The 2009 Report on Manufacturing Instruments and Related Devices for Measuring, Displaying, Indicating, Recording, Transmitting, and Controlling Industrial Process Variables: World Market Segmentation by City
ICON Group International, May 2009, Pages: 360
Market Potential Estimation Methodology
Overview
This study covers the world outlook for manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables across more than 2000 cities. For the year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for the city in question (in millions of U.S. dollars), the percent share the city is of the region and of the globe. These comparative benchmarks allow the reader to quickly gauge a city vis-à-vis others. Using econometric models which project fundamental economic dynamics within each country and across countries, latent demand estimates are created. This report does not discuss the specific players in the market serving the latent demand, nor specific details at the product level. The study also does not consider short-term cyclicalities that might affect realized sales. The study, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved.
This study does not report actual sales data (which are simply unavailable, in a comparable or consistent manner in virtually all of the cities of the world). This study gives, however, my estimates for the worldwide latent demand, or the P.I.E. for manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables. It also shows how the P.I.E. is divided across the world’s cities. In order to make these estimates, a multi-stage methodology was employed that is often taught in courses on international strategic planning at graduate schools of business.
What is Latent Demand and the P.I.E.?
The concept of latent demand is rather subtle. The term latent typically refers to something that is dormant, not observable, or not yet realized. Demand is the notion of an economic quantity that a target population or market requires under different assumptions of price, quality, and distribution, among other factors. Latent demand, therefore, is commonly defined by economists as the industry earnings of a market when that market becomes accessible and attractive to serve by competing firms. It is a measure, therefore, of potential industry earnings (P.I.E.) or total revenues (not profit) if a market is served in an efficient manner. It is typically expressed as the total revenues potentially extracted by firms. The “market” is defined at a given level in the value chain. There can be latent demand at the retail level, at the wholesale level, the manufacturing level, and the raw materials level (the P.I.E. of higher levels of the value chain being always smaller than the P.I.E. of levels at lower levels of the same value chain, assuming all levels maintain minimum profitability).
The latent demand for manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables is not actual or historic sales. Nor is latent demand future sales. In fact, latent demand can be lower either lower or higher than actual sales if a market is inefficient (i.e., not representative of relatively competitive levels). Inefficiencies arise from a number of factors, including the lack of international openness, cultural barriers to consumption, regulations, and cartel-like behavior on the part of firms. In general, however, latent demand is typically larger than actual sales in a city market.
Another reason why sales do not equate to latent demand is exchange rates. In this report, all figures assume the long-run efficiency of currency markets. Figures, therefore, equate values based on purchasing power parities across countries. Short-run distortions in the value of the dollar, therefore, do not figure into the estimates. Purchasing power parity estimates of country income were collected from official sources, and extrapolated using standard econometric models. The report uses the dollar as the currency of comparison, but not as a measure of transaction volume. The units used in this report are: US $ mln.
For reasons discussed later, this report does not consider the notion of “unit quantities”, only total latent revenues (i.e., a calculation of price times quantity is never made, though one is implied). The units used in this report are U.S. dollars not adjusted for inflation (i.e., the figures incorporate inflationary trends) and not adjusted for future dynamics in exchange rates (i.e., the figures reflect average exchange rates over recent history). If inflation rates or exchange rates vary in a substantial way compared to recent experience, actually sales can also exceed latent demand (when expressed in U.S. dollars, not adjusted for inflation). On the other hand, latent demand can be typically higher than actual sales as there are often distribution inefficiencies that reduce actual sales below the level of latent demand.
As mentioned earlier, this study is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved. If fact, all the current products or services on the market can cease to exist in their present form (i.e., at a brand-, R&D specification, or corporate-image level) and all the players can be replaced by other firms (i.e., via exits, entries, mergers, bankruptcies, etc.), and there will still be an international latent demand for manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables at the aggregate level. Product and service offering details, and the actual identity of the players involved, while important for certain issues, are relatively unimportant for estimates of latent demand.
The Methodology
In order to estimate the latent demand for manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables on a city-by-city basis, I used a multi-stage approach. Before applying the approach, one needs a basic theory from which such estimates are created. In this case, I heavily rely on the use of certain basic economic assumptions. In particular, there is an assumption governing the shape and type of aggregate latent demand functions. Latent demand functions relate the income of a country, city, state, household, or individual to realized consumption. Latent demand (often realized as consumption when an industry is efficient), at any level of the value chain, takes place if an equilibrium in realized. For firms to serve a market, they must perceive a latent demand and be able to serve that demand at a minimal return. The single most important variable determining consumption, assuming latent demand exists, is income (or other financial resources at higher levels of the value chain). Other factors that can pivot or shape demand curves include external or exogenous shocks (i.e., business cycles), and or changes in utility for the product in question.
Ignoring, for the moment, exogenous shocks and variations in utility across countries, the aggregate relation between income and consumption has been a central theme in economics. The figure below concisely summarizes one aspect of problem. In the 1930s, John Meynard Keynes conjectured that as incomes rise, the average propensity to consume would fall. The average propensity to consume is the level of consumption divided by the level of income, or the slope of the line from the origin to the consumption function. He estimated this relationship empirically and found it to be true in the short-run (mostly based on cross-sectional data). The higher the income, the lower the average propensity to consume. This type of consumption function is labeled "A" in the figure below (note the rather flat slope of the curve). In the 1940s, another macroeconomist, Simon Kuznets, estimated long-run consumption functions which indicated that the marginal propensity to consume was rather constant (using time series data across countries). This type of consumption function is show as "B" in the figure below (note the higher slope and zero-zero intercept). The average propensity to consume is constant.
Is it declining or is it constant? A number of other economists, notably Franco Modigliani and Milton Friedman, in the 1950s (and Irving Fisher earlier), explained why the two functions were different using various assumptions on intertemporal budget constraints, savings, and wealth. The shorter the time horizon, the more consumption can depend on wealth (earned in previous years) and business cycles. In the long-run, however, the propensity to consume is more constant. Similarly, in the long run, households, industries or countries with no income eventually have no consumption (wealth is depleted). While the debate surrounding beliefs about how income and consumption are related and interesting, in this study a very particular school of thought is adopted. In particular, we are considering the latent demand for manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables across some 230 countries. The smallest have fewer than 10,000 inhabitants. I assume that all of these counties fall along a "long-run" aggregate consumption function. This long-run function applies despite some of these countries having wealth, current income dominates the latent demand for manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables. So, latent demand in the long-run has a zero intercept. However, I allow firms to have different propensities to consume (including being on consumption functions with differing slopes, which can account for differences in industrial organization, and end-user preferences).
Given this overriding philosophy, I will now describe the methodology used to create the latent demand estimates for manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables. Since ICON Group has asked me to apply this methodology to a large number of categories, the rather academic discussion below is general and can be applied to a wide variety of categories, not just manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables.
Step 1. Product Definition and Data Collection
Any study of latent demand across countries requires that some standard be established to define “efficiently served”. Having implemented various alternatives and matched these with market outcomes, I have found that the optimal approach is to assume that certain key countries or cities are more likely to be at or near efficiency than others. These are given greater weight than others in the estimation of latent demand compared to others for which no known data are available. Of the many alternatives, I have found the assumption that the world’s highest aggregate income and highest income-per-capita markets reflect the best standards for “efficiency”. High aggregate income alone is not sufficient (i.e., China has high aggregate income, but low income per capita and can not assumed to be efficient). Aggregate income can be operationalized in a number of ways, including gross domestic product (for industrial categories), or total disposable income (for household categories; population times average income per capita, or number of households times average household income per capita). Brunei, Nauru, Kuwait, and Lichtenstein are examples of countries with high income per capita, but not assumed to be efficient, given low aggregate level of income (or gross domestic product); these countries have, however, high incomes per capita but may not benefit from the efficiencies derived from economies of scale associated with large economies. Only countries with high income per capita and large aggregate income are assumed efficient. This greatly restricts the pool of countries to those in the OECD (Organization for Economic Cooperation and Development), like the United States, or the United Kingdom (which were earlier than other large OECD economies to liberalize their markets).
The selection of countries is further reduced by the fact that not all countries in the OECD report industry revenues at the category level. Countries that typically have ample data at the aggregate level that meet the efficiency criteria include the United States, the United Kingdom and in some cases France and Germany.
Latent demand is therefore estimated using data collected for relatively efficient markets from independent data sources (e.g. Euromonitor, Mintel, Thomson Financial Services, the U.S. Industrial Outlook, the World Resources Institute, the Organization for Economic Cooperation and Development, various agencies from the United Nations, industry trade associations, the International Monetary Fund, and the World Bank). Depending on original data sources used, the definition of “manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables” is established. In the case of this report, the data were reported at the aggregate level, with no further breakdown or definition. In other words, any potential product or service that might be incorporated within manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables falls under this category. Public sources rarely report data at the disaggregated level in order to protect private information from individual firms that might dominate a specific product-market. These sources will therefore aggregate across components of a category and report only the aggregate to the public. While private data are certainly available, this report only relies on public data at the aggregate level without reliance on the summation of various category components. In other words, this report does not aggregate a number of components to arrive at the “whole”. Rather, it starts with the “whole”, and estimates the whole for all cities and the world at large (without needing to know the specific parts that went into the whole in the first place).
Given this caveat, this study covers “manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables” as defined by the North American Industrial Classification system or NAICS (pronounced “nakes”). For a complete definition of manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables, please refer to the Web site at http://www.icongrouponline.com/codes/NAICS.html. The NAICS code for manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables is 334513. It is for this definition of manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables that the aggregate latent demand estimates are derived. “Manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables” is specifically defined as follows:
334513
This U.S. industry comprises establishments primarily engaged in manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables. These instruments measure, display or control (monitor, analyze, and so forth) industrial process variables, such as temperature, humidity, pressure, vacuum, combustion, flow, level, viscosity, density, acidity, concentration, and rotation.
3345130
PROCESS CONTROL INSTRUMENTS
33451300
Process control instruments
3345130000
Process control instruments
33451301
Process control instruments
3345130100
Process control instruments
3345130101
General purpose control system instruments and related equipment, electronic systems, unified architecture, controllers (recording, indicating, or blind)
3345130103
General purpose control system instruments and related equipment, electronic systems, unified architecture, recorders, with or without sefl_ contained set_point stations
3345130105
General purpose control system instruments and related equipment, electronic systems, unified architecture, indicators, with or without sefl_ contained set_point stations
3345130107
General purpose control system instruments and related equipment, electronic systems, unified architecture, auxiliary stations and analog computing devices (manual loaders, ratio stations, etc.)
3345130109
General purpose control system instruments and related equipment, electronic systems, non_unified architecture, all types (except multi_ function process computers)
3345130111
General purpose control system instruments and related equipment, industrial multi_function process computers
3345130113
General purpose control system instruments and related equipment, industrial pneumatic systems, controllers (recording, indicating, or blind)
3345130115
General~purpose pneumatic recorders, with or without self~contained set~ point stations
3345130116
General purpose control system instruments and related equipment, industrial pneumatic systems, recorders and indicators, with or without self_contained set_point stations
3345130117
General~purpose pneumatic indicators, with or without self~contained set~ point stations
3345130119
General purpose control system instruments and related equipment, industrial pneumatic systems, auxiliary stations and analog computing devices (manual loaders, ratio stations, adders, etc.)
334513011G
General purpose control system instruments and related equipment, electrical and electronic measuring types, direct_deflecting type controllers, indicators, and recorders
334513011J
Electromechanical self~balancing electric or pneumatic controllers, indicators, recorders, and integrators for all other process variables
3345130121
General purpose control system instruments and related equipment, industrial pneumatic systems, receiver_type gauges, analog and digital
3345130123
General purpose control system instruments and related equipment, industrial annunciators, electro_mechanical and solid_state types
33451302
Process control instruments other than general~purpose
334513021A
All other continuous process gas analyzers for on~stream gas and liquid analysis
334513021C
Continuous process Ph analyzers for on~stream gas and liquid analysis
334513021E
All other continuous process liquid analyzers for on~stream gas and liquid analysis
334513021L
Electrical and electronic digital indicators for all other process variables
334513021M
Electrical and electronic transmitters producing standardized electric or pneumatic analog transmission signals for all other process variables
334513021P
Mechanical noncontrol indicating or recording controllers and recorders for all other process variables
334513021R
Mechanical indicators for all other process variables
334513021T
Mechanical transmitters producing standardized electric or pneumatic analog transmission signals for all other process variables
3345130225
Direct~deflecting controllers for electrical and electronic temperature measuring instruments
3345130227
Direct~deflecting indicators and recorders for electrical and electronic temperature measuring instruments
3345130229
Electromechanical self~balancing controllers for electrical and electronic temperature measuring instruments
334513022A
All other industrial process temperature instruments
334513022C
All other industrial process flow and liquid level instruments
334513022E
All other industrial continuous process instruments
334513022G
All other industrial process instruments
3345130231
Electromechanical self~balancing indicators, recorders, and integrators for electrical and electronic temperature measuring instruments
3345130233
Electronic controllers for electrical and electronic temperature measuring sensors
3345130235
Digital indicators for electrical and electronic temperature measuring sensors (exclude data loggers)
3345130237
Electric transmitters producing standardized electric analog transmission signals for all types of temperature sensors
3345130239
Pneumatic transmitters producing standardized electric analog transmission signals for all types of temperature sensors
3345130241
Mechanical temperature measuring and filled systems indicating or recording controllers
3345130243
Mechanical temperature measuring and filled systems recorders, noncontrol
3345130245
Mechanical temperature measuring and filled systems indicators, excluding indoor~outdoor and other household or appliance type thermometers
3345130247
Mechanical temperature measuring and filled systems, transmitters producing standardized electric or pneumatic analog transmission signals
3345130249
Thermocouples and thermocouple lead wire for primary temperature sensors, excluding aircraft types
3345130251
All other types of primary temperature sensors, excluding aircraft types
3345130253
Pressure (gauge, absolute, vacuum) and draft indicating or recording controllers
3345130255
Pressure (gauge, absolute, vacuum) and draft noncontrol recorders
3345130257
Pressure (gauge, absolute, vacuum) and draft indicators 3~inch diameter and over
3345130259
Pressure (gauge, absolute, vacuum) and draft indicators under 3~inch diameter
3345130261
Pressure (gauge, absolute, vacuum) and draft transmitters producing standardized electronic analog transmission signals
3345130263
Pressure (gauge, absolute, vacuum) and draft transmitters producing standardized pneumatic analog transmission signals
3345130265
Flow and liquid level measuring differential pressure type indicating or recording controllers
3345130267
Flow and liquid level measuring differential pressure type noncontrol recorders and indicators
3345130269
Flow and liquid level measuring differential pressure transmitters producing standardized electronic analog transmission signals
3345130271
Flow and liquid level measuring differential pressure transmitters producing standardized pneumatic analog transmission signals
3345130273
Flow and liquid level measuring differential primary pressure sensors (including load cells and strain gauges)
3345130275
Flow and liquid level measuring differential pressure primary flow elements
3345130277
Electromagnetic primary device flowmeters
3345130279
Electromagnetic secondary type flowmeters
3345130281
Capacitance, ultrasonic, and other electronic instruments for flow and liquid level measuring instruments
3345130283
Variable area controlling, recording, indicating, and transmitting instruments and associated primary flow elements
3345130285
Float and displacement controlling, recording, indicating, and transmitting instruments and associated primary flow elements
3345130287
Turbine and propeller controlling, recording, indicating, and transmitting instruments and associated primary flow elements
3345130289
Mass flow controlling, recording, indicating, and transmitting instruments and associated primary flow elements
3345130291
All other controlling, recording, indicating, and transmitting instruments and associated primary flow elements
3345130293
Humidity controlling, recording, indicating, and transmitting instruments and associated primary humidity elements, excluding home and general~ purpose type
3345130295
Continuous process chromatographic analyzers for on~stream gas and liquid analysis
3345130297
Continuous process infrared analyzers for on~stream gas and liquid analysis
3345130299
Continuous process oxygen analyzers for on~stream gas and liquid analysis
33451303
Parts, supplies, and accessories for other industrial process instruments
334513032J
Parts, supplies, accessories, and other primary sensors for primarily temperature instruments
334513032L
Parts, supplies, accessories, and other primary sensors for primarily flow and liquid level instruments
334513032N
Parts, supplies, accessories, and other primary sensors for primarily continuous process instruments
334513032P
Parts, supplies, accessories, and other primary sensors for primarily industrial instruments
3345131
Industrial process control instrument mfg
334513M
Miscellaneous receipts
334513P
Primary products
334513S
Secondary products
334513SM
Secondary products and miscellaneous receipts
Furthermore, the definition of NAICS code 334513 includes the following:
Absorption analyzers, industrial process type (e.g., infrared), manufacturing
Acidity (i.e., pH) instruments, industrial process type, manufacturing
Analyzers, industrial process control type, manufacturing
Annunciators, relay and solid-state types, industrial display, manufacturing
Boiler controls, industrial, power, and marine-type, manufacturing
Buoyancy instruments, industrial process-type, manufacturing
Chromatographs, industrial process-type, manufacturing
Combustion control instruments (except commercial, household furnace-type) manufa
Controllers for process variables (e.g., electric, electronic, mechanical, pneuma
Coulometric analyzers, industrial process-type, manufacturing
Data loggers, industrial process-type, manufacturing
Density and specific gravity instruments, industrial process-type, manufacturing
Differential pressure instruments, industrial process-type, manufacturing
Digital displays of process variables manufacturing
Display instruments, industrial process control-type, manufacturing
Draft gauges, industrial process-type, manufacturing
Electric and electronic controllers, industrial process-type, manufacturing
Electrodes used in industrial process measurement manufacturing
Electrolytic conductivity instruments, industrial process-type, manufacturing
Electromagnetic flowmeters manufacturing
Flow instruments, industrial process-type, manufacturing
Fluidic devices, circuits, and systems for process control, manufacturing
Gas analyzers, industrial process-type, manufacturing
Gas and liquid analysis instruments, industrial process-type, manufacturing
Gas chromatographic instruments, industrial process-type, manufacturing
Gas flow instrumentation, industrial process-type, manufacturing
Gauges (i.e., analog, digital), industrial process-type, manufacturing
Humidity instruments, industrial process-type, manufacturing
Hydrometers, industrial process-type, manufacturing
Hygrometers, industrial process-type, manufacturing
Indicators, industrial process control-type, manufacturing
Industrial process control instruments manufacturing
Infrared instruments, industrial process-type, manufacturing
Instruments for industrial process control manufacturing
Level and bulk measuring instruments, industrial process-type, manufacturing
Liquid analysis instruments, industrial process-type, manufacturing
Liquid concentration instruments, industrial process-type, manufacturing
Liquid level instruments, industrial process-type, manufacturing
Magnetic flow meters, industrial process-type, manufacturing
Manometers, industrial process-type, manufacturing
Measuring instruments, industrial process control-type, manufacturing
Mechanical measuring instruments, industrial process-type, manufacturing
Meters, industrial process control-type, manufacturing
Moisture meters, industrial process-type, manufacturing
Panelboard indicators, recorders, and controllers, receiver industrial process-ty
Pneumatic controllers, industrial process type, manufacturing
Potentiometric instruments (except X-Y recorders), industrial process-type, manuf
Pressure gauges (e.g., dial, digital), industrial process-type, manufacturing
Pressure instruments, industrial process-type, manufacturing
Primary elements for process flow measurement (i.e., orifice plates) manufacturin
Primary process temperature sensors manufacturing
Process control instruments, industrial, manufacturing
Programmers, process-type, manufacturing
Pyrometers, industrial process-type, manufacturing
Recorders, industrial process control-type, manufacturing
Refractometers, industrial process-type, manufacturing
Resistance thermometers and bulbs, industrial process-type, manufacturing
Telemetering instruments, industrial process-type, manufacturing
Temperature instruments, industrial process-type (except glass and bimetal thermo
Thermal conductivity instruments, industrial process-type, manufacturing
Thermistors, industrial process-type, manufacturing
Thermocouples, industrial process-type, manufacturing
Thermometers, filled system industrial process-type, manufacturing
Time cycle and program controllers, industrial process-type, manufacturing
Transmitters, industrial process control-type, manufacturing
Turbidity instruments, industrial process-type, manufacturing
Turbine flow meters, industrial process-type, manufacturing
Variable control instruments, industrial process-type, manufacturing
Viscosimeters, industrial process-type, manufacturing
Water quality monitoring and control systems manufacturing.
Step 2. Filtering and Smoothing
Based on the aggregate view of manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables as defined above, data were then collected for as many similar countries and cities as possible for that same definition, at the same level of the value chain. This generates a convenience sample from which comparable figures are available. If the series in question do not reflect the same accounting period, then adjustments are made. In order to eliminate short-term effects of business cycles, the series are smoothed using an 2 year moving average weighting scheme (longer weighting schemes do not substantially change the results). If data are available for a country, but these reflect short-run aberrations due to exogenous shocks (such as would be the case of beef sales in a country stricken with foot and mouth disease), these observations were dropped or "filtered" from the analysis.
Step 3. Filling in Missing Values
In some cases, data are available for countries or cities on a sporadic basis. In other cases, data may be available for only one year. From a Bayesian perspective, these observations should be given greatest weight in estimating missing years. Assuming that other factors are held constant, the missing years are extrapolated using changes and growth in aggregate national income. Based on the overriding philosophy of a long-run consumption function (defined earlier), cities which have missing data for any given year, are estimated based on historical dynamics of aggregate income for that country.
Step 4. Varying Parameter, Non-linear Estimation
Given the data available from the first three steps, the latent demand is estimated using a “varying-parameter cross-sectionally pooled time series model”. Simply stated, the effect of income on latent demand is assumed to be constant across cities unless there is empirical evidence to suggest that this effect varies (i.e., the slope of the income effect is not necessarily same for all countries). This assumption applies across cities along the aggregate consumption function, but also over time (i.e., not all cities are perceived to have the same income growth prospects over time and this effect can vary from city to city as well). Another way of looking at this is to say that latent demand for manufacturing instruments and related devices for measuring, displaying, indicating, recording, transmitting, and controlling industrial process variables is more likely to be similar across cities that have similar characteristics in terms of economic development (i.e., African cities will have similar latent demand structures controlling for the income variation across
1 INTRODUCTION & METHODOLOGY 11
1.1 Overview and Definitions 11
1.2 Market Potential Estimation Methodology 11
1.2.1 Overview 11
1.2.2 What is Latent Demand and the P.I.E.? 12
1.2.3 The Methodology 13
1.2.3.1 Step 1. Product Definition and Data Collection 14
1.2.3.2 Step 2. Filtering and Smoothing 22
1.2.3.3 Step 3. Filling in Missing Values 22
1.2.3.4 Step 4. Varying Parameter, Non-linear Estimation 22
1.2.3.5 Step 5. Fixed-Parameter Linear Estimation 23
1.2.3.6 Step 6. Aggregation and Benchmarking 23
2 USING THE DATA 24
3 CITY SEGMENTS RANKED BY MARKET SIZE 25
3.1 Top 15 Markets 25
3.2 Markets 16 to 30 26
3.3 Remaining Cities by Market Rank 27
4 CITY SEGMENTS IN ALPHABETICAL ORDER 130
4.1 A: from Aalborg to Az Zawiyah 130
4.2 B: from Bacolod to Bydgoszcz 137
4.3 C: from Caaguazu to Cyangugu 145
4.4 D: from Da Nang to Dzhizak 154
4.5 E: from East London to Esteli 158
4.6 F: from Fagatogo to Funchal 160
4.7 G: from Gabes to Gyumri 163
4.8 H: from Hachinohe to Hyderabad 167
4.9 I: from Iasi to Izmir 171
4.10 J: from Jaboatao to Jyvaskyla 174
4.11 K: from Kabul to Kzyl-Orda 177
4.12 L: from La Ceiba to Lyon 185
4.13 M: from Macae to Mzuzu 191
4.14 N: from Nacala to Nzerekore 201
4.15 O: from Oaklahoma City to Oyem 206
4.16 Ö: from Örebro to Örebro 208
4.17 P: from Pago Pago to Pyuthan 209
4.18 Q: from Qandahar to Quito 216
4.19 R: from Rabat to Rustavi 217
4.20 S: from S. Luis Potosi to Szombathely 220
4.21 T: from Tabligbo to Tyre 232
4.22 U: from Uberaba to Utulei 240
4.23 V: from Vacoas-Phoenix to Vukovar 242
4.24 W: from Wadi Medani to Wuhan 245
4.25 X: from Xalapa to Xian 246
4.26 Y: from Yamagata to Yungkang 247
4.27 Z: from Zadar to Zvishavane 248
5 CITY SEGMENTS RANKED BY COUNTRY 250
5.1 Afghanistan 250
5.2 Albania 250
5.3 Algeria 251
5.4 American Samoa 251
5.5 Andorra 252
5.6 Angola 252
5.7 Antigua and Barbuda 252
5.8 Argentina 253
5.9 Armenia 254
5.10 Aruba 254
5.11 Australia 255
5.12 Austria 255
5.13 Azerbaijan 256
5.14 Bahrain 256
5.15 Bangladesh 257
5.16 Barbados 257
5.17 Belarus 258
5.18 Belgium 258
5.19 Belize 259
5.20 Benin 259
5.21 Bermuda 259
5.22 Bhutan 260
5.23 Bolivia 260
5.24 Bosnia and Herzegovina 261
5.25 Botswana 261
5.26 Brazil 262
5.27 Brunei 267
5.28 Bulgaria 268
5.29 Burkina Faso 268
5.30 Burma 269
5.31 Burundi 269
5.32 Cambodia 269
5.33 Cameroon 270
5.34 Canada 270
5.35 Cape Verde 271
5.36 Central African Republic 271
5.37 Chad 272
5.38 Chile 272
5.39 China 273
5.40 Christmas Island 273
5.41 Colombia 274
5.42 Comoros 274
5.43 Congo (formerly Zaire) 275
5.44 Cook Islands 275
5.45 Costa Rica 276
5.46 Cote dIvoire 276
5.47 Croatia 277
5.48 Cuba 277
5.49 Cyprus 278
5.50 Czech Republic 278
5.51 Denmark 279
5.52 Djibouti 279
5.53 Dominica 280
5.54 Dominican Republic 280
5.55 Ecuador 281
5.56 Egypt 281
5.57 El Salvador 282
5.58 Equatorial Guinea 282
5.59 Estonia 282
5.60 Ethiopia 283
5.61 Fiji 283
5.62 Finland 284
5.63 France 284
5.64 French Guiana 285
5.65 French Polynesia 285
5.66 Gabon 285
5.67 Georgia 286
5.68 Germany 286
5.69 Ghana 287
5.70 Greece 287
5.71 Greenland 288
5.72 Grenada 288
5.73 Guadeloupe 289
5.74 Guam 289
5.75 Guatemala 290
5.76 Guinea 290
5.77 Guinea-Bissau 290
5.78 Guyana 291
5.79 Haiti 291
5.80 Honduras 292
5.81 Hong Kong 292
5.82 Hungary 293
5.83 Iceland 293
5.84 India 294
5.85 Indonesia 295
5.86 Iran 296
5.87 Iraq 296
5.88 Ireland 297
5.89 Israel 297
5.90 Italy 298
5.91 Jamaica 298
5.92 Japan 299
5.93 Jordan 302
5.94 Kazakhstan 302
5.95 Kenya 303
5.96 Kiribati 303
5.97 Kuwait 303
5.98 Kyrgyzstan 304
5.99 Laos 304
5.100 Latvia 304
5.101 Lebanon 305
5.102 Lesotho 305
5.103 Liberia 305
5.104 Libya 306
5.105 Liechtenstein 306
5.106 Lithuania 307
5.107 Luxembourg 307
5.108 Macau 307
5.109 Madagascar 308
5.110 Malawi 308
5.111 Malaysia 309
5.112 Maldives 309
5.113 Mali 310
5.114 Malta 310
5.115 Marshall Islands 310
5.116 Martinique 311
5.117 Mauritania 311
5.118 Mauritius 312
5.119 Mexico 313
5.120 Micronesia Federation 314
5.121 Moldova 314
5.122 Monaco 314
5.123 Mongolia 315
5.124 Morocco 315
5.125 Mozambique 316
5.126 Namibia 316
5.127 Nauru 316
5.128 Nepal 317
5.129 New Caledonia 317
5.130 New Zealand 318
5.131 Nicaragua 318
5.132 Niger 319
5.133 Nigeria 319
5.134 Niue 320
5.135 Norfolk Island 320
5.136 North Korea 320
5.137 Norway 321
5.138 Oman 321
5.139 Pakistan 322
5.140 Palau 322
5.141 Palestine 322
5.142 Panama 323
5.143 Papua New Guinea 323
5.144 Paraguay 324
5.145 Peru 324
5.146 Philippines 325
5.147 Poland 326
5.148 Portugal 326
5.149 Puerto Rico 327
5.150 Qatar 327
5.151 Republic of Congo 328
5.152 Reunion 328
5.153 Romania 329
5.154 Russia 329
5.155 Rwanda 330
5.156 San Marino 330
5.157 Sao Tome E Principe 330
5.158 Saudi Arabia 331
5.159 Senegal 331
5.160 Seychelles 332
5.161 Sierra Leone 332
5.162 Singapore 332
5.163 Slovakia 333
5.164 Slovenia 333
5.165 Solomon Islands 333
5.166 Somalia 334
5.167 South Africa 334
5.168 South Korea 335
5.169 Spain 336
5.170 Sri Lanka 336
5.171 St. Kitts and Nevis 337
5.172 St. Lucia 337
5.173 St. Vincent and the Grenadines 337
5.174 Sudan 338
5.175 Suriname 338
5.176 Swaziland 339
5.177 Sweden 339
5.178 Switzerland 340
5.179 Syrian Arab Republic 340
5.180 Taiwan 341
5.181 Tajikistan 342
5.182 Tanzania 342
5.183 Thailand 343
5.184 The Bahamas 343
5.185 The British Virgin Islands 343
5.186 The Cayman Islands 344
5.187 The Falkland Islands 344
5.188 The Gambia 344
5.189 The Netherlands 345
5.190 The Netherlands Antilles 345
5.191 The Northern Mariana Island 345
5.192 The U.S. Virgin Islands 346
5.193 The United Arab Emirates 346
5.194 The United Kingdom 347
5.195 The United States 348
5.196 Togo 349
5.197 Tokelau 349
5.198 Tonga 350
5.199 Trinidad and Tobago 350
5.200 Tunisia 350
5.201 Turkey 351
5.202 Turkmenistan 351
5.203 Tuvalu 352
5.204 Uganda 352
5.205 Ukraine 353
5.206 Uruguay 353
5.207 Uzbekistan 354
5.208 Vanuatu 354
5.209 Venezuela 355
5.210 Vietnam 356
5.211 Wallis and Futuna 356
5.212 Western Sahara 356
5.213 Western Samoa 357
5.214 Yemen 357
5.215 Zambia 357
5.216 Zimbabwe 358
6 DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS 359
6.1 Disclaimers & Safe Harbor 359
6.2 ICON Group International, Inc. User Agreement Provisions 360
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