C-GIDD extensions Leveraging C-GIDD in consulting work Appendix: C-GIDD geographic coverage
  3. 3. 3 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.
  4. 4. 4 Canback is the leader in scientific and quantitative management consulting, and in particular the use of predictive analytics, which bring better results to organizations Performance 1900 1960 1990 2016 Traditional management consulting Scientific and quantitative management consulting MANAGEMENT CONSULTING INDUSTRY S-CURVE Canback is the best-known firm in management consulting based on science A new approach with higher performance Few, if any, break- throughs since the early 1990s
  5. 5. 5 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) Abuja +12: Shaping the Future of Health in Africa (2013) Contextualising the Mass Market Banking Opportunity (2011) The Shifting Urban Economic Landscape: What Does it Mean for Cities? (2013) Annual Results Presentation (2013) 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) The Future of Retailer Brands (2010) Amfiteatru Economic: Income Distribution Determinants and Inequality (2014) Constructing Official Inequality Poverty Lines for Countries in Transition (2014) Consolidated Annual Report (2012) 2014 New York Analyst Day (2014)
  6. 6. 6 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 Canback Management consulting 75% Strategy development 40% M&A due diligence 35% 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
  7. 7. 7 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 Core office Satellite office CANBACK OFFICES OFFICE CAPABILITIES Boston London Beijing Johannes- burg Chicago Dubai Shanghai Singapore MexicoCity SaoPaulo Jakarta Tokyo Management consulting Predictive analytics C-GIDD Research
  8. 8. 8 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% United States: 7% South America: 30% Mid America: 11% Europe: 7% Africa: 24% Asia: 8% Core office Satellite office Country projects Consultants work travel
  9. 9. 9 Agenda Introduction to EIU Canback C-GIDD Classic C-GIDD extensions Leveraging C-GIDD in consulting work Appendix: C-GIDD geographic coverage
  10. 10. 10 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
  11. 11. 11 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 benchmark products and services data Internal to Canback C-GIDD economic, demographic, social and psychographic data Internal to Canback C-GIDD income distribution data Available as a commercial service at C-GIDD COVERAGE • The world's only database with complete subnational data series • GDP, household income, size of income brackets, size of socioeconomic classes, population • 213 countries, 696 subdivisions and 997 cities • Subnational: 2001-2026 National: 1970-2036 C-GIDD MODULES EXAMPLES OF C-GIDD USES • Quantify number of households at specific income or socioeconomic levels • Compare consumer market sizes across geographies in a uniform way • Merge with category or sales data to spot new or under-developed opportunities EXPLANATORY POWER OF C-GIDD Demand variance explained by income above category-specific thresholds R2 0.00 0.50 1.00 Televison sets Oil consumption Cellphone subscribers Internet users Personal computers McDonald's restaurants Milk consumption Cash machines (ATMs) Insurance premiums Bank deposits Electricity consumption Airline passengers
  12. 12. 12 • Population data • GDP • Household income data UN and national household economic surveys • Short and medium term economic projections IMF • Population projections UN and US Census Bureau • Income distributions WIDER and national surveys • City and other subdivision data National statistics offices • City data UN, Eurostat, CityPopulation and national censuses • PPP data International Comparison Program (ICP) Sophisticated econometric models to find true income at city level Proprietary purchasing power and cost-of-living adjustments Proprietary income distribution algorithms Robust income projection algorithms C-GIDD 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 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
  13. 13. 13 Millions of households with income higher than PPP$ 20,000 2005 constant values Millions of middle-class households by location in 2014 Socioeconomic levels A, B, C+ and C Income per household in Egypt in 2014 Egyptian Pounds, 2014 current values Total GDP in PPP$ trillions 2005 constant values 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 4.4 4.1 US 11.7 14.0 13.8 EU Japan China India 2014 6.0 4.3 15.3 17.6 2019 16.1 5.1 3.0 2.1 1.1 2019201420092004 Shanghai 4.0 2.8 1.6 0.7 20092004 20192014 Mumbai 5.5 5.6 2.5 1.2 0.8 3.1 1.8 1.1 0.5 0.1 0.2 0.1 0.7 0.6 Chile Colombia Mexico Brazil Argentina 0.5 Major Cities RuralOther Urban 49,913 69,209 79,855 88,767 99,097 121,382 Rural Other Urban Suez Alexandria Cairo Port Said * Purchasing power parity dollars C-GIDD’s data includes values in US dollars, local currency, and PPP*
  14. 14. 14 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 60 40 0 50 10 30 20 110 100 80 70 90 Lower Lower middle Marginalized Middle Upper Upper middle BRAZILIAN POPULATION BY SOCIOECONOMIC LEVEL Millions, 1974 - 2034 forecast HEALTHCARE CONSUMING CLASS Millions of people, 2014-2024 C-GIDD also contains socioeconomic level population data, used to conduct powerful growth projections of unique consumption classes Source: C-GIDD; Canback analysis 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. 2014 33.4 +64.6% 2024 55.0 Healthcare consuming class is statistically demonstrated to comprise middle class and above
  15. 15. 15Source: C-GIDD; Canback analysis TANZANIAN POPULATION DISTRIBUTION BY SEL 35.6% 33.1% 22.6% 17.2% 11.3% 5.5% 8.6% 4.3% 4.2% 5.2% 2023 2.0% D 2003 1.6% E4 E2 26.6% 67.4% E3 2013 E1 E5 45.9% ABC+C <1% D+ 2.1% 2.4 % Arusha Tabora Dar Es Salaam Zanzibar Katavi Iringa Rukwa Manyara Pwani Lindi Shinyanga Simiyu Kilimanjaro Geita Kagera Mbeya Mara Singida Njombe Tanga Ruvuma Kigoma Dodoma Morogoro Mtwara Mwanza E5 E4 E3 E2 E1 D+ D ABC+C Lowest economic level Highest economic level TANZANIAN SEL DISTRIBUTION BY REGION 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
  16. 16. 16 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
  17. 17. 17 Agenda Introduction to EIU Canback C-GIDD Classic C-GIDD extensions Leveraging C-GIDD in consulting work Appendix: C-GIDD geographic coverage
  18. 18. 18 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: 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. 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. ( 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. (
  19. 19. 19 The second type of extension is to build more detailed datasets. Our sub-Saharan Africa database (sold separately) illustrates this 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. SUB-SAHARAN AFRICA (SSA) DATABASE ADVANTAGES OF THE SSA DATABASE 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 1 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 2
  20. 20. 20 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 C-GIDD Client shipment data for 27 countries Market research data from Nielsen and Euromonitor Economic, demographic, and social indicators provided by the UN, IMF, and World Bank BUILDING THE ORAL CARE DATABASE Insights, adjustments, and additional information provided by regional teams 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 PREDICTED VERSUS ACTUAL UNITS SOLD 2004 - log-log scale 8 10 12 14 Predicted 8 10 12 14 Actual R2=0.97
  21. 21. 21 Agenda Introduction to EIU Canback C-GIDD Classic C-GIDD extensions Leveraging C-GIDD in consulting work Appendix: C-GIDD geographic coverage
  22. 22. 22 EIU Canback leverages a variety of statistical methods to model demand growth, calculate elasticities and analyze commercial opportunities POOLED CROSS-SECTIONAL TIME SERIES ANALYSIS 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 cross- sectional time series is a dataset which has observations of multiple cross-sectional units such as countries (X) over time (T) PRAIS-WINSTEN REGRESSION What is it? 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 META ANALYSIS What is it? 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 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 CLASSIC TIME SERIES What is it? 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 CONJOINT What is it? 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 COMMONLY USED STATISTICAL MODELS 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
  23. 23. 23 In one project, Canback leveraged C-GIDD and our management consulting practice for a market sizing and product launch effort in healthcare 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 OBJECTIVE PARASITIC WORM PREVALENCE SANITATION CONDITIONS QUALITY OF HOUSING DISPOSABLE INCOME ACCESS TO HEALTH CARE MATERNAL EDUCATION PRIMARY DRIVERS SECONDARY DRIVERS DRIVERS OF REDUCED INTESTINAL PARASITE PREVALENCE 17% 23% 23% 32% 13,364 17,700 22,508 12,188 87% 96% 98% 79% 44% 75% 79% 72% 36% 55% 65% 41% Disposable income per Household-equivalent in 2005 PPP$ % of women with tertiary education % of children getting DPT3 vaccination % of population with sustained access to improved sanitation % of population living with durable floors, walls, and roofs; water, and electricity China Brazil Mexico Philippines TARGET COUNTRIES C-GIDD database was complemented with data from WHO, UNESCO, and similar databases
  24. 24. 24 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 Interest in prevention of parasitic infections Income INTERPRETATION 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 Algeria Argentina Bangladesh Botswana Burkina Faso Burundi Cambodia Cameroon Colombia Costa Rica Dominican Republic El Salvador Ethiopia Ghana Guinea Guyana Honduras India Indonesia Iran Jordan Kenya South Korea Laos Madagascar Malaysia Mali MauritaniaMongolia Morocco Namibia Nepal Nigeria Oman Pakistan Panama Paraguay Peru Saudi Arabia South Africa Tanzania Thailand Uganda Uruguay Viet Nam Yemen Brazil China Mexico Philippines High prevalence Low socioeconomic readiness High to moderate prevalence High socioeconomic readiness Low prevalence High socioeconomic readiness Statistically fitted trendline Current state of 4 countries under review State of 4 countries under review in 10 years time None of the four countries will reach a stage where prevention is unnecessary for at least another generation COUNTRY PROFILE • 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 Low penetration of powdered beverages and negative brand image impacts the new product perception Believability of the product is a concern FINDINGS FROM CONSUMER ENGAGEMENT Milk has wide appeal as a substitute carrier product Respondents are willing to pay a premium for a new product that fights parasite infection
  25. 25. 25 Finally, Canback delivered specific recommendations for a distribution and marketing strategy as well as provided “to-be” market projections for each country Large supermarkets Given at schools for free Primarily shelved with “health food” Primarily shelved with “regular food” Doctors’ clinics and hospitals Pharmacy Traditional stores WHERE TO SELL OR DISTRIBUTE Mean score on a scale of 1 (strongly disagree) to 5 (strongly agree) 3.98 3.91 3.74 3.73 3.08 2.94 2.37 PROJECTED GROWTH OF FOOD RETAIL Billion CNY 0 200 400 600 800 1000 1200 1400 1600 1800 2006 2011 1,063 1,615 23% 77% 56% 44% cagr: 9% cagr: 26% cagr: 2% Traditional Modern RECOMMENDATION Product Distribution Marketing Price Possible Outcome A: Extension of pre- existing product B: Milk-centric product Small pack sizes for affordability and large pack sizes to give lower unit cost with sustained use • Skewed to modern trade • Initial focus on greater Shanghai area where modern trade is well- developed • Shelved with regular food • Social network- driven: Word-of- mouth • Address believability issues 20-30% premium above current product price • $100M in retail revenue 4-6 years after launch • Contribution to brand image + distribution footprint
  26. 26. 26 Agenda Introduction to EIU Canback C-GIDD Classic C-GIDD extensions Leveraging C-GIDD in consulting work Appendix: C-GIDD geographic coverage
  27. 27. 27Note: Countries in green have subdivisions, see next page Afghanistan Central African Republic Greece Liechtenstein Palau Suriname Albania Chad Greenland Lithuania Palestine Swaziland Algeria Chile Grenada Luxembourg Panama Sweden Andorra China Guatemala Macao Papua New Guinea Switzerland Angola Colombia Guinea Macedonia Paraguay Syria Anguilla Comoros Guinea-Bissau Madagascar Peru Taiwan Antigua and Barbuda Congo-Brazzaville Guyana Malawi Philippines Tajikistan Argentina Congo-Kinshasa Haiti Malaysia Poland Tanzania Armenia Cook Islands Honduras Maldives Portugal Thailand Aruba Costa Rica Hong Kong Mali Puerto Rico Timor-Leste Australia Cote d'Ivoire Hungary Malta Qatar Togo Austria Croatia Iceland Marshall Islands Romania Tonga Azerbaijan Cuba India Mauritania Russia Trinidad and Tobago Bahamas Curacao Indonesia Mauritius Rwanda Tunisia Bahrain Cyprus Iran Mexico Saint Kitts and Nevis Turkey Bangladesh Czech Republic Iraq Micronesia Saint Lucia Turkmenistan Barbados Denmark Ireland Moldova Saint Vincent and the Grenadines Turks and Caicos Islands Belarus Djibouti Israel Monaco Samoa Tuvalu Belgium Dominica Italy Mongolia San Marino Uganda Belize Dominican Republic Jamaica Montenegro Sao Tome and Principe Ukraine Benin Ecuador Japan Montserrat Saudi Arabia United Arab Emirates Bermuda Egypt Jordan Morocco Senegal United Kingdom Bhutan El Salvador Kazakhstan Mozambique Serbia United States Bolivia Equatorial Guinea Kenya Myanmar Seychelles Uruguay Bosnia and Herzegovina Eritrea Kiribati Namibia Sierra Leone Uzbekistan Botswana Estonia Korea, North Nauru Singapore Vanuatu Brazil Ethiopia Korea, South Nepal Sint Maarten Venezuela Brunei Fiji Kosovo Netherlands Slovakia Viet Nam Bulgaria Finland Kuwait New Caledonia Slovenia Virgin Islands, British Burkina Faso France Kyrgyzstan New Zealand Solomon Islands Western Sahara Burundi French Polynesia Laos Nicaragua Somalia Yemen Cambodia Gabon Latvia Niger South Africa Zambia Cameroon Gambia Lebanon Nigeria South Sudan Zimbabwe Canada Georgia Lesotho Norway Spain Cape Verde Germany Liberia Oman Sri Lanka Cayman Islands Ghana Libya Pakistan Sudan Appendix A C-GIDD countries Updated February 2016
  28. 28. 28 Argentina Austria Brazil China Colombia Catamarca Eastern Austria Parana Anhui Amazonia Chaco Southern Austria Pernambuco Beijing Andina Norte Chubut Western Austria Piaui Chongqing Andina Sur Ciudad Autonoma de Buenos Aires Rio de Janeiro Fujian Atlantica Cordoba Bangladesh Rio Grande do Norte Gansu Bogota Corrientes Barisal Rio Grande do Sul Guangdong Orinoquia Entre Rios Chittagong Rondonia Guangxi Pacifica Formosa Dhaka Roraima Guizhou Jujuy Khulna Santa Catarina Hainan Finland La Pampa Rajshahi Sao Paulo Hebei Aland La Rioja Rangpur Sergipe Heilongjiang Mainland Finland Mendoza Sylhet Tocantins Henan Misiones Hubei France Neuquen Belgium Bulgaria Hunan Bassin Parisien Provincia de Buenos Aires Brussels-Capital Region North Bulgaria Inner Mongolia Center-East Rio Negro Flemish Region South Bulgaria Jiangsu East Salta Walloon Region Jiangxi Ile de France San Juan Canada Jilin Mediterranee San Luis Brazil Alberta Liaoning Nord-Pas-de-Calais Santa Cruz Acre British Columbia Ningxia Overseas departments Santa Fe Alagoas Manitoba Qinghai South-West Santiago del Estero Amapa New Brunswick Shaanxi West Tierra del Fuego Amazonas Newfoundland and Labrador Shandong Tucuman Bahia Northwest Territories Shanghai Germany Ceara Nova Scotia Shanxi Baden-Wurttemberg Australia Distrito Federal Nunavut Sichuan Bavaria Australian Capital Territory Espirito Santo Ontario Tianjin Berlin New South Wales Goias Prince Edward Island Tibet Brandenburg Northern Territory Maranhao Quebec Xinjiang Bremen Queensland Mato Grosso Saskatchewan Yunnan Hamburg South Australia Mato Grosso do Sul Yukon Territory Zhejiang Hesse Tasmania Minas Gerais Lower Saxony Victoria Para Mecklenburg-Vorpommern Western Australia Paraiba North Rhine-Westphalia Appendix B C-GIDD subdivisions Updated October 2015
  29. 29. 29 C-GIDD subdivisions, continued Germany India Indonesia Japan Japan Rhineland-Palatinate Jharkhand Gorontalo Chiba Shizuoka Saarland Karnataka Jakarta Raya Ehime Tochigi Saxony Kerala Jambi Fukui Tokushima Saxony-Anhalt Lakshadweep Lampung Fukuoka Tokyo Schleswig-Holstein Madhya Pradesh Maluku Fukushima Tottori Thuringia Maharashtra North Maluku Gifu Toyama Manipur North Sulawesi Gunma Wakayama Greece Meghalaya North Sumatera Hiroshima Yamagata Aegean Islands and Crete Mizoram Papua Hokkaido Yamaguchi Attica Nagaland Riau Hyogo Yamanashi Central Greece Orissa Riau Islands Ibaraki Northern Greece Puducherry South Kalimantan Ishikawa Korea, South Punjab South Sulawesi Iwate Busan Hungary Rajasthan South Sumatera Kagawa Chungcheongbugdo Central Hungary Sikkim Southeast Sulawesi Kagoshima Chungcheongnamdo Great Plain and North Tamil Nadu West Jawa Kanagawa Daegu Transdanubia Telangana West Kalimantan Kochi Daejeon Tripura West Nusa Tenggara Kumamoto Gang'weondo India Uttar Pradesh West Papua Kyoto Gwangju Andaman and Nicobar Islands Uttarakhand West Sulawesi Mie Gyeonggido Andhra Pradesh West Bengal West Sumatera Miyagi Gyeongsangbugdo Arunachal Pradesh Yogyakarta Miyazaki Gyeongsangnamdo Assam Indonesia Nagano Incheon Bihar Aceh Italy Nagasaki Jejudo Chandigarh Bali Center Nara Jeonrabugdo Chhattisgarh Bangka Belitung Islands Islands Niigata Jeonranamdo Dadra and Nagar Haveli Banten North-East Oita Seoul Daman and Diu Bengkulu North-West Okayama Ulsan Delhi Central Jawa South Okinawa Goa Central Kalimantan Osaka Mexico Gujarat Central Sulawesi Japan Saga Aguascalientes Haryana East Jawa Aichi Saitama Baja California Himachal Pradesh East Kalimantan Akita Shiga Baja California Sur Jammu and Kashmir East Nusa Tenggara Aomori Shimane Campeche
  30. 30. 30 C-GIDD subdivisions, continued Mexico Nigeria Nigeria Poland South Africa Chiapas Abia Taraba Central Mpumalanga Chihuahua Adamawa Yobe East Northern Cape Coahuila Akwa Ibom Zamfara North North-West Colima Anambra North-West Western Cape Distrito Federal Bauchi Pakistan South Durango Bayelsa Azad Kashmir South-West Spain Guanajuato Benue Balochistan Canary Islands Guerrero Borno Federally Administered Tribal Areas Portugal Center Hidalgo Cross River Gilgit-Baltistan Azores East Jalisco Delta Islamabad Continental Portugal Madrid Mexico Ebonyi Khyber Pakhtunkhwa Madeira Northeast Michoacan Edo Punjab Northwest Morelos Ekiti Sindh Romania South Nayarit Enugu Macroregion 1 Nuevo Leon Federal Capital Territory Philippines Macroregion 2 Sweden Oaxaca Gombe ARMM Macroregion 3 Eastern Puebla Imo Bicol Macroregion 4 Northern Queretaro Jigawa Cagayan Valley Southern Quintana Roo Kaduna CALABARZON Russia San Luis Potosi Kano Caraga Central Taiwan Sinaloa Katsina Central Luzon Far East Central Sonora Kebbi Central Visayas North Caucasus Eastern Tabasco Kogi Cordillera Northwest Northern Tamaulipas Kwara Davao Siberia Southern Tlaxcala Lagos Eastern Visayas South Veracruz Nassarawa Ilocos Ural Thailand Yucatan Niger MIMAROPA Volga Bangkok and Vicinities Zacatecas Ogun National Capital Region Central Ondo Northern Mindanao South Africa Eastern Netherlands Osun SOCCSKSARGEN Eastern Cape Northeastern Eastern Netherlands Oyo Western Visayas Free State Northern Northern Netherlands Plateau Zamboanga Peninsula Gauteng Southern Southern Netherlands Rivers KwaZulu-Natal Western Western Netherlands Sokoto Limpopo
  31. 31. 31 C-GIDD subdivisions, continued Turkey United States United States Aegean Connecticut South Carolina Central Anatolia Delaware South Dakota Eastern Black Sea District of Columbia Tennessee Eastern Marmara Florida Texas Istanbul Georgia Utah Mediterranean Hawaii Vermont Mideastern Anatolia Idaho Virginia Northeastern Anatolia Illinois Washington Southeastern Anatolia Indiana West Virginia Western Anatolia Iowa Wisconsin Western Black Sea Kansas Wyoming Western Marmara Kentucky Louisiana United Kingdom Maine East Midlands Maryland East of England Massachusetts London Michigan North East Minnesota North West Mississippi Northern Ireland Missouri Scotland Montana South East Nebraska South West Nevada Wales New Hampshire West Midlands New Jersey Yorkshire and the Humber New Mexico New York United States North Carolina Alabama North Dakota Alaska Ohio Arizona Oklahoma Arkansas Oregon California Pennsylvania Colorado Rhode Island
  32. 32. 32 Afghanistan Australia Brazil Brazil Central African Republic China Kabul Sydney Aracaju Vale do Aco Bangui Dalian Baixada Santista Vitoria Dandong Albania Austria Belem Chad Daqing Tirana Vienna Belo Horizonte Bulgaria N'Djamena Datong Blumenau Plovdiv Deyang Algeria Azerbaijan Brasilia Sofia Chile Dezhou Algiers Baku Campinas Concepcion Dongguan Constantine Campo Grande Burkina Faso Santiago de Chile Dongying Oran Bangladesh Cuiaba Bobo Dioulasso Valparaiso Ezhou Chittagong Curitiba Ouagadougou Foshan Angola Dhaka Feira de Santana China Fuling Huambo Khulna Florianopolis Burundi Anqing Fushun Luanda Rajshahi Fortaleza Bujumbura Anshan Fuxin Sylhet Goiania Anyang Fuyang Argentina Joao Pessoa Cambodia Baoding Fuzhou Buenos Aires Belarus Joinville Phnom Penh Baoji Ganzhou La Plata Minsk Juiz de Fora Baotou Guangzhou Mar del Plata Jundiai Cameroon Beijing Guigang Mendoza Belgium Londrina Douala Bengbu Guilin Rosario Antwerp Maceio Yaounde Benxi Guiyang Salta Brussels Manaus Binzhou Haicheng San Miguel de Tucuman Gent Maringa Canada Changchun Haikou Santa Fe Liege Natal Calgary Changde Handan Porto Alegre Edmonton Changsha Hangzhou Armenia Benin Recife Hamilton Changshu Harbin Yerevan Abomey-Calavi Ribeirao Preto Montreal Changzhi Hefei Cotonou Rio de Janeiro Ottawa Changzhou Hegang Australia Salvador Quebec Chaozhou Hengyang Adelaide Bolivia Sao Jose dos Campos Toronto Chengde Heze Brisbane Cochabamba Sao Luis Vancouver Chengdu Hohhot Gold Coast La Paz Sao Paulo Winnipeg Chenzhou Huai'an Melbourne Santa Cruz Sorocaba Chifeng Huaibei Newcastle Teresina Chongqing Huainan Perth Uberlandia Cixi Huangshi Appendix C C-GIDD cities Updated October 2015
  33. 33. 33 China China China China China Congo-Kinshasa Huizhou Luoyang Shaoguan Xi'an Zhaoqing Kisangani Huludao Luzhou Shaoxing Xiangtan Zhengzhou Lubumbashi Huzhou Ma'anshan Shaoyang Xiangyang Zhenjiang Mbuji-Mayi Jiamusi Maoming Shenyang Xiantao Zhongshan Tshikapa Jiangyin Mianyang Shenzhen Xianyang Zhoushan Jiaozuo Mudanjiang Shijiazhuang Xiaogan Zhucheng Costa Rica Jiaxing Nan'an Shiyan Xinghua Zhuhai San Jose Jieyang Nanchang Siping Xingtai Zhuji Jilin Nanchong Suining Xining Zhuzhou Cote d'Ivoire Jimo Nanjing Suqian Xintai Zibo Abidjan Jinan Nanning Suzhou Xinxiang Zigong Bouake Jingzhou Nantong Suzhou Xinyang Zoucheng Jinhua Nanyang Taian Xinyu Zunyi Croatia Jining Neijiang Taixing Xuzhou Zagreb Jinzhou Ningbo Taiyuan Yancheng Colombia Jiujiang Panjin Taizhou Yangquan Barranquilla Cuba Jixi Panzhihua Taizhou Yangzhou Bogota Havana Kaifeng Pingdingshan Tangshan Yantai Bucaramanga Kunming Pingxiang Tengzhou Yibin Cali Czech Republic Laiwu Pizhou Tianjin Yichang Cartagena Brno Langfang Puning Tianmen Yichun Cucuta Ostrava Lanzhou Putian Tianshui Yinchuan Ibague Prague Leshan Qingdao Tongliao Yingkou Medellin Lianyungang Qingyuan Urumqi Yiwu Pereira Denmark Liaocheng Qinhuangdao Wanzhou Yongzhou Copenhagen Liaoyang Qiqihar Weifang Yueqing Congo-Brazzaville Linfen Qitaihe Weihai Yueyang Brazzaville Dominican Republic Linyi Quanzhou Wenling Yulin Pointe-Noire Santiago de los Caballeros Liu'an Rizhao Wenzhou Yuyao Santo Domingo Liupanshui Rugao Wuhan Zaozhuang Congo-Kinshasa Liuyang Rui'an Wuhu Zhangjiakou Bukavu Ecuador Liuzhou Shanghai Wuxi Zhangzhou Kananga Guayaquil Lufeng Shangqiu Wuzhou Zhanjiang Kinshasa Quito Luohe Shantou Xiamen C-GIDD cities, continued
  34. 34. 34 Egypt France Germany India India India Alexandria Toulon Wurzburg Aligarh Jabalpur Raurkela Cairo Toulouse Allahabad Jaipur Saharanpur Port Said Ghana Amravati Jalandhar Salem Suez Gabon Accra Amritsar Jammu Sangli Libreville Kumasi Asansol Jamnagar Siliguri El Salvador Sekondi Takoradi Aurangabad Jamshedpur Solapur San Salvador Georgia Bangalore Jhansi Srinagar Tbilisi Greece Bareilly Jodhpur Surat Eritrea Athens Belgaum Kannur Thiruvananthapuram Asmara Germany Thessaloniki Bhavnagar Kanpur Tiruchirappalli Aachen Bhiwandi Kochi Tiruppur Estonia Augsburg Guatemala Bhopal Kolhapur Ujjain Tallinn Berlin Guatemala City Bhubaneswar Kolkata Vadodara Bonn Bikaner Kota Varanasi Ethiopia Bremen Guinea Bokaro Steel City Kozhikode Vijayawada Addis Ababa Cologne Conakry Chandigarh Lucknow Visakhapatnam Dresden Chennai Ludhiana Warangal Finland Dusseldorf Haiti Coimbatore Madurai Helsinki Erfurt Port-au-Prince Cuttack Malegaon Indonesia Frankfurt Dehra Dun Mangalore Balikpapan France Freiburg Honduras Delhi Meerut Bandar Lampung Bordeaux Hamburg San Pedro Sula Dhanbad Moradabad Bandung Grenoble Hannover Tegucigalpa Durgapur Mumbai Banjarmasin Lille Heidelberg Durg-Bhilai Nagar Mysore Batam Lyon Karlsruhe Hong Kong Erode Nagpur Denpasar Marseille Kiel Hong Kong Firozabad Nanded Jakarta Montpellier Leipzig Gorakhpur Nashik Jambi Nantes Mannheim-LudwigshafenHungary Gulbarga Nellore Makassar Nice Munich Budapest Guntur Patna Malang Paris Nuremberg Guwahati Puducherry Medan Rennes Osnabruck India Gwalior Pune Padang Rouen Ruhr Area Agra Hubli-Dharwad Raipur Palembang Saint-Etienne Saarbrucken Ahmadabad Hyderabad Rajkot Pekanbaru Strasbourg Stuttgart Ajmer Indore Ranchi Pontianak C-GIDD cities, continued
  35. 35. 35 Indonesia Israel Japan Kuwait Malawi Mexico Samarinda Be'er Sheva Osaka Kuwait City Blantyre Mexico City Semarang Haifa Sapporo Lilongwe Monterrey Serang Jerusalem Sendai Kyrgyzstan Morelia Surabaya Tel Aviv-Jaffa Shizuoka Bishkek Malaysia Oaxaca Tasikmalaya Tokyo Ipoh Pachuca Italy Utsunomiya Laos Johor Bahru Poza Rica Iran Bari Vientiane Kuala Lumpur-Klang Valley Puebla Ahvaz Bologna Jordan Kuching Queretaro Esfahan Catania Amman Latvia Penang Reynosa Hamadan Florence Riga Saltillo Karaj Genoa Kazakhstan Mali San Luis Potosi Kerman Milan Almaty Lebanon Bamako Tampico Kermanshah Naples Astana Beirut Tijuana Mashhad Padova Shymkent Mauritania Tlaxcala Orumiyeh Palermo Liberia Nouakchott Toluca Qom Rome Kenya Monrovia Torreon Rasht Turin Mombasa Mexico Tuxtla Gutierrez Shiraz Venice Nairobi Libya Acapulco Veracruz Tabriz Verona Benghazi Aguascalientes Villahermosa Tehran Korea, North Misratah Cancun Xalapa Zahedan Jamaica Chongjin Tripoli Celaya Kingston Hamhung Chihuahua Moldova Iraq Pyongyang Lithuania Cuernavaca Chisinau Baghdad Japan Vilnius Culiacan Basra Fukuoka Korea, South Durango Mongolia Erbil Hamamatsu Busan Luxembourg Guadalajara Ulaanbaatar Karbala Himeji Changwon Luxembourg Hermosillo Kirkuk Hiroshima Cheongju Juarez Morocco Mosul Kobe Daegu Macao Leon Agadir Najaf Kumamoto Daejeon Macao Merida Casablanca Sulaymaniyah Kyoto Gwangju Mexicali Fes Nagoya Jeonju Madagascar Ireland Niigata Seoul Antananarivo Dublin Ulsan C-GIDD cities, continued
  36. 36. 36 Morocco Nigeria Pakistan Poland Russia Saudi Arabia Marrakech Aba Multan Bydgoszcz Lipetsk Jedda Meknes Abuja Peshawar Gdansk Makhachkala Mecca Rabat Benin City Quetta Katowice Moscow Medina Tangier Enugu Rawalpindi Krakow Naberezhnye Chelny Riyadh Ibadan Sargodha Lodz Nizhny Novgorod Tabuk Mozambique Ilorin Sialkot Lublin Novokuznetsk Ta'if Maputo Jos Poznan Novosibirsk Matola Kaduna Palestine Warsaw Omsk Senegal Nampula Kano Gaza Wroclaw Orenburg Dakar Lagos Penza Touba Myanmar Maiduguri Panama Portugal Perm Mandalay Nnewi Panama City Lisbon Rostov Serbia Nay Pyi Taw Onitsha Porto Ryazan Belgrade Rangoon Osogbo Paraguay Saint Petersburg Owerri Asuncion Puerto Rico Samara Sierra Leone Nepal Port Harcourt San Juan Saratov Freetown Kathmandu Uyo Peru Tolyatti Warri Arequipa Qatar Tomsk Singapore Netherlands Zaria Chiclayo Doha Tula Singapore Amsterdam Lima Tyumen Eindhoven Norway Trujillo Romania Ufa Slovakia Hague, The Oslo Bucharest Ulyanovsk Bratislava Rotterdam Philippines Vladivostok Utrecht Oman Antipolo Russia Volgograd Slovenia Muscat Bacolod Astrakhan' Voronezh Ljubljana New Zealand Cagayan de Oro Barnaul Yaroslavl Auckland Pakistan Cebu Chelyabinsk Yekaterinburg Somalia Bahawalpur Dasmarinas Irkutsk Hargeysa Nicaragua Faisalabad Davao Izhevsk Rwanda Mogadishu Managua Gujranwala General Santos City Kazan Kigali Hyderabad Manila Kemerovo South Africa Niger Islamabad Zamboanga Khabarovsk Saudi Arabia Cape Town Niamey Karachi Krasnodar Dammam Durban Lahore Krasnoyarsk Hufuf-Mubarraz Emfuleni C-GIDD cities, continued
  37. 37. 37 South Africa Syria Turkey United Arab Emirates United States Johannesburg Aleppo Adana Sharjah Boise City Port Elizabeth Al-Raqqa Ankara Boston Pretoria Damascus Antalya United Kingdom Buffalo Hamah Bursa Belfast Charleston Spain Homs Diyarbakir Birmingham Charlotte Barcelona Latakia Eskisehir Bournemouth Chattanooga Bilbao Gaziantep Bristol Chicago Cordoba Taiwan Gebze Cardiff Cincinnati Granada Hsinchu Istanbul Coventry Cleveland Las Palmas Kaohsiung Izmir Edinburgh Colorado Springs Madrid Taichung-Changhua Kayseri Glasgow Columbia Malaga Tainan Konya Kingston-upon-Hull Columbus Murcia Taipei-Keelung Mersin Leeds-Bradford Dallas-Fort Worth Palma di Mallorca Taoyuan-Jhongli Leicester Dayton Seville Turkmenistan Liverpool Deltona-Daytona Beach-Ormond Beach Valencia Tajikistan Ashgabat London Denver Vigo Dushanbe Manchester Des Moines Zaragoza Uganda Newcastle Detroit Tanzania Kampala Nottingham Durham Sri Lanka Dar es Salaam Portsmouth El Paso Colombo Mwanza Ukraine Sheffield Fort Myers Dnipropetrovs'k Fresno Sudan Thailand Donetsk United States Grand Rapids Khartoum Bangkok Kharkov Akron Greensboro Nyala Chiang Mai Kiev Albany Greenville Samut Prakan Krivoi Rog Albuquerque Harrisburg Sweden Lvov Allentown Hartford Gothenburg Togo Mykolaiv Atlanta Honolulu Malmo Lome Odessa Augusta Houston Stockholm Zaporizhzhya Austin Indianapolis Tunisia Bakersfield Jackson Switzerland Safaqis United Arab Emirates Baltimore Jacksonville Geneva Tunis Abu Dhabi Baton Rouge Kansas City Zurich Dubai Birmingham Knoxville C-GIDD cities, continued
  38. 38. 38 United States United States Uzbekistan Lakeland Richmond Tashkent Lancaster Riverside-San Bernardino Las Vegas Rochester Venezuela Little Rock Sacramento Barcelona-Puerto La Cruz Los Angeles Saint Louis Barquisimeto Louisville Salt Lake City Caracas Madison San Antonio Ciudad Guayana McAllen San Diego Maracaibo Memphis San Francisco Maracay Miami San Jose Valencia Milwaukee Sarasota Minneapolis-Saint Paul Scranton Viet Nam Modesto Seattle Bien Hoa Nashville Spokane Can Tho New Haven Springfield Da Nang New Orleans Stamford Haiphong New York Stockton Hanoi Ogden Syracuse Ho Chi Minh City Oklahoma City Tampa Omaha Toledo Yemen Orlando Tucson Aden Oxnard Tulsa Sana'a' Palm Bay Virginia Beach Taiz Philadelphia Washington Phoenix Wichita Zambia Pittsburgh Winston-Salem Kitwe Portland Worcester Lusaka Portland Youngstown Providence Zimbabwe Provo-Orem Uruguay Bulawayo Raleigh Montevideo Harare C-GIDD cities, continued
  39. 39. 39 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
  40. 40. 40 Canback contact information AMERICAS Boston EIU Canback, Inc. 210 Broadway, Suite 303 Cambridge MA 02139 +1-617-399-1300 Irina Blinova Mexico City 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 Chicago EIU Canback USA 500 N. Michigan Ave. Suite 1925 Chicago IL 60611 +1-312-853-3716 or 3823 Tom Andrews Maureen Lanigan Sao Paulo EIU Canback Brazil Av. Brigadeiro Faria Lima, 3144 3º andar Jardim Paulistano São Paulo, 01451-000 +55-11-3845 4767 Marcio Zanetti EUROPE London EIU Canback Europe 20 Cabot Square London E14 4QW +44-20-7576-8181 Chris Pearce Asif Chaudhary 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 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 ASIA Beijing 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 Shanghai EIU Canback China Rm 2508A, 25/F, Rui Jin Bldg 205 Mao Ming South Rd, Shanghai 200020 +86-21-6473-7128 Seumas Graham Singapore EIU Canback Southeast Asia 8 Cross St, #23-01 PWC Bldg. Singapore 048424 +65-6534-5177 Vanny Dang Tokyo EIU Canback Japan Ginza Wall Building UCF 5F 6-13-16 Ginza Chuo-ku, Tokyo 104-0061 +81-3-6338-0002 Shin Ito Jakarta EIU Canback SE Asia Jl. Tiang Bendera 5 no. 2A DKI Jakarta 11230 +62-812-8743 7578 Teddy Purnomo