The 2011 Report on Test Equipment for Testing Electrical, Radio and Communication Circuits, and Motors: World Market Segmentation by City

Market Potential Estimation Methodology Overview This study covers the world outlook for test equipment for testing electrical, radio and communication circuits, and motors 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 test equipment for testing electrical, radio and communication circuits, and motors. 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 test equipment for testing electrical, radio and communication circuits, and motors 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 test equipment for testing electrical, radio and communication circuits, and motors 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 test equipment for testing electrical, radio and communication circuits, and motors 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 test equipment for testing electrical, radio and communication circuits, and motors 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 test equipment for testing electrical, radio and communication circuits, and motors. 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 test equipment for testing electrical, radio and communication circuits, and motors. 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 test equipment for testing electrical, radio and communication circuits, and motors. 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 “test equipment for testing electrical, radio and communication circuits, and motors” 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 test equipment for testing electrical, radio and communication circuits, and motors 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 “test equipment for testing electrical, radio and communication circuits, and motors” as defined by the North American Industrial Classification system or NAICS (pronounced “nakes”). test equipment for testing electrical, radio and communication circuits, and motors The NAICS code for test equipment for testing electrical, radio and communication circuits, and motors is 3345153. It is for this definition of test equipment for testing electrical, radio and communication circuits, and motors that the aggregate latent demand estimates are derived. “Test equipment for testing electrical, radio and communication circuits, and motors” is specifically defined as follows: 3345153 Test equipment for testing electrical, radio & communication circuits, & motors  33451530 Test equipment for testing electrical, radio and communication circuits, and motors, except portable instrument transformers  3345153000 Test equipment for testing electrical, radio and communication circuits, and motors, except portable instrument transformers  3345153001 Digital electronic, voltage, current, and resistance measuring equipment, excluding multimeters  3345153003 Analog electronic, voltage, current, and resistance measuring equipment, excluding multimeters  3345153005 Electrical voltage, current, and resistance measuring equipment, excluding panel meters  3345153007 Electronic multimeters, digital and analog  3345153009 Electrical multimeters  3345153011 Electronic analog power and energy measuring equipment  3345153013 Electronic digital power and energy measuring equipment  3345153015 Electrical power and energy measuring equipment, excluding electrical integrating instruments sold separately  3345153017 Universal frequency counters and timers with interval measuring capability  3345153019 All other frequency counters  3345153021 Frequency meters  3345153023 All other frequency counters and timers  3345153025 Waveform measuring or analyzing oscilloscopes and plug~in accessories  3345153027 Waveform spectrum analyzers  3345153029 All other waveform measuring or analyzing equipment  3345153031 Audio signal generating equipment  3345153033 RF signal generating equipment, over 20kc to 890 megacycles  3345153035 Microwave signal generating equipment, 890 megacycles and above  3345153037 Electronic field strength and intensity measuring equipment, including RFI measuring equipment  3345153039 Electrical field strength and intensity measuring equipment, including RFI measuring equipment  3345153043 Electronic impedance and related measuring equipment  3345153045 Standing wave measuring equipment  3345153047 Electronic X~Y plotters (recorders)  3345153049 Combination or group automatic test and measuring equipment  3345153051 Electron tube test sets  3345153053 Semiconductor component memory test sets  3345153055 Semiconductor component linear test sets  3345153057 Semiconductor component microprocessor test sets  3345153059 All other semiconductor component test equipment  3345153061 Circuit board loaded test equipment  3345153063 All other component test sets for automatic test and measuring equipment  3345153065 Equipment and subassembly test and measuring equipment  3345153067 Electronic standards and calibration equipment for test measuring equipment  3345153069 Electrical standards and calibration equipment for test measuring equipment  3345153071 Portable analyzers for testing characteristics of internal~combustion engines, excluding aircraft  3345153073 All other analyzers for testing characteristics of internal~combustion engines, excluding aircraft  3345153075 Communication network analyzers  3345153077 Communication cable backplane and other continuity testers  3345153079 Fiber optics (OTDR, optical S~N meters) communications test equipment, nec  3345153081 All other communications test, monitoring, and control equipment, excluding microwave  3345153083 Microwave communications test equipment, nec, 1,300 MHZ and above  3345153085 Logic analyzers, similar logic state, timing, and signature analyzers  3345153087 Microprocessor development systems  3345153089 Pulse, function, data generators, and similar metered frequency synthesizers  3345153091 Other field service test and measurement equipment, logic probes, clips, and pulsers  3345153093 All other measuring and checking instruments for testing electrical, radio, and communication circuits and motors  3345153095 All other analyzing instruments for checking electrical quantities  3345153097 Parts and components for test equipment for testing electrical, radio and communication circuits and motors (sold separately)  33451531 Automatic test and measurement equipment  3345153100 Test equipment for testing electrical, radio, and communication circuits, and motors (except portable instrument transformers)  3345153101 Test equipment for electrical and radio and communication circuits and motors, voltage, current, and resistance measuring equipment (excluding multimeters), electronic, digital  3345153103 Test equipment for electrical and radio and communication circuits and motors, voltage, current, and resistance measuring equipment (excluding multimeters), electronic, analog  3345153105 Test equipment for electrical and radio and communication circuits and motors, voltage, current, and resistance measuring equipment (excluding multimeters), electrical (excluding panel meters)  3345153107 Test equipment for electrical and radio and communication circuits and motors, multimeters, electronic, digital and analog  3345153109 Test equipment for electrical and radio and communication circuits and motors, multimeters, electrical  334515311 Combination and/or group test sets  3345153114 Test equipment for electrical and radio and communication circuits and motors, power and energy measuring equipment, electronic, digital and analog  3345153115 Test equipment for electrical and radio and communication circuits and motors, power and energy measuring equipment, electrical  3345153118 Test equipment for electrical and radio and communication circuits and motors, frequency counters, timers, and other frequency and time measuring equipment (excluding standards)  334515312 Semiconductor component test equipment  3345153126 Test equipment for electrical and radio and communication circuits and motors, waveform measuring and/or analyzing equipment (including oscilloscopes and spectrum analyzers)  334515313 Other automatic test and measurement equipment  3345153131 Test equipment for electrical and radio and communication circuits and motors, signal generating equipment, audio  3345153133 Test equipment for electrical and radio and communication circuits and motors, signal generating equipment, RF (over 20 kc to 890 megacycles)  3345153135 Test equipment for electrical and radio and communication circuits and motors, signal generating equipment, microwave (890 megacycles and above)  3345153137 Test equipment for electrical and radio and communication circuits and motors, field strength and intensity measuring equipment (including RFI measuring equipment), electronic  3345153139 Test equipment for electrical and radio and communication circuits and motors, field strength and intensity measuring equipment (including RFI measuring equipment), electrical  3345153143 Test equipment for electrical and radio and communication circuits and motors, impedance and standing wave ratio measuring equipment (transfer function measuring equipment), electronic  3345153149 Test equipment for electrical and radio and communication circuits and motors, automatic test and measuring equipment, combination and/or group test sets  3345153151 Test equipment for electrical and radio and communication circuits and motors, automatic test and measuring equipment, component part test sets, electron tube test equipment  3345153153 Test equipment for electrical and radio and communication circuits and motors, automatic test and measuring equipment, component part test sets, semiconductor component test equipment, memory  3345153155 Test equipment for electrical and radio and communication circuits and motors, automatic test and measuring equipment, component part test sets, semiconductor component test equipment, linear  3345153157 Test equipment for electrical and radio and communication circuits and motors, automatic test and measuring equipment, component part test sets, semiconductor component test equipment, microprocessor  3345153159 Test equipment for electrical and radio and communication circuits and motors, automatic test and measuring equipment, component part test sets, semiconductor component test equipment, other  3345153161 Test equipment for electrical and radio and communication circuits and motors, automatic test and measuring equipment, component part test sets, circuit board loaded test equipment  3345153163 Test equipment for electrical and radio and communication circuits and motors, automatic test and measuring equipment, component part test sets, other  3345153165 Test equipment for electrical and radio and communication circuits and motors, automatic test and measuring equipment, all other equipment and subassembly test equipment (disc drive testers, etc.)  3345153168 Standards and calibration equipment for test measuring equipment, including laboratory types (metered bench_top, rack_mountable, or plug_in equipment)  3345153171 Test equipment for electrical and radio and communication circuits and motors, analyzers for testing characteristics of internal_combustion engines (excluding aircraft), portable  3345153173 Test equipment for electrical and radio and communication circuits and motors, analyzers for testing characteristics of internal_combustion engines (excluding aircraft), other  3345153175 Test equipment for electrical and radio and communication circuits and motors, all other communications test equipment, network analyzers  3345153177 Test equipment for electrical and radio and communication circuits and motors, all other communications test equipment, cable backplane and other continuity testers  3345153179 Test equipment for electrical and radio and communication circuits and motors, all other communications test equipment, fiber optics test equipment (OTDR, optical S/N meters, etc.)  3345153181 Test equipment for electrical and radio and communication circuits and motors, all other communications test equipment, other (excluding microwave)  3345153183 Test equipment for electrical and radio and communication circuits and motors, all other communications test equipment, all other microwave test equipment (1300 MHZ and above)  3345153185 Test equipment for electrical and radio and communication circuits and motors, logic analyzers and similar logic state, timing, and signature analyzers  3345153187 Test equipment for electrical and radio and communication circuits and motors, microprocessor development systems  3345153189 Test equipment for electrical and radio and communication circuits and motors, pulse, function, and data generators and similar metered frequency synthesizers  3345153191 Test equipment for electrical and radio and communication circuits and motors, other field service test and measurement equipment, logic probes, clips, and pulsers  3345153193 Other measuring and checking instruments for test equipment for testing electrical and radio and communication circuits and motors  3345153195 Other analyzing instruments for checking electrical quantities  3345153197 Parts and components for test equipment for testing electrical and radio and communication circuits and motors (sold separately)  33451532 Communications test equipment  33451533 Other test equipment for electric circuits and motors, including parts   Step 2. Filtering and Smoothing Based on the aggregate view of test equipment for testing electrical, radio and communication circuits, and motors 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 test equipment for testing electrical, radio and communication circuits, and motors 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 test equipment for testing electrical, radio and communication circuits, and motors 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 test equipment for testing electrical, radio and communication circuits, and motors). 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 1.1 Overview and Definitions 1.2 Market Potential Estimation Methodology 1.2.1 Overview 1.2.2 What is Latent Demand and the P.I.E.? 1.2.3 The Methodology 1.2.3.1 Step 1. Product Definition and Data Collection 1.2.3.2 Step 2. Filtering and Smoothing 1.2.3.3 Step 3. Filling in Missing Values 1.2.3.4 Step 4. Varying Parameter, Non-linear Estimation 1.2.3.5 Step 5. Fixed-Parameter Linear Estimation 1.2.3.6 Step 6. Aggregation and Benchmarking 2 USING THE DATA 3 CITY SEGMENTS RANKED BY MARKET SIZE 3.1 Top 15 Markets 3.2 Markets 16 to 30 3.3 Remaining Cities by Market Rank 4 CITY SEGMENTS IN ALPHABETICAL ORDER 4.1 A: from Aalborg to Az Zawiyah 4.2 B: from Bacolod to Bydgoszcz 4.3 C: from Caaguazu to Cyangugu 4.4 D: from Da Nang to Dzhizak 4.5 E: from East London to Esteli 4.6 F: from Fagatogo to Funchal 4.7 G: from Gabes to Gyumri 4.8 H: from Hachinohe to Hyderabad 4.9 I: from Iasi to Izmir 4.10 J: from Jaboatao to Jyvaskyla 4.11 K: from Kabul to Kzyl-Orda 4.12 L: from La Ceiba to Lyon 4.13 M: from Macae to Mzuzu 4.14 N: from Nacala to Nzerekore 4.15 O: from Oaklahoma City to Oyem 4.16 Ö: from Örebro to Örebro 4.17 P: from Pago Pago to Pyuthan 4.18 Q: from Qandahar to Quito 4.19 R: from Rabat to Rustavi 4.20 S: from S. Luis Potosi to Szombathely 4.21 T: from Tabligbo to Tyre 4.22 U: from Uberaba to Utulei 4.23 V: from Vacoas-Phoenix to Vukovar 4.24 W: from Wadi Medani to Wuhan 4.25 X: from Xalapa to Xi'an 4.26 Y: from Yamagata to Yungkang 4.27 Z: from Zadar to Zvishavane 5 CITY SEGMENTS RANKED BY COUNTRY 5.1 Afghanistan 5.2 Albania 5.3 Algeria 5.4 American Samoa 5.5 Andorra 5.6 Angola 5.7 Antigua and Barbuda 5.8 Argentina 5.9 Armenia 5.10 Aruba 5.11 Australia 5.12 Austria 5.13 Azerbaijan 5.14 Bahrain 5.15 Bangladesh 5.16 Barbados 5.17 Belarus 5.18 Belgium 5.19 Belize 5.20 Benin 5.21 Bermuda 5.22 Bhutan 5.23 Bolivia 5.24 Bosnia and Herzegovina 5.25 Botswana 5.26 Brazil 5.27 Brunei 5.28 Bulgaria 5.29 Burkina Faso 5.30 Burma 5.31 Burundi 5.32 Cambodia 5.33 Cameroon 5.34 Canada 5.35 Cape Verde 5.36 Central African Republic 5.37 Chad 5.38 Chile 5.39 China 5.40 Christmas Island 5.41 Colombia 5.42 Comoros 5.43 Congo (formerly Zaire) 5.44 Cook Islands 5.45 Costa Rica 5.46 Cote d'Ivoire 5.47 Croatia 5.48 Cuba 5.49 Cyprus 5.50 Czech Republic 5.51 Denmark 5.52 Djibouti 5.53 Dominica 5.54 Dominican Republic 5.55 Ecuador 5.56 Egypt 5.57 El Salvador 5.58 Equatorial Guinea 5.59 Estonia 5.60 Ethiopia 5.61 Fiji 5.62 Finland 5.63 France 5.64 French Guiana 5.65 French Polynesia 5.66 Gabon 5.67 Georgia 5.68 Germany 5.69 Ghana 5.70 Greece 5.71 Greenland 5.72 Grenada 5.73 Guadeloupe 5.74 Guam 5.75 Guatemala 5.76 Guinea 5.77 Guinea-Bissau 5.78 Guyana 5.79 Haiti 5.80 Honduras 5.81 Hong Kong 5.82 Hungary 5.83 Iceland 5.84 India 5.85 Indonesia 5.86 Iran 5.87 Iraq 5.88 Ireland 5.89 Israel 5.90 Italy 5.91 Jamaica 5.92 Japan 5.93 Jordan 5.94 Kazakhstan 5.95 Kenya 5.96 Kiribati 5.97 Kuwait 5.98 Kyrgyzstan 5.99 Laos 5.100 Latvia 5.101 Lebanon 5.102 Lesotho 5.103 Liberia 5.104 Libya 5.105 Liechtenstein 5.106 Lithuania 5.107 Luxembourg 5.108 Macau 5.109 Madagascar 5.110 Malawi 5.111 Malaysia 5.112 Maldives 5.113 Mali 5.114 Malta 5.115 Marshall Islands 5.116 Martinique 5.117 Mauritania 5.118 Mauritius 5.119 Mexico 5.120 Micronesia Federation 5.121 Moldova 5.122 Monaco 5.123 Mongolia 5.124 Morocco 5.125 Mozambique 5.126 Namibia 5.127 Nauru 5.128 Nepal 5.129 New Caledonia 5.130 New Zealand 5.131 Nicaragua 5.132 Niger 5.133 Nigeria 5.134 Niue 5.135 Norfolk Island 5.136 North Korea 5.137 Norway 5.138 Oman 5.139 Pakistan 5.140 Palau 5.141 Palestine 5.142 Panama 5.143 Papua New Guinea 5.144 Paraguay 5.145 Peru 5.146 Philippines 5.147 Poland 5.148 Portugal 5.149 Puerto Rico 5.150 Qatar 5.151 Republic of Congo 5.152 Reunion 5.153 Romania 5.154 Russia 5.155 Rwanda 5.156 San Marino 5.157 Sao Tome E Principe 5.158 Saudi Arabia 5.159 Senegal 5.160 Seychelles 5.161 Sierra Leone 5.162 Singapore 5.163 Slovakia 5.164 Slovenia 5.165 Solomon Islands 5.166 Somalia 5.167 South Africa 5.168 South Korea 5.169 Spain 5.170 Sri Lanka 5.171 St. Kitts and Nevis 5.172 St. Lucia 5.173 St. Vincent and the Grenadines 5.174 Sudan 5.175 Suriname 5.176 Swaziland 5.177 Sweden 5.178 Switzerland 5.179 Syrian Arab Republic 5.180 Taiwan 5.181 Tajikistan 5.182 Tanzania 5.183 Thailand 5.184 The Bahamas 5.185 The British Virgin Islands 5.186 The Cayman Islands 5.187 The Falkland Islands 5.188 The Gambia 5.189 The Netherlands 5.190 The Netherlands Antilles 5.191 The Northern Mariana Island 5.192 The U.S. Virgin Islands 5.193 The United Arab Emirates 5.194 The United Kingdom 5.195 The United States 5.196 Togo 5.197 Tokelau 5.198 Tonga 5.199 Trinidad and Tobago 5.200 Tunisia 5.201 Turkey 5.202 Turkmenistan 5.203 Tuvalu 5.204 Uganda 5.205 Ukraine 5.206 Uruguay 5.207 Uzbekistan 5.208 Vanuatu 5.209 Venezuela 5.210 Vietnam 5.211 Wallis and Futuna 5.212 Western Sahara 5.213 Western Samoa 5.214 Yemen 5.215 Zambia 5.216 Zimbabwe 6 DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS 6.1 Disclaimers & Safe Harbor 6.2 ICON Group International, Inc. 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