The 2009 Report on Manufacturing Dental Equipment and Supplies, Dental Chairs, Dental Instrument Delivery Systems, Dental Hand Instruments, and Dental Impression Material: World Market Segmentation by City
ICON Group International, May 2009, Pages: 353
Market Potential Estimation Methodology
Overview
This study covers the world outlook for manufacturing dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material 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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material. 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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material 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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material 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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material 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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material 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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material. 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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material. 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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material.
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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material” 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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material 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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material” as defined by the North American Industrial Classification system or NAICS (pronounced “nakes”). For a complete definition of manufacturing dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material, please refer to the Web site at http://www.icongrouponline.com/codes/NAICS.html. The NAICS code for manufacturing dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material is 339114. It is for this definition of manufacturing dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material that the aggregate latent demand estimates are derived. “Manufacturing dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material” is specifically defined as follows:
339114
This U.S. industry comprises establishments primarily engaged in manufacturing dental equipment and supplies used by dental laboratories and offices of dentists, such as dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material and dental cements.
3391141
DENTAL PROFESSIONAL EQUIPMENT AND SUPPLIES
33911411
Dental professional equipment
3391141101
Dental chairs
3391141106
Dental instrument delivery systems (dental units)
3391141111
Dental hand pieces
3391141116
Dental hand instruments, including broaches, cutting instruments, forceps, and pliers
3391141121
Other dental professional equipment, including dental lasers (excluding X_ray equipment)
33911412
Dental professional supplies
3391141226
Dental tools for use with dental hand pieces, including burs, disks, abrasive points, diamond points, and wheels
3391141231
Dental alloys for amalgams
3391141236
Dental impression materials, including alginates and silicones
3391141241
Dental cements and other nonmetallic filling materials
3391141246
Other dental professional supplies
3391143
DENTAL LABORATORY EQUIPMENT AND SUPPLIES
33911431
Dental laboratory equipment and supplies
3391143101
Dental laboratory equipment, including benches, blow pipes, casting machines, flasks, furnaces, lathes, polishing units, and presses
3391143106
Precious dental metals, including gold, platinum, and silver
3391143111
Nonprecious dental metals
3391143116
Artificial teeth not customized for individual application, excluding dentures
3391143121
Other dental laboratory supplies, including gypsums and waxes, bridges, crowns, dentures, and other orthodontic appliances (except artificial teeth) not customized for individual application
3391145
Dental professional equipment and supplies
339114511
Dental professional equip., incl. dental chairs, units, hand pieces, excl. X-ray
33911452
Dental professional supplies
3391146
Dental laboratory equipment and supplies
339114M
Miscellaneous receipts
339114P
Primary products
339114S
Secondary products
339114SM
Secondary products and miscellaneous receipts
Furthermore, the definition of NAICS code 339114 includes the following:
Abrasive points, wheels, and disks, dental, manufacturing
Amalgams, dental, manufacturing
Autoclaves, dental, manufacturing
Cements, dental, manufacturing
Chairs, dentists, manufacturing
Cutting instruments, dental, manufacturing
Dental alloys for amalgams manufacturing
Dental chairs manufacturing
Dental equipment and instruments manufacturing
Dental glues and cements manufacturing
Dental hand instruments (e.g., forceps) manufacturing
Dental impression materials manufacturing
Dental instrument delivery systems manufacturing
Dental laboratory equipment manufacturing
Dental wax manufacturing
Denture materials manufacturing
Drills, dental, manufacturing
Enamels, dental, manufacturing
Furnaces, dental laboratory, manufacturing
Glue, dental, manufacturing
Impression material, dental, manufacturing
Orthodontic appliances manufacturing
Points, abrasive dental, manufacturing
Sterilizers, dental, manufacturing
Teeth (except customized) manufacturing
Tools, dentists, manufacturing
Ultrasonic dental equipment manufacturing.
Step 2. Filtering and Smoothing
Based on the aggregate view of manufacturing dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material 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 dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material 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 the pool of African cities).
This approach is useful across cities for which some notion of non-linearity exists in the aggregate consumption function. For some categories, however, the reader must realize that the numbers will reflect a city’s contribution to global latent demand and may never be realized in the form of local sales. For certain category combinations this will result in what at first glance will be odd results. For example, the latent demand for the category “space vehicles” will exist for cities in “Togo” even though they have no space program. The assumption is that if the economies in these countries did not exist, the world aggregate for these categories would be lower. The share attributed to these cities is based on a proportion of their income (however small) being used to consume the category in question (i.e., perhaps via resellers).
Step 5. Fixed-Parameter Linear Estimation
Nonlinearities are assumed in cases where filtered data exist along the aggregate consumption function. Because the world consists of more than 2000 cities, there will always be those cities, especially toward the bottom of the consumption function, where non-linear estimation is simply not possible. For these cities, equilibrium latent demand is assumed to be perfectly parametric and not a function of wealth (i.e., a city’s stock of income), but a function of current income (a city’s flow of income). In the long run, if a city has no current income, the latent demand for manufacturing dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material is assumed to approach zero. The assumption is that wealth stocks fall rapidly to zero if flow income falls to zero (i.e., cities which earn low levels of income will not use their savings, in the long run, to demand manufacturing dental equipment and supplies, dental chairs, dental instrument delivery systems, dental hand instruments, and dental impression material). In a graphical sense, for low income cities, latent demand approaches zero in a parametric linear fashion with a zero-zero intercept. In this stage of the estimation procedure, low-income cities are assumed to have a latent demand proportional to their income, based on the city closest to it on the aggregate consumption function.
Step 6. Aggregation and Benchmarking
Based on the models described above, latent demand figures are estimated for all cities of the world, including for the smallest economies. These are then aggregated to get world totals and regional totals. To make the numbers more meaningful, regional and global demand averages are presented. Figures are rounded, so minor inconsistencies may exist across tables.
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 17
1.2.3.3 Step 3. Filling in Missing Values 17
1.2.3.4 Step 4. Varying Parameter, Non-linear Estimation 18
1.2.3.5 Step 5. Fixed-Parameter Linear Estimation 18
1.2.3.6 Step 6. Aggregation and Benchmarking 19
2 USING THE DATA 20
3 CITY SEGMENTS RANKED BY MARKET SIZE 21
3.1 Top 15 Markets 21
3.2 Markets 16 to 30 22
3.3 Remaining Cities by Market Rank 23
4 CITY SEGMENTS IN ALPHABETICAL ORDER 126
4.1 A: from Aalborg to Az Zawiyah 126
4.2 B: from Bacolod to Bydgoszcz 133
4.3 C: from Caaguazu to Cyangugu 141
4.4 D: from Da Nang to Dzhizak 149
4.5 E: from East London to Esteli 153
4.6 F: from Fagatogo to Funchal 155
4.7 G: from Gabes to Gyumri 158
4.8 H: from Hachinohe to Hyderabad 162
4.9 I: from Iasi to Izmir 166
4.10 J: from Jaboatao to Jyvaskyla 169
4.11 K: from Kabul to Kzyl-Orda 172
4.12 L: from La Ceiba to Lyon 180
4.13 M: from Macae to Mzuzu 186
4.14 N: from Nacala to Nzerekore 196
4.15 O: from Oaklahoma City to Oyem 201
4.16 Ö: from Örebro to Örebro 203
4.17 P: from Pago Pago to Pyuthan 204
4.18 Q: from Qandahar to Quito 211
4.19 R: from Rabat to Rustavi 212
4.20 S: from S. Luis Potosi to Szombathely 215
4.21 T: from Tabligbo to Tyre 227
4.22 U: from Uberaba to Utulei 234
4.23 V: from Vacoas-Phoenix to Vukovar 236
4.24 W: from Wadi Medani to Wuhan 239
4.25 X: from Xalapa to Xian 240
4.26 Y: from Yamagata to Yungkang 241
4.27 Z: from Zadar to Zvishavane 242
5 CITY SEGMENTS RANKED BY COUNTRY 243
5.1 Afghanistan 243
5.2 Albania 243
5.3 Algeria 244
5.4 American Samoa 244
5.5 Andorra 245
5.6 Angola 245
5.7 Antigua and Barbuda 245
5.8 Argentina 246
5.9 Armenia 247
5.10 Aruba 247
5.11 Australia 248
5.12 Austria 248
5.13 Azerbaijan 249
5.14 Bahrain 249
5.15 Bangladesh 250
5.16 Barbados 250
5.17 Belarus 251
5.18 Belgium 251
5.19 Belize 252
5.20 Benin 252
5.21 Bermuda 252
5.22 Bhutan 253
5.23 Bolivia 253
5.24 Bosnia and Herzegovina 254
5.25 Botswana 254
5.26 Brazil 255
5.27 Brunei 260
5.28 Bulgaria 261
5.29 Burkina Faso 261
5.30 Burma 262
5.31 Burundi 262
5.32 Cambodia 262
5.33 Cameroon 263
5.34 Canada 263
5.35 Cape Verde 264
5.36 Central African Republic 264
5.37 Chad 265
5.38 Chile 265
5.39 China 266
5.40 Christmas Island 266
5.41 Colombia 267
5.42 Comoros 267
5.43 Congo (formerly Zaire) 268
5.44 Cook Islands 268
5.45 Costa Rica 269
5.46 Cote dIvoire 269
5.47 Croatia 270
5.48 Cuba 270
5.49 Cyprus 271
5.50 Czech Republic 271
5.51 Denmark 272
5.52 Djibouti 272
5.53 Dominica 273
5.54 Dominican Republic 273
5.55 Ecuador 274
5.56 Egypt 274
5.57 El Salvador 275
5.58 Equatorial Guinea 275
5.59 Estonia 275
5.60 Ethiopia 276
5.61 Fiji 276
5.62 Finland 277
5.63 France 277
5.64 French Guiana 278
5.65 French Polynesia 278
5.66 Gabon 278
5.67 Georgia 279
5.68 Germany 279
5.69 Ghana 280
5.70 Greece 280
5.71 Greenland 281
5.72 Grenada 281
5.73 Guadeloupe 282
5.74 Guam 282
5.75 Guatemala 283
5.76 Guinea 283
5.77 Guinea-Bissau 283
5.78 Guyana 284
5.79 Haiti 284
5.80 Honduras 285
5.81 Hong Kong 285
5.82 Hungary 286
5.83 Iceland 286
5.84 India 287
5.85 Indonesia 288
5.86 Iran 289
5.87 Iraq 289
5.88 Ireland 290
5.89 Israel 290
5.90 Italy 291
5.91 Jamaica 291
5.92 Japan 292
5.93 Jordan 295
5.94 Kazakhstan 295
5.95 Kenya 296
5.96 Kiribati 296
5.97 Kuwait 296
5.98 Kyrgyzstan 297
5.99 Laos 297
5.100 Latvia 297
5.101 Lebanon 298
5.102 Lesotho 298
5.103 Liberia 298
5.104 Libya 299
5.105 Liechtenstein 299
5.106 Lithuania 300
5.107 Luxembourg 300
5.108 Macau 300
5.109 Madagascar 301
5.110 Malawi 301
5.111 Malaysia 302
5.112 Maldives 302
5.113 Mali 303
5.114 Malta 303
5.115 Marshall Islands 303
5.116 Martinique 304
5.117 Mauritania 304
5.118 Mauritius 305
5.119 Mexico 306
5.120 Micronesia Federation 307
5.121 Moldova 307
5.122 Monaco 307
5.123 Mongolia 308
5.124 Morocco 308
5.125 Mozambique 309
5.126 Namibia 309
5.127 Nauru 309
5.128 Nepal 310
5.129 New Caledonia 310
5.130 New Zealand 311
5.131 Nicaragua 311
5.132 Niger 312
5.133 Nigeria 312
5.134 Niue 313
5.135 Norfolk Island 313
5.136 North Korea 313
5.137 Norway 314
5.138 Oman 314
5.139 Pakistan 315
5.140 Palau 315
5.141 Palestine 315
5.142 Panama 316
5.143 Papua New Guinea 316
5.144 Paraguay 317
5.145 Peru 317
5.146 Philippines 318
5.147 Poland 319
5.148 Portugal 319
5.149 Puerto Rico 320
5.150 Qatar 320
5.151 Republic of Congo 321
5.152 Reunion 321
5.153 Romania 322
5.154 Russia 322
5.155 Rwanda 323
5.156 San Marino 323
5.157 Sao Tome E Principe 323
5.158 Saudi Arabia 324
5.159 Senegal 324
5.160 Seychelles 325
5.161 Sierra Leone 325
5.162 Singapore 325
5.163 Slovakia 326
5.164 Slovenia 326
5.165 Solomon Islands 326
5.166 Somalia 327
5.167 South Africa 327
5.168 South Korea 328
5.169 Spain 329
5.170 Sri Lanka 329
5.171 St. Kitts and Nevis 330
5.172 St. Lucia 330
5.173 St. Vincent and the Grenadines 330
5.174 Sudan 331
5.175 Suriname 331
5.176 Swaziland 332
5.177 Sweden 332
5.178 Switzerland 333
5.179 Syrian Arab Republic 333
5.180 Taiwan 334
5.181 Tajikistan 335
5.182 Tanzania 335
5.183 Thailand 336
5.184 The Bahamas 336
5.185 The British Virgin Islands 336
5.186 The Cayman Islands 337
5.187 The Falkland Islands 337
5.188 The Gambia 337
5.189 The Netherlands 338
5.190 The Netherlands Antilles 338
5.191 The Northern Mariana Island 338
5.192 The U.S. Virgin Islands 339
5.193 The United Arab Emirates 339
5.194 The United Kingdom 340
5.195 The United States 341
5.196 Togo 342
5.197 Tokelau 342
5.198 Tonga 343
5.199 Trinidad and Tobago 343
5.200 Tunisia 343
5.201 Turkey 344
5.202 Turkmenistan 344
5.203 Tuvalu 345
5.204 Uganda 345
5.205 Ukraine 346
5.206 Uruguay 346
5.207 Uzbekistan 347
5.208 Vanuatu 347
5.209 Venezuela 348
5.210 Vietnam 349
5.211 Wallis and Futuna 349
5.212 Western Sahara 349
5.213 Western Samoa 350
5.214 Yemen 350
5.215 Zambia 350
5.216 Zimbabwe 351
6 DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS 352
6.1 Disclaimers & Safe Harbor 352
6.2 ICON Group International, Inc. User Agreement Provisions 353
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