The 2011 Report on Cement and Concrete Products Manufacturing: World Market Segmentation by City
ICON Group International, January 2011, Pages: 334
Market Potential Estimation Methodology
Overview
This study covers the world outlook for cement and concrete products manufacturing 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 cement and concrete products manufacturing. 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 cement and concrete products manufacturing 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 cement and concrete products manufacturing 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 cement and concrete products manufacturing 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 cement and concrete products manufacturing 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 cement and concrete products manufacturing. 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 cement and concrete products manufacturing. 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 cement and concrete products manufacturing.
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 “cement and concrete products manufacturing” 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 cement and concrete products manufacturing 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 “cement and concrete products manufacturing” as defined by the North American Industrial Classification system or NAICS (pronounced “nakes”). cement and concrete products manufacturing The NAICS code for cement and concrete products manufacturing is 3273. It is for this definition of cement and concrete products manufacturing that the aggregate latent demand estimates are derived. “Cement and concrete products manufacturing” is specifically defined as follows:
3273
Cement and Concrete Product Manufacturing
32731
This industry comprises establishments primarily engaged in manufacturing portland, natural, masonry, pozzalanic, and other hydraulic cements. Cement manufacturing establishments may calcine earths or mine, quarry, manufacture, or purchase lime.
327310
This industry comprises establishments primarily engaged in manufacturing portland, natural, masonry, pozzalanic, and other hydraulic cements. Cement manufacturing establishments may calcine earths or mine, quarry, manufacture, or purchase lime.
3273100
CEMENT, HYDRAULIC (INCLUDING COST OF SHIPPING CONTAINERS)
32731001
Normal portland cement ASTM type I, hydraulic (including cost of shipping containers)
3273100111
Normal portland cement ASTM type I, hydraulic (including cost of shipping containers)
32731002
Portland cement, moderate heat of hydration (moderate sulfate resistance) ASTM type II, hydraulic (including cost of shipping containers)
3273100211
Portland cement, moderate heat of hydration (moderate sulfate resistance) ASTM type II, hydraulic (including cost of shipping containers)
32731003
Other portland hydraulic cements including ASTM type III, ASTM type IV, and ASTM type V
3273100311
Portland cement, high early strength ASTM type III, hydraulic (including cost of shipping containers)
3273100321
Portland cement, high sulfate resistance ASTM type V, hydraulic (including cost of shipping containers)
3273100331
Other portland hydraulic cements (oil well, white cement, blended cements, etc.) including low heat of hydration ASTM type IV (including cost of shipping containers)
32731004
Other cements (including cost of shipping containers)
3273100411
Masonry cement, hydraulic (including cost of shipping containers)
3273100421
Other cements (natural, hydraulic lime, etc.) (including cost of shipping containers)
3273100431
Cement clinker, for sale separately, hydraulic (including cost of shipping containers)
3273101
Cement, hydraulic
327310M
Miscellaneous receipts
327310P
Primary products
327310S
Secondary products
32732
This industry comprises establishments, such as batch plants or mix plants, primarily engaged in manufacturing concrete delivered to a purchaser in a plastic and unhardened state. Ready-mix concrete manufacturing establishments may mine, quarry, or purchase sand and gravel.
327320
This industry comprises establishments, such as batch plants or mix plants, primarily engaged in manufacturing concrete delivered to a purchaser in a plastic and unhardened state. Ready-mix concrete manufacturing establishments may mine, quarry, or purchase sand and gravel.
3273200
READY_MIX CONCRETE
32732001
Ready_mix concrete
3273200100
Ready_mix concrete
3273201
Ready-mixed concrete
327320M
Miscellaneous receipts
327320P
Primary products
327320S
Secondary products
327320SM
Secondary products and miscellaneous receipts
32733
This industry comprises establishments primarily engaged in manufacturing concrete pipe, brick, and block.
327331
This U.S. industry comprises establishments primarily engaged in manufacturing concrete block and brick.
3273310
CONCRETE BLOCK AND BRICK
32733101
Structural block, lightweight units (units made with concrete weighing less than 105 lb per cubic foot) (dry weight)
3273310111
Structural block, lightweight units (units made with concrete weighing less than 105 lb per cubic foot) (dry weight)
32733102
Structural block, mediumweight units (units made with concrete weighing at least 105 lb but less than 125 lb per cubic foot) (dry weight)
3273310211
Structural block, mediumweight units (units made with concrete weighing at least 105 lb but less than 125 lb per cubic foot) (dry weight)
32733103
Structural block, normalweight units (units made with concrete weighing at least 125 lb per cubic foot) (dry weight)
3273310311
Structural block, normalweight units (units made with concrete weighing at least 125 lb per cubic foot) (dry weight)
32733104
Decorative block (including screen block, split block, slump block, shadowal block, etc.)
3273310411
Decorative block (including screen block, split block, slump block, shadowal block, etc.)
32733105
Concrete pavers (including grid, interlocking, etc.)
3273310511
Concrete pavers (including grid, interlocking, etc.)
32733106
Concrete brick
3273310611
Concrete brick
32733112
Structural block, medium weight units (weighing at least 105 lbs but less than 12
32733113
Structural block, normal weight units (weighing 125 lbs or more)
32733114
Decorative block (such as screen, split, slump, shadowal, etc)
32733115
Concrete pavers (incl. grind, interlocking, etc.)
32733116
Concrete brick
327331M
Miscellaneous receipts
327331P
Primary products
327331S
Secondary products
327331SM
Secondary products and miscellaneous receipts
327332
This U.S. industry comprises establishments primarily engaged in manufacturing concrete pipe.
3273320
CONCRETE PIPE
32733201
Concrete culvert pipe
3273320111
Concrete reinforced culvert pipe, 36 inches or more
3273320121
Concrete reinforced culvert pipe, less than 36 inches
3273320131
Concrete nonreinforced culvert pipe
32733202
Concrete storm sewer pipe
3273320211
Concrete reinforced storm sewer pipe, 36 inches or more
3273320221
Concrete reinforced storm sewer pipe, less than 36 inches
3273320231
Concrete nonreinforced storm sewer pipe
32733203
Concrete pipe, except concrete culvert pipe and concrete storm sewer pipe
3273320311
Concrete reinforced sanitary sewer pipe, 24 inches or more
3273320321
Concrete reinforced sanitary sewer pipe, less than 24 inches
3273320331
Concrete nonreinforced sanitary sewer pipe
3273320341
Reinforced concrete pressure pipe
3273320351
Prestressed concrete cylinder pressure pipe
3273320361
Pretensioned concrete cylinder pipe and other pressure pipe
3273320371
Concrete irrigation pipe and drain tile
3273320381
Other concrete pipe (such as manholes and conduits)
3273321
Concrete pipe
32733211
Concrete culvert pipe
32733212
Concrete storm sewer pipe
32733213
Concrete pipe, except concrete culvert and storm sewer pipe
327332M
Miscellaneous receipts
327332P
Primary products
327332S
Secondary products
327332SM
Secondary products and miscellaneous receipts
32739
This industry comprises establishments primarily engaged in manufacturing concrete products (except block, brick, and pipe).
327390
This industry comprises establishments primarily engaged in manufacturing concrete products (except block, brick, and pipe).
3273901
Precast concrete products
32739011
Precast concrete slabs and tile, roof and floor units
3273901111
Slabs and tile, roof and floor units
32739012
Precast concrete architectural wall panels
3273901211
Architectural wall panels
32739013
Burial vaults and boxes, precast concrete
3273901311
Burial vaults, precast concrete
3273901321
Burial boxes, precast concrete
3273901331
Burial vaults and boxes
32739014
Precast concrete products, except burial vaults and boxes, concrete slabs and tile, and architectural wall panels
3273901411
Precast concrete joists and beams, roof and floor units
3273901421
Precast concrete piling, posts, and poles
3273901431
Precast concrete stone products for architectural purposes (except architectural wall panels, such as window sills, ashlar, etc.)
3273901441
Precast concrete, prefabricated building systems, primarily concrete, sold as complete units, and shipped in panel or modular form
3273901451
Other precast concrete construction or building products (including prefabricated housing components)
3273901461
Septic tanks, precast concrete
3273901471
Other precast concrete products (except construction or building products)
3273901481
Other precast concrete products n.e.c.
3273904
Prestressed concrete products
32739041
Prestressed concrete bridge beams
3273904111
Bridge beams
32739042
Prestressed concrete solid and hollow cored slabs and panels
3273904211
Solid and hollow cored slabs and panels
32739043
Prestressed concrete products, except bridge beams and solid and hollow cored slabs and panels
3273904311
Prestressed concrete single tees, double tees, and channels
3273904321
Prestressed concrete piling, bearing piles, and sheet piles
3273904331
Prestressed concrete joists, girders, and beams (other than bridge beams)
3273904341
Other prestressed concrete products (including arches, columns, etc.)
3273904351
Other prestressed concrete products n.e.c.
327390M
Miscellaneous receipts
327390P
Primary products
327390S
Secondary products
327390SM
Secondary products and miscellaneous receipts
Step 2. Filtering and Smoothing
Based on the aggregate view of cement and concrete products manufacturing 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 cement and concrete products manufacturing 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 cement and concrete products manufacturing 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 cement and concrete products manufacturing). 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. User Agreement Provisions
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